Nov 13, 2019 | Volume 9 - Issue 4
Katherine E. Purswell
The purpose of this paper is to explain how humanistic learning theory is applicable to current counselor education practices. A review of humanistic learning theory and the rationale for the application of the learning theory to counselor education provide a framework for application of these concepts to counselor education classrooms. Specifically, a person-centered framework is applied to the seeming incompatibility of external accreditation standards and humanistic learning theory. I propose suggestions for implementing humanistic, person-centered learning theory within counselor education programs and courses, focusing special attention on the attitudes and values of the counselor educator as these principles are applied.
Keywords: humanistic learning theory, person-centered theory, counselor education, accreditation, attitudes
With the philosophical shift in the mental health field from a meaning-making, holistic model of mental health toward a reductionistic, medical model of mental health, counselor preparation programs have adapted by increasing the emphasis on measuring outcomes, sometimes at the expense of focusing on aspects of counseling that are less easy to quantitatively assess (Hansen, 2009). Furthermore, external realities such as university policies and accreditation requirements have put pressure on programs and faculty members to focus more on measurable outcomes. In many counselor education programs, external requirements come in the form of the Council for Accreditation of Counseling and Related Educational Programs (CACREP; 2015) standards. With the advent of the 2009 standards, the focus in counselor education changed from program-level evaluation to directly assessing student outcomes (Barrio Minton & Gibson, 2012), a trend consistent in higher education (Penn, 2011). Although the admirable intention of accountability measures is to ensure quality programs and competent counselors, these systems do not provide incentives for counselor educators employing pedagogy that emphasizes process and critical thinking over product and knowledge retention.
Many counseling faculty ascribe to a humanistic way of viewing people, including students, and the increasing focus on outcomes over process may create dissonance for these counselor educators. They can feel internal as well as external pressure to adopt a more didactic or reductionistic form of teaching that does not fit with their philosophy of education (Hansen, 2009). This paper is directed at person-centered counselor educators who wish to teach in a more humanistic way but feel constrained by the current system. This paper also may be helpful for other counselor educators who wish to explore humanistic teaching. The purpose of this article is to demonstrate that counseling faculty can apply a person-centered learning philosophy to counselor preparation settings within the reality of external requirements intended to ensure quality in counselor preparation programs. Because the person-centered teaching literature is not sufficiently robust to accomplish this purpose, I will also draw from humanistic learning theory. First, I provide an overview and rationale for humanistic learning theory and then discuss the application of person-centered concepts, within the context of humanistic learning theory, to counselor preparation settings. When a view is specifically person-centered, I will use that term. Otherwise, I will refer to humanistic learning theory, which encompasses person-centered learning theory.
Humanistic Learning Theory
Humanistic learning theory is grounded in the philosophy of humanistic theories of psychology, including person-centered theory (Gould, 2012). Primary contributors to humanistic learning theory include Arthur Combs, Carl Rogers, and Malcolm Knowles, all of whom believed the goal of education is to facilitate students’ development and self-actualization (Combs, 1982; Gould, 2012; Rogers, 1951). Therefore, humanist educators have an unwavering trust in the individual’s growth capacity and view self-directed learning as most facilitative of growth (Combs, 1982; Knowles, 1975; Rogers, 1951). Additionally, humanistic theorists hold a phenomenological view of humans in that they believe each person’s view of the world is reality for that person and that learning is motivated by personal need based on one’s internal frame of reference (Combs, 1986; Rogers, 1951). For example, a student with low self-efficacy might not attempt difficult projects because of a belief that “I am not capable,” whereas a student with a high level of self-trust can go beyond the direct instructions of an assignment to tailor the assignment to fit their learning needs. Highly self-actualized individuals view themselves as dynamic beings who are constantly growing and changing (Knowles, 1975; Tolan, 2017).
In general, humanistic learning theorists define learning as the holistic growth of the person, including cognitive, emotional, and interpersonal domains (Combs, 1986; Dollarhide & Granello, 2012; Rogers, 1957, 1989). They tend to focus less on accumulation of knowledge and more on how the learner’s way of being in the world impacts the integration of skills and knowledge (Combs, 1986; Kleiman, 2007). This view of knowing requires a paradigm shift for the person who tends to describe learning as the acquisition and application of knowledge. In particular, learners who have learned to approach assignments or classes with a grade-based mentality (e.g., “What do I need to do to get an ‘A’?”) may have difficulty changing, or even understanding the rationale for changing, their focus to a learning-based mentality (e.g., “What do I need to learn to positively impact my personal and professional development?”).
Humanistic learning theorists avoid teacher-directed learning, defined as transmission of knowledge, because they believe the most important learning and growth cannot be transmitted directly from person to person (Knowles, 1975; Rogers, 1957, 1989). Rather, they believe knowledge integration is a natural process occurring in a facilitative environment (Rogers & Freiberg, 1994). Because learning requires this environment, humanistic educators focus first on themselves and their ability to provide that environment (Combs, 1982; Rogers & Freiberg, 1994). In this article, the term educator is used in the broadest sense of the word to mean a facilitator of learning.
Rogers’s Conditions in Humanistic Learning Theory
Most humanistic learning theorists base their view of the educator–learner relationship on Rogers’s (1957) three therapist-provided conditions for personality change: congruence, empathic understanding, and unconditional positive regard (Combs, 1986; Mearns, 1997; Rogers & Freiberg, 1994). In an educational setting, empathic understanding, which Rogers (1951) considered a sensitive understanding of a person’s internal frame of reference, involves focusing on the person rather than only on course content (Mearns, 1997). For example, the educator also would value and empathize with learners’ reactions to course content as well as other circumstances in learners’ lives that might impact their experience in the class.
Unconditional positive regard is an experience of accepting and prizing another person regardless of whether one agrees or disagrees with the person’s behaviors or ideology (Rogers, 1957). Rogers and Freiberg (1994) described unconditional positive regard as “a basic trust—a belief that this other person is somehow fundamentally trustworthy” (p. 156). This trust differentiates unconditional positive regard from the common use of the term acceptance. In a classroom setting, unconditional positive regard for students can mean valuing and respecting students wherever they are in their growth processes and trusting they are moving toward growth as they are ready or able (Kunze, 2013). For example, if a student struggles to accept feedback in supervision, the counselor educator will accept the student in that moment and trust that there are valid reasons for the student’s difficulty. This acceptance is an attitude and does not mean educators abandon their professional gatekeeping roles.
Congruence, also called transparency in a classroom setting, involves openness to one’s experience within a relationship, including an acceptance of one’s own feelings or desires at any moment, even if one chooses not to act upon those feelings (Mearns, 1997; Rogers, 1951; Rogers & Freiberg, 1994). Transparency is closely tied to a non-defensiveness that promotes openness rather than debate as well as the formation of respectful, trusting relationships between educators and learners (Mearns, 1997). These trusting relationships form the basis for open dialogue.
The result of the interaction between these conditions can be transformational for students in the classroom. When an educator makes a genuine effort to help a learner feel understood rather than evaluated, the learner is more free to stop judging or evaluating oneself and to creatively explore the learning environment with the security of knowing that any ideas, even those that conflict with the educator’s views, will be respectfully acknowledged and discussed (Combs, 1982; Rogers & Freiberg, 1994). Meaningful learning can occur in an environment in which the contributions and ideas of learners are valued just as much as those of the educator (Kleiman, 2007). Humanistic educators strive to provide some level of Rogers’s (1957) three conditions to all learners.
Rationale for Use of Person-Centered Learning Theory
The goal of facilitating relationships in a learning environment characterized by the person-centered conditions of congruence, unconditional positive regard, and empathy is to provide learners with the opportunity for the growth and development of the whole person (Dollarhide & Granello, 2012; Rogers & Freiberg, 1994). Some of the results of such a learning environment are a deeper understanding and acceptance of oneself, a strong connection and openness to the experiences of others, and the development of skills and knowledge to facilitate the growth of both the individual and society. Because of these outcomes, a person-centered approach to learning is an appropriate match for counseling faculty and supervisors who believe these growth processes are key purposes of training counselors (Combs, 1986; Dollarhide & Granello, 2012).
One of the primary goals of counseling faculty is to develop the counselor-in-training’s (CIT’s) belief system about counseling and about oneself as a counselor (Combs, 1986; Gibson, Dollarhide, & Moss, 2010). From a phenomenological perspective, beliefs influence behavior; therefore, person-centered counseling faculty can focus on helping CITs develop their own beliefs about themselves in the context of counseling relationships (Combs, 1986; Dollarhide & Granello, 2012). When counseling faculty facilitate genuine, accepting, and empathic relationships between themselves and learners and among learners, they create an environment in which CITs are free to examine those beliefs that are both more and less accepted by society and then to modify those beliefs in ways that are more helpful (Mearns, 1997). For example, if a CIT holds stereotypical beliefs about a certain population, the CIT will be better able to express and challenge those beliefs in an open rather than judgmental environment.
Additionally, in a person-centered learning environment, CITs develop confidence in their abilities to find creative responses to difficult situations, such as client challenges and ethical dilemmas (Combs, 1986). Alternatively, when CITs feel they must act a certain way, they can learn to say the right words but fail to internalize a belief system that is meaningful to them. Therefore, when they are challenged or when the external evaluator is no longer present, they will quickly fall back into arguably less helpful ways of being with clients, such as giving advice. By offering a person-centered learning environment, counseling faculty help students meet CACREP standards related to facilitating a helping relationship (CACREP, 2015, 2.F.5.).
Relatedly, person-centered counseling faculty can utilize the learning environment as a microcosm of the helping relationship to allow CITs to experience the type of relationships counseling faculty hope they will provide their clients (Combs, 1986). Rogers (1957, 1989) argued that educators may foster the values and attitudes of a helping relationship by providing those same values and attitudes to learners. Although the professor–student relationship differs from the counselor–client relationship, the basic attitudes (care, warmth, prizing), values (worth of the person), and purpose of the relationship (growth) remain the same (Mearns, 1997). Most students in counselor education programs are intelligent and able to accomplish the academic work, but the relational skills necessary for an effective counselor cannot be memorized or studied for (McAuliffe, 2011; Nelson & Neufeldt, 1998). Therefore, it is critical that counseling faculty provide experiences that facilitate the development of relational abilities.
In addition to developing intrapersonally and interpersonally, CITs must develop good judgment and the ability to critically reflect on their counseling practice, including their work with clients and both current and future educational experiences (McAuliffe, 2011; Nelson & Neufeldt, 1998). Both the ACA Code of Ethics (American Counseling Association [ACA], 2014) and many state laws require new and experienced counselors to continue to seek professional development, and students need to be able to evaluate the training they are receiving. Additionally, in their analysis of extensive interviews with master therapists, Skovholt and Rønnestad (1992) found that those therapists considered continual reflection on their experiences and their growth process to be a key aspect of their professional growth. This finding supports King and Kitchner’s (2004) reflective judgment theory. They posited that as individuals progress in their development, they move on a continuum from viewing knowledge as truth that can readily be conferred by experts to seeing it as something that can be approximated based on what is known but can never be fully obtained because of the fallibility of human knowing. Counselors whose beliefs fall toward the reflective judgment end of this continuum will not assume that something must be true just because a professor or trainer told them it is the best way to do it. In addition, they will be more open to many views of the world and will also be able to critically yet nonjudgmentally evaluate those perspectives. Counselors are frequently required to tolerate ambiguous situations in which there is no clear right or wrong answer (McAuliffe, 2011; Skovholt, Jennings, & Mullenbach, 2004). Person-centered educators aim to foster a tolerance of ambiguity by encouraging learners and supervisees to examine the evidence themselves rather than implying that there is only one answer or one response to a given counseling concern or question (Rogers, 1951). The facilitation of open-mindedness in this way is relevant to CACREP standards related to diversity and advocacy.
CITs need to be able to address needs from clients with diverse backgrounds and expectations (CACREP, 2015, 2.F.2.; McAuliffe, 2011). One key aspect of multicultural competency is for counselors to be aware of their own attitudes, biases, and beliefs (Arredondo et al., 1996). Additionally, counselors must be able to think critically about the impact of their personal values on others (CACREP, 2015). A humanistic learning environment provides the opportunity for in-depth self-understanding and critical thinking (Combs, 1986; Dollarhide & Granello, 2012). Rogers (1951) described people moving toward self-actualization as “necessarily more understanding of others and . . . more accepting of others as separate individuals” (p. 520). This attitude embodies that of a multiculturally competent counselor (Arredondo et al., 1996).
Objectives of a Humanistic Learning Environment
When educators provide the environment described above and students begin to take responsibility for their own learning, certain results related to this self-actualization process can be expected. One key outcome of the humanistic approach to learning is a deeper understanding of self (Dollarhide & Granello, 2012), an important characteristic of a counselor. Increased self-understanding can lead to deeper learning. Learning can be enhanced when adult learners are able to accept themselves as they are while continuing to work toward growth (Knowles, 1959; Kunze, 2013). Similarly, Combs (1982) indicated that highly self-actualized individuals tend to view themselves in a positive way while honestly accepting their areas for growth, an attitude that leads to freedom to take more risks in educational settings. For example, learners who do not base their self-worth on grades might feel more free to focus on the meaning class material has for their future careers rather than on retaining facts in order to make a high grade in the class. In clinical classes, supervisees who have both a sense of self-worth and an openness to growth are more likely to be authentic with their clients and supervisors as well as less concerned about finding the “right” thing to say, and can focus more on what is most helpful in the context of that specific counseling relationship rather than being self-focused on performing well. Further, when learners are given substantial control over their own learning, they are better able to regulate their own processes of thinking and learning, leading to greater integration of the material (McCombs, 2013).
A humanistic learning environment also promotes a sense of care, acceptance, and respect toward individuals in society as well as a connection to the human condition (Combs, 1982; Knowles, 1959; Rogers, 1951). Combs (1982) argued that when learners feel a sense of belonging with those around them, they naturally become curious about their peers’ interests, and thus their learning opportunities are expanded. Rogers (1951) believed that when a person can accept one’s own experience, the person is free to be more open to and accepting of the experiences of others. Similarly, Combs (1982) wrote that highly self-actualized people can “confront the world accurately, realistically, and with a minimum distortion” (pp. 106–107). This openness to their experiences impacts their problem-solving abilities because they have more perceptual information from which to make decisions. In a classroom setting, this connection or sense of belonging can result in positive, in-depth group discussions that facilitate the learning of all involved beyond what an individual instructor could accomplish by sharing only one perspective. Further, an openness to the experience of others can lead to challenging one’s implicit or explicit beliefs about groups of people who have previously been seen as “other.” In clinical settings, supervisees will undoubtedly be exposed to individuals who hold differing beliefs, and an openness to their own experiences can help supervisees work better with these clients.
Concrete knowledge and skills are an outcome in humanistic learning theory, though they are generally considered more of a byproduct than the primary focus of learning. Rogers (1951) stated that one of the goals of learning is to develop knowledge relevant to the specific problem of focus, as well as to develop strategies for acquiring knowledge for new problems. Knowles (1959) noted the importance of acquiring skills that will aid a person in reaching their full potential and allow that person to positively influence society. Furthermore, Combs (1986) emphasized that knowledge leading toward self-actualization does not have to be academic. These humanists believed that learners who experience a facilitative learning environment will better retain knowledge and skills because they will have critically examined, applied, and connected it to their lives (McCombs, 2013).
Other Considerations in a Humanistic Learning Environment
Because application of humanistic learning theory requires a paradigm shift for both educators and learners, some learners may struggle to feel comfortable with the idea that the educator’s responsibility is to facilitate a learning environment and the learner’s responsibility is to pursue growth (Mearns, 1997). Many learners have grown up in educational environments where acquisition of knowledge was almost exclusively the goal of learning, and an educator who presents them with a different way of learning may induce stress. However, person-centered and humanistic learning theorists have emphasized that empathically helping students in the process of gaining self-responsibility helps the whole person develop (Knowles, 1975; Rogers & Freiberg, 1994; Smith, 2002).
Providing a warm, transparent, empathic environment does not preclude counselor educators from giving students feedback that may challenge them. When students struggle, person-centered and humanistic educators try to develop an empathic understanding of the struggling student’s view of oneself, to be accepting of that view, and to be transparently honest with the learner about his or her standing in the program. This conversation can involve counseling the student out of the program by communicating understanding that counseling may not be a good fit with the student’s current development. The educator attempts to make such discussions a collaborative effort in promoting the learner’s growth rather than a communication that the learner is failing (Dollarhide & Granello, 2012).
Application of Person-Centered Learning Theory in Counselor Education
Counseling faculty today are not only tasked with helping students develop their growth potential and learn the process of becoming effective counselors, but are also required to engage in assessment activities in addition to many other roles (CACREP, 2015). The purpose of the following section is to describe some specific ways in which a humanistic theory of learning can be applied to teaching and accountability measures.
Teaching
Given that the educator–student relationship is a model for the counselor–client relationship, and that students must feel accepted and understood in order to learn, the person of the educator is crucial in a humanistic classroom (Combs, 1982; Rogers, 1951). Of utmost importance is the counseling faculty member’s belief in the growth tendency of the human being. The attitudes of congruence, unconditional positive regard, and empathic understanding for the learner’s perceptual world are predicated upon this foundation, and any practical intervention in the classroom must be firmly based in those attitudes rather than adherence to a specific technique. However, there are specific classroom practices that are more facilitative of a humanistic way of learning than others.
Lecturing and other forms of direct knowledge transmission are generally considered among the least person-centered methods for learning because they are typically based on a power differential in which the teacher is considered the expert (Rogers & Freiberg, 1994). Freire (2011) described this type of teaching as a banking system of education because it involves teachers “depositing” information in their students’ heads, and he compared it to a system of education in which the students are active participants in deciding what is most important to learn and how. He believed students who were more active and took more responsibility for their own learning were better able to critically question their own and others’ beliefs and thus promote growth. This assertion does not mean lecture is never used or valuable in a person-centered classroom (e.g., Cornelius-White, 2005), but the person-centered educator works to have an attitude of humility and collaborative exploration (Combs, 1982; Dollarhide & Granello, 2012; Freire, 2011; Nelson & Neufeldt, 1998). A person-centered theory of learning requires the counseling faculty to give up much of their power and trust the learners’ ability to contribute equally to the learning environment.
Person-centered counseling faculty might also relinquish power regarding learning objectives for individual learners (Knowles, 1975; Rogers & Freiberg, 1994). The educator can have broad goals for the course, but counseling faculty can engage CITs in developing their own specific learning objectives and in deciding how those objectives will be met. Although it is clearly not possible to meet the needs of every individual in a course, counseling faculty can address the most common learning needs within the structure of the course and provide resources for individuals with unique learning interests (Cornelius-White, 2005; Knowles, 1975; Mearns, 1997). Projects proposed by students exemplify a humanistic-oriented way of helping students meet their learning objectives because self-chosen projects tend to be based on problems that are of relevance to the students (Rogers & Freiberg, 1994). Humanistic counseling faculty give students responsibility for the creation and implementation of projects and act as a resource when assistance or experience is needed. Projects that provide a resource or service to the community can help students reach learning objectives in an experiential way (Burnett, Long, & Horne, 2005; Svinicki & McKeachie, 2011) and meet CACREP standards related to advocacy and diversity. In one classroom, student journal entries indicated that service learning increased the students’ “awareness, knowledge, responsibility, and skills related to cultural, social . . . and civic concerns of diverse communities” (Burnett et al., 2005, p. 166). Educators also may encourage the self-direction of students by engaging students in posing a large-scale problem and giving the students the responsibility to investigate and propose possible reasons for the problem and ways to address the problem (Rogers & Freiberg, 1994).
One way that person-centered counseling faculty help CITs develop critical thinking is to place responsibility for learning upon the learners (Combs, 1986; Mearns, 1997). Knowles (1975) described self-directed learning as students taking “the initiative, with or without the help of others, in diagnosing their learning needs, formulating learning goals, identifying human and material resources for learning, choosing and implementing appropriate learning strategies, and evaluating learning outcomes” (p. 18). However, he realized that the typical student was not socialized to learn this way; therefore, he emphasized the importance of using small steps to facilitate self-direction. Although person-centered counseling faculty do not take responsibility for CITs’ learning, they do feel much responsibility to students to provide a facilitative environment by developing meaningful relationships with CITs, serving as resources, providing needed supervision, and making necessary changes to the environment as learners pursue their growth process (Dollarhide & Granello, 2012; Mearns, 1997). Teaching CITs to think for themselves and helping them develop the basic attitudes toward people that are facilitative of change will give beginning counselors the tools to respond to difficult or unique counseling situations and to know how to find the type of supervision or support they need.
Ethical and legal issues are another important dimension for CITs (ACA, 2014, F.7.e., F.5.a.; CACREP, 2015, 2.F.1.), and one for which a humanistic approach to learning is particularly appropriate because of the focus on helping learners develop the ability to critically think through problems (Knowles, 1975). One way that person-centered counseling faculty can model ethical principles is by giving their students a full disclosure of what to expect from a humanistic-oriented learning environment. CITs need to be informed of expectations regarding their responsibility for learning, expectations for self-disclosure, and how grades will be assigned (ACA, 2014, F.9.a.; CACREP, 2015, 2.D.; Morrisett & Gadbois, 2006). Although these disclosures are necessary in any classroom, special clarification of the differences between a humanistic learning environment and a typical classroom may be necessary to help decrease learners’ anxiety about an unfamiliar learning environment (Knowles, 1975). Counseling faculty can emphasize that grades will not be reflective of learners’ self-disclosure, but they also note the role of honesty about one’s experience in facilitating growth (ACA, 2014, F.8.d.). Finally, counseling faculty can clarify appropriate faculty–student roles (ACA, 2014, F.10.; Morrisett & Gadbois, 2006). This may be particularly important in a humanistic classroom where the power differential between faculty member and student is decreased.
Teaching from a person-centered perspective is not an all-or-nothing endeavor. Just as each of the attitudes of a person-centered educator lie on a continuum, so do activities that may be utilized in the classroom (Rogers & Freiberg, 1994). For example, self-assessment and student-directed inquiry are on the more purely humanistic side of the spectrum while lecture and questioning are on the teacher-focused extreme. Projects, portfolios, and role-plays fall somewhere in the middle. Additionally, person-centered counseling faculty may choose to assign one self-directed project and several teacher-directed assignments for practical reasons or because of their personal comfort level.
Accountability. One purpose of accountability measures, such as licensure and accreditation standards, is to confirm that individuals are qualified to provide the services they are offering, and institutions that make some statement to the public about the qualifications of an individual also have a responsibility to that public to graduate only those who meet such qualifications (Mearns, 1997). From a purely theoretical person-centered perspective, such external requirements as CACREP standards and the grades required by universities represent an external locus of control and could impede the process of learning by causing the learner to conform to external methods of evaluation (Gould, 2012; Rogers & Freiberg, 1994). Ideally, individuals would pursue learning solely out of an intrinsic desire for growth, and facilitators of learning would not have to worry with grades or formal assessments. Rogers disliked summative assessment because it implied that a person had reached an endpoint (Mearns, 1997), and person-centered educators believe growth is a dynamic process (Knowles, 1959; Rogers, 1957). However, from a practical perspective, accountability is necessary, both at the course level and the program level, to ensure CITs are adequately prepared and to protect students from programs that purport to train counselors but do not have sufficiently rigorous standards to adequately prepare their students for the work of effective counseling.
CACREP standards are aimed at ensuring that counseling programs produce competent counselors. Although many practices required to meet accreditation standards, such as the use of program-wide rubrics for specific classes, are not consistent with a person-centered and humanistic approach to learning (Hansen, 2009), person-centered educators can find ways to work within this context to maintain a facilitative learning environment. One possibility is for counseling faculty to give students the learning objectives for a certain course or rubric for a key assessment and allow students to create individual projects or products that will show their competency in the learning outcomes the standard or assessment is intended to address. Another option is the use of portfolios to measure some of the learning outcomes (Barrio Minton & Gibson, 2012). These alternate assignments are not intended to be viewed as ways of circumventing the CACREP standards, but as ways of meeting them via practices that are most meaningful for students and that best facilitate their learning.
Although person-centered counseling faculty have to operate in a learning environment that emphasizes external accountability requirements, they do not have to give up their approach to learning (Hansen, 2009; Mearns, 1997). Even if program policies require some specific assessments, counseling faculty have flexibility with other measures of learning outcomes. Furthermore, they can frame what they are already doing in terms that appeal to accreditation reviewers. Mearns (1997) argued that person-centered teachers use a great deal of diagnostic and formative assessment as they help CITs develop learning objectives and assess whether those are being met. The type of assessment must fit the outcome desired (Cobia, Carney, & Shannon, 2011). If counseling faculty value process over the product, then they will focus on both formative and summative assessment throughout the process, such as the use of embedded assessments (Svinicki & McKeachie, 2011). Contracts are one form of assessment that encompasses aspects of diagnostic, formative, and summative assessment and also rely on the self-direction of the individual (Knowles, 1975; Rogers & Freiberg, 1994). With the use of contracts, each learner creates individual learning objectives and a plan for accomplishing the objectives. Once the educator and the learner agree on the terms of the contract, it is used to guide the learner throughout the course. At the end of the course, the learner completes a self-assessment on whether the contract has been completed sufficiently. The counseling faculty member typically has final authority over the grade the student assigns themself (Mearns, 1997). Although contracts can be helpful in bridging the gap between student-directed learning and the need for accountability, their use evolves into a completely behavioral method without the attitudes that embody a humanistic learning environment (Rogers & Freiberg, 1994). For example, if a faculty member engages students in creating learning contracts but does not simultaneously demonstrate respect and trust that the learners are capable of directing their own learning, the assignment is no longer humanistic. By including the students in all aspects of the assessment process, the counseling faculty member indicates a respect for the students’ input and facilitates an internalized locus of control. By involving students in their own assessment, counseling faculty model ethical assessment procedures (CACREP, 2015, 2.F.7.) in that counselors also should seek client input before evaluating client functioning (ACA, 2014, A.1.c.).
Challenges. Regardless of how much an educator trusts the self-actualizing tendency in others, there are instances in which the timeline of the learning institution does not allow students sufficient time for their growth process (O’Leary, 1989). Person-centered counseling faculty do not see students as failing, but continuing their development in an environment that is more conducive to their current growth process. When a student needs to be counseled out of the program, counseling faculty are honest and empathic (Mearns, 1997). Maintaining an attitude of unconditional positive regard does not mean thinking everything a student does is fine. However, when dismissing a student from a program, counseling faculty work to maintain an empathic, caring relationship throughout the process in hopes that the student might continue to feel valued as a person by the counseling faculty.
Limitations. This approach may not be a good fit for all counselor educators, particularly those who do not identify with more humanistic modes of learning. In addition, this approach to learning is not always appreciated by all students. Some students prefer the teacher tell them what they need to know and how to demonstrate their knowledge. The idea of taking responsibility for their learning can be stressful for some students. Counselor educators utilizing this theory of learning need to assess whether such stress levels are facilitative or debilitating for learners.
Conclusion
Humanistic learning theory is a way of approaching counselor education that emphasizes the humanistic underpinnings of the profession rather than the current reductionist approach of diagnosis and skills development (Hansen, 2009). Person-centered counseling faculty can utilize humanistic learning theory to facilitate an open, accepting, and understanding environment in which they engage CITs in directing their own learning. Counseling faculty can focus on CITs’ attitudes and beliefs about people in relation to knowledge and skills. Person-centered counseling faculty hope to foster CITs’ self-understanding, caring and accepting attitudes toward people, and the acquisition of concrete knowledge and skills needed in the counseling profession. Counseling faculty using humanistic learning theory engage learners in assessment of their learning as much as feasible, while honoring the realities of external evaluation through accreditation.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
References
American Counseling Association. (2014). ACA code of ethics. Alexandria, VA: Author.
Arredondo, P., Toporek, R., Brown, S. P., Jones, J., Locke, D. C., Sanchez, J., & Stadler, H. (1996). Operationalization of the multicultural counseling competencies. Journal of Multicultural Counseling and Development, 24, 42–78. doi:10.1002/j.2161-1912.1996.tb00288.x
Barrio Minton, C. A., & Gibson, D. M. (2012). Evaluating student learning outcomes in counselor education: Recommendations and process considerations. Counseling Outcome Research and Evaluation, 3(2), 73–91. doi:10.1177/2150137812452561
Burnett, J. A., Long, L. L., & Horne, H. L. (2005). Service learning for counselors: Integrating education, training, and the community. The Journal of Humanistic Counseling, Education and Development, 44, 158–167. doi:10.1002/j.2164-490X.2005.tb00028.x
Cobia, D. C., Carney, J. S., & Shannon, D. M. (2011). What do students know and what can they do? Assessing competence in counselor education. In G. McAuliffe & K. Eriksen (Eds.), Handbook of counselor preparation: Constructivist, developmental, and experiential approaches (pp. 367–376). Thousand Oaks, CA: SAGE.
Combs, A. W. (1982). A personal approach to teaching: Beliefs that make a difference. Boston, MA: Allyn & Bacon.
Combs, A. W. (1986). Person-centered assumptions for counselor education. Person-Centered Review, 1, 72–82.
Cornelius-White, J. H. D. (2005). Teaching person-centered multicultural counseling: Collaborative endeavors to transcend resistance and increase awareness. The Journal of Humanistic Counseling, Education and Development, 44, 225–239. doi:10.1002/j.2164-490X.2005.tb00033.x
Council for Accreditation of Counseling and Related Educational Programs. (2015). 2016 CACREP standards. Retrieved from www.cacrep.org/wp-content/uploads/2017/08/2016-Standards-with-citations.pdf
Dollarhide, C. T., & Granello, D. H. (2012). Humanistic perspectives on counselor education and supervision. In M. B. Scholl, A. S. McGowan, & J. T. Hansen (Eds.), Humanistic perspectives on contemporary counseling issues (pp. 277–305). New York, NY: Routledge.
Freire, P. (2011). Pedagogy of the oppressed (M. B. Ramos, Trans.). New York, NY: Continuum.
Gibson, D. M., Dollarhide, C. T., & Moss, J. M. (2010). Professional identity development: A grounded theory of transformational tasks of new counselors. Counselor Education and Supervision, 50, 21–38.
doi:10.1002/j.1556-6978.2010.tb00106.x
Gould, J. (2012). Learning theory and classroom practice in the lifelong learning sector. Thousand Oaks, CA: SAGE.
Hansen, J. T. (2009). Counselor education and the meaning-reduction pendulum. The Journal of Humanistic Counseling, Education and Development, 48, 65–76. doi:10.1002/j.2161-1939.2009.tb00068.x
King, P. M., & Kitchner, K. S. (2004). Reflective judgment: Theory and research on the development of epistemic assumptions through adulthood. Educational Psychologist, 39, 5–18. doi:10.1207/s15326985ep3901_2
Kleiman, S. (2007). Revitalizing the humanistic imperative in nursing education. Nursing Education Perspectives, 28, 209–213.
Knowles, M. (1959). Informal adult education. New York, NY: Association Press.
Knowles, M. (1975). Self-directed learning: A guide for learners and teachers. New York, NY: Association Press.
Kunze, D. (2013). The person-centered approach in adult education. In J. H. D. Cornelius-White, R. Motschnig-Pitrik, & M. Lux (Eds.), Interdisciplinary applications of the person-centered approach (pp. 115–123). New York, NY: Springer.
McAuliffe, G. J. (2011). Constructing counselor education. In G. McAuliffe & K. Eriksen (Eds.), Handbook of counselor education and preparation: Constructivist, developmental, and experiential approaches (pp. 3–12). Thousand Oaks, CA: SAGE.
McCombs, B. L. (2013). The learner-centered model: From the vision to the future. In J. H. D. Cornelius-White, R. Motschnig-Pitrik, & M. Lux (Eds.), Interdisciplinary applications of the person-centered approach (pp. 83–113). New York, NY: Springer.
Mearns, D. (1997). Person-centred counselling training. London, England: SAGE.
Morrissette, P. J., & Gadbois, S. (2006). Ethical consideration of counselor education teaching strategies. Counseling and Values, 50, 131–141. doi:10.1002/j.2161-007X.2006.tb00049.x
Nelson, M. L., & Neufeldt, S. A. (1998). The pedagogy of counseling: A critical examination. Counselor Education and Supervision, 38(2), 70–88. doi:10.1002/j.1556-6978.1998.tb00560.x
O’Leary, E. (1989). The expression of disapproval by teachers and the maintenance of unconditional positive regard. Person-Centered Review, 4, 420–428.
Penn, J. D. (2011). Future directions for assessing complex general education student learning outcomes. New Directions for Institutional Research, 149, 109–117. doi:10.1002/ir.384
Rogers, C. R. (1951). Client-centered therapy: Its current practice, implications, and theory. Oxford, England: Houghton Mifflin.
Rogers, C. R. (1957). The necessary and sufficient conditions of therapeutic personality change. Journal of Consulting Psychology, 21, 95–103. doi:10.1037/h0045357
Rogers, C. R. (1989). Personal thoughts on teaching and learning. In H. Kirschenbaum & V. L. Henderson (Eds.), The Carl Rogers reader (pp. 301–304). New York, NY: Houghton Mifflin. (Reprinted from Merrill-Palmer Quarterly, 3, 241–243.)
Rogers, C., & Freiberg, H. J. (1994). Freedom to learn (3rd ed). Upper Saddle River, NJ: Prentice Hall.
Skovholt, T. M., & Rønnestad, M. H. (1992). Themes in therapist and counselor development. Journal of Counseling & Development, 70, 505–515. doi:10.1002/j.1556-6676.1992.tb01646.x
Skovholt, T. M., Jennings, L., & Mullenbach, M. (2004). Portrait of the master therapist: Developmental model of the highly functioning self. In T. M. Skovholt & L. Jennings (Eds.), Master therapists: Exploring expertise in therapy and counseling (pp. 125–146). Boston, MA: Pearson.
Smith, M. K. (2002). Malcolm Knowles, informal adult education, self-direction and andragogy. The Encyclopedia of Informal Education. Retrieved from www.infed.org/thinkers/et-knowl.htm
Svinicki, M., & McKeachie, W. J. (2011). McKeachie’s teaching tips: Strategies, research, and theory for college and university teachers (13th ed). Belmont, CA: Wadsworth Cengage Learning.
Tolan, J. (2017). Skills in person-centered counseling & psychotherapy (3rd ed). Thousand Oaks, CA: SAGE.
Katherine E. Purswell is an assistant professor at Texas State University. Correspondence can be addressed to Katherine Purswell, 601 University Dr., EDU 4019, San Marcos, TX 78666, kp1074@txstate.edu.
Nov 12, 2019 | Volume 9 - Issue 4
Deborah L. Duenyas, Chad Luke
In recent decades, professional counselors have increasingly focused on neuroscience to inform their case conceptualization and treatment planning with clients. With the additional lens of neuroscience, both the counselor and client can gain new understandings of the client’s issues and improve the quality of the therapeutic relationship. The benefits of integrating neuroscience into the profession of counseling (i.e., neuroscience-informed counseling) are being documented in the scholarly literature; however, information on integrating neuroscience-informed counseling into the counselor education curriculum is sparse. This article describes one teaching approach for a neuroscience-informed counseling course. The structure of the course, methods for effective instruction, and ethical and cultural considerations are discussed.
Keywords: neuroscience, counselor education, teaching, neuroscience-informed, instruction
Neuroscience-informed counseling is a growing force in the counseling profession (Beeson & Field, 2017). The integration of neuroscience into the profession of counseling has been evident over the past two decades. Examples include the development of neuroscience interest networks by the American Counseling Association (ACA), the American Mental Health Counselors Association (AMHCA), and the Association for Counselor Education and Supervision (ACES). There have been numerous books published that focus on neuroscience for counselors (Field, Jones, & Russell-Chapin, 2017; Luke, 2019) and an increased amount of scholarly literature focused on integrating neuroscience into counseling practice (Beeson & Field, 2017; Lorelle & Michel, 2017; Luke, Redekop, & Jones, 2018; Makinson & Young, 2012; Miller, 2016; Myers & Young, 2012).
Neuroscience is the study of the brain and nervous system (Kalat, 2019). Neuroscience-informed counseling involves integrating principles from the structure and function of the brain and nervous system to counseling practice (Russell-Chapin, 2016). This integrative work in counseling is being used to treat behavioral and mental health challenges (Field et al., 2017). According to Beeson and Field (2017), neurocounseling is a
specialty within the counseling field, defined as the art and science of integrating neuroscience
principles related to the nervous system and physiological processes underlying all human
functioning into the practice of counseling for the purpose of enhancing clinical effectiveness in the
screening and diagnosis of physiological functioning and mental disorders, treatment planning
and delivery, evaluation of outcomes, and wellness promotion. (p. 74)
Three methods for integrating neuroscience into the counseling profession have been identified in the scholarly literature, including neuroeducation (Fishbane, 2013), neurofeedback (Myers & Young, 2012), and the use of a metaphor-based approach (Luke, 2016).
The first method, neuroeducation, is defined by Miller (2016) as “a didactic or experiential-based intervention that aims to reduce client distress and improve client outcome by helping clients understand the neurological processes underlying mental functioning” (p. 105). Neuroeducation is essentially psychoeducation about the brain and nervous system. Neuroeducation can be used as an intervention to help clients understand the neurological processes that underlie their symptoms and development (Miller, 2016). Miller described various methods for integrating neuroeducation into counseling practice through the use of information on neuroplasticity, brain structures and functions, and memories.
Plasticity is an object’s or organism’s ability to stretch and to be resilient. As applied to the brain and central nervous system, this is called neuroplasticity or neural plasticity, and involves “changes in the activity and connectivity of the various circuits within the nervous system [that] enable learning, encode memory, and drive behavior” (Li, Park, Zhong, & Chen, 2019, p. 44). Information on neuroplasticity and self-defeating patterns of thought and behavior may help demystify change processes.
Informing clients about the various brain structures and functions (e.g., brain stem, limbic, and cortical regions) can help with understanding the brain from a developmental perspective—that the brain is built to change and to be resilient (Luke, 2019). Educating clients about how their memories are encoded, stored, and accessed, drawn from the groundbreaking work of Eric Kandel (1976), can help clients gain a better understanding of their own brain and behavior (Miller, 2016). This knowledge can instill hope that although events of the past cannot be changed, the meaning of the memories associated with those events can be changed (Sweatt, 2016). Furthermore, the relational context in which change takes place can help clients’ brains overwrite rigid rules and threats about relationships learned from earlier dysfunctional relationships (Kandel, Dudai, & Mayford, 2014; Schore, 2010; Siegel, 2015).
A second method, neurofeedback, has been recognized as an effective treatment for reducing symptoms of various mental health concerns (Russell-Chapin, 2016). A specialized form of biofeedback, neurofeedback changes brain wave patterns to aid in the treatment of conditions such as attention-deficit/hyperactivity disorder, anxiety, depression, addiction, trauma, autism spectrum disorders, and personality disorders (Russell-Chapin, 2016). Neurofeedback is just one method that counselors can use with clients to help them understand and change the function of their brains. Additional examples include basic biofeedback tools and methods like those found on many “smart” watches and fitness trackers.
The third method for integrating neuroscience-informed counseling is described by Michael and Luke (2016) as using a metaphor-based approach to teaching the neuroscience of play therapy. This approach is an extension and application of that described in Luke (2016), wherein neuroscience concepts are used both as metaphors for the human experience, as well as understanding brain function. Tay (2017a) has identified the therapeutic value of metaphor and its utility in understanding language and the body. Relatedly, the practices of mindfulness and meditation often use imagery, a form of metaphor, to engage practitioners in engaging more fully in the experience (Tang, Hölzel, & Posner, 2015). As neuroscience-informed counseling continues to become integrated into the work of professional counselors, counselor educators must adapt in order to keep their coursework relevant.
Counselor Education and Neuroscience-Informed Counseling
Beeson and Field (2017), along with others (Field et al., 2017; Luke, 2017; Miller, 2016) have called for more training for counselors who seek to integrate neuroscience into their practice. They also have identified the challenges associated with infusing neuroscience into counseling courses. The Council for Accreditation of Counseling and Related Educational Programs (CACREP; 2015) standards now require competency in “the biological, neurological, and physiological factors that affect human development, functioning, and behavior” (p. 10). CACREP standards, along with growing momentum in the field, support the development of a course designed specifically for integrating neuroscience for counselors. The AMHCA clinical training standards include recommendations for competence in understanding and applying the biological bases of behavior. The AMHCA standards outline basic knowledge and skills, which include integrating research into practice, as well as clinical interventions.
Field et al. (2017) laid a foundation for incorporating neuroscience-informed counseling across the CACREP curriculum. This approach addresses neuroscience in pre-existent courses, yet there is limited availability of literature on how to teach a graduate content course in neuroscience-informed counseling. In the absence of established models for teaching a course in neuroscience-informed counseling, counselor educators and others can feel at a loss for how to proceed. The purpose of this article is to provide recommendations for developing a neuroscience-informed counseling course designed for graduate students. This includes the course structure (e.g., content and resources), methods for effective instruction (e.g., teaching approach and assignments), and ethical considerations.
Course Structure: Content and Resources
The Neuroscience for Counselors course builds on prior core counseling courses, including counseling theories and the fundamentals of counseling. As such, it represents an extension of counseling theory and fundamentals and is not intended to be a substitute or replacement. Neuroscience-informed counseling explores how different counseling theories and interventions influence and change neurobiology and help facilitate client wellness.
The Neuroscience for Counselors course was offered to master’s students enrolled in a CACREP-accredited counseling program at a mid-size university in the northeast region of the United States. The course was offered as an elective that fulfilled three graduate credits toward degree completion. The course was designed as an introduction to neuroscience research and clinical interventions for counselors. Specific attention was given to reviewing the structures, systems, and functions of the brain. Psychodynamic, behavioral, humanistic, and constructivist counseling theories were explored in relation to neuroscience research. The neuroscience of mental health disorders, such as anxiety, depression, stress, and addictions and substance use, were explored.
Course assignments included developing a neuroscience-informed guided metaphor; completing a brain resource book on structures, systems, and functions; dyads to practice using neuroscience-informed counseling interventions; reflection in a neuroscience process analysis log (N-PAL); and activities exploring neuroscience-informed technology. A final paper included a case conceptualization based on the 8-factor meta-model (Luke, 2017, 2019) of case conceptualization to explore their client’s presenting concerns.
The assigned textbook for this course was Luke’s (2016) Neuroscience for Counselors and Therapists: Integrating the Sciences of Mind and Brain, which focuses on client conceptualization, brain anatomy, various theoretical approaches, and an array of commonly diagnosed mental health concerns. The text also provides case vignettes highlighting how a student might use neuroscience-informed counseling interventions with a diverse population of clients. The first chapter of the text discusses ethical and philosophical issues related to integration. Chapter 2 presents an overview of the basic brain structures, systems, and functions, including neurons and synapses. Chapters 3 through 6 cover the major categories of counseling theories: psychodynamic, cognitive-behavioral, humanistic-existential, and postmodern and constructivist. Chapters 7 through 10 describe conceptualizing and treating anxiety, depression, stress-related disorders, and substance use disorders. The text is written for counselors and counselors-in-training who have little or no background in the physiological bases of behavioral and mental health concerns.
The course instructor provided supplemental material, including magazine articles, peer-reviewed journal publications, apps, videos, websites, and links to neuroscience interest networks. For example, students were provided a link to the Neuroscience News website, which is an independent science news website that offers free cognitive science research papers, neuroscience resources, and a science social network. Also included were links to the Dana Foundation, an organization that supports brain research via grants, publications, and education, and the ACA’s Neurocounseling Interest Network. The supplemental material was selected as a method to broaden student understanding and support knowledge acquisition in neuroscience.
Methods: Teaching Approach and Assignments
Experiential education is not a new approach in higher education. Educational psychologists in the past, such as John Dewey (1938), Carl Rogers (1969), and David Kolb (1984), have laid the groundwork for the development of contemporary experiential education. Kolb (1984) defined learning as “the process whereby knowledge is created through the transformation of experience. Knowledge results from the combination of grasping and transforming experience” (p. 41). The Association for Experiential Education (AEE; 2019a) defined experiential education as a teaching philosophy “in which educators purposefully engage with learners in direct experience and focused reflection in order to increase knowledge, develop skills, clarify values, and develop people’s capacity to contribute to their communities” (para. 1). In essence, experiential education is the process of learning through experience and reflection.
Methods of instruction in the Neuroscience for Counselors course were consistent with the 12 principles of practice outlined by the AEE (2019b). For example, class assignments provided students with the opportunity for reflection, critical thinking, and personal application. The instructor’s teaching roles included “setting suitable experiences, posing problems, setting boundaries, supporting learners, insuring physical and emotional safety, and facilitating the learning process” (AEE, 2019b, para. 9). Sakofs (2001) cautioned that experiential activities can be misused by educators as a form of entertainment with no real educational value. The following six assignments were designed with the intention to deepen students’ understanding of neuroscience concepts as they relate to the profession of counseling.
Six Neuroscience Course Assignments
Developing a neuroscience-informed guided metaphor. Historically, neuroscience has been considered the realm of the medical professional or psychiatrist who has studied the complex inner workings of the brain. Developing a neuroscience-informed guided metaphor provides counseling students the experiential opportunity of taking an unfamiliar concept or idea (i.e., using neuroscience-informed counseling) and making it more accessible by relating it to ideas they are already familiar with (Jamrozik, McQuire, Cardillo, & Chatterjee, 2016; Lawson, 2005). For this assignment, students were assigned to read the article “The Birth of the Neuro-counselor?” (Montes, 2013), in which the term neurocounselor was first used. The article introduces and encourages students to begin thinking about what it means to use neuroscience-informed counseling in practice and how it influences their professional identity as a counselor.
After reading the article, students illustrated a guided metaphor that could be used to inform their model of neuroscience-informed counseling practice. Students were provided with the prompt, “Neuroscience-informed counseling is _________” and then asked to fill in the blank with a noun. Students included a paragraph explaining their choice in metaphor and how they came to make that decision. Students were asked to share their metaphors with their peers in class. A student’s illustration could be a visual representation, in writing, or a combination of both. Metaphor is, simply put, the practice of describing one thing in terms of another (Tay, 2017b). More specifically, the use of metaphor increases understanding of a less well-understood concept or idea by describing it in terms of something that is better understood. In the assignment described above, students generated metaphors such as “neuroscience-informed counseling is the first mission to the moon,” “neuroscience-informed counseling is a penlight in a dark maze,” and “neuroscience-informed counseling is a puzzle” to be solved. Lawson (2005) extolled the virtues of metaphors in counseling, noting that they “can help the counselor connect to the client’s world” (p. 135). The use of neuroscience metaphors, whether generated by the client or the counselor, can aid in promoting empathy and therefore trust (Luke, 2017) and can aid in learning neuroscience concepts (Michael & Luke, 2016). For example, in the wildly popular “I Had a Black Dog, His Name Was Depression” World Health Organization video on YouTube (over 9 million views as of this writing), depression is compared to a black dog that affects every facet of an individual’s life (World Health Organization, 2012). The metaphor works by comparing an abstract concept like depression with something concrete like a black dog. It enables the client to experience their depression as something happening to them, not emerging from their core self. When incorporated with relevant neuroscience information, the metaphor takes on increased significance. This black dog hijacks a person’s will, leaving them with diminished options for meaningful action.
Developing metaphors for the counselor’s roles when using neuroscience-informed counseling can clarify and strengthen counselor identity. When introducing this assignment, it is important to note that neuroscience-informed counseling is not its own therapeutic orientation. Whereas many graduate counseling programs have courses focused on advanced therapeutic orientations, such as solution-focused therapy or motivational interviewing, a course in neuroscience for counselors can strengthen a counselor’s current theoretical framework (Luke, 2017). For example, counselors practicing cognitive behavior therapy who learn about Hebb’s rule (1949), which states that “neurons that fire together wire together,” along with the concept of neuroplasticity, have another avenue of support for clients working to make positive behavioral changes. In this example, neuroscience can help the client gain awareness of the neurological structures that reinforce their behavior and also provide hard evidence that change is possible (Li et al., 2019). Neuroscience-informed counseling is one of many tools in the counselor toolbox. In addition to conceptualizing neuroscience-informed counseling as part of their professional identity, students also learn content knowledge of the brain’s structures, systems, and functions.
Brain structures, systems, and functions book. This assignment required students to research the basic structures, systems, and functions of the human brain and design their own book. The instructor provided students black and white images of various structures of the brain discussed in the class textbook. Images included lateral and dorsal views of the brain, the two hemispheres of the brain, the three divisions of the brain (i.e., forebrain, midbrain, and hindbrain), the four lobes of the brain (i.e., frontal, temporal, occipital, and parietal), the anatomy of a neuron, and a stem chart of the nervous system tasks, including the sympathetic and parasympathetic nervous system functions. This approach is supported by works such as the Wammes, Meade, and Fernandes (2016) investigation of the neural processes of storing and retrieving memory. The authors found that drawing important words and phrases improves one’s ability to remember important concepts. Students were asked to use various mediums, including colored pencils, crayons, and markers, to label and highlight the different neuroanatomy. Students also were asked to use their class textbook to write descriptions of the functions of these parts of the brain within their assignment.
Mental health diagnoses can be intimidating for clients, as can the symptoms of a disorder. Anchoring a client’s experience in their neurobiology can increase their understanding of what is happening. Basic neuroscience information can empower them to learn more about, and in some ways objectify, their experience. In other words, knowledge of the underlying brain function can encourage clients to reflect on mind and body and how they interact. For example, depression is a result of brain function, but the choices an individual makes in response can be a function of the mind. In practice, clients can be led through the process of identifying brain function and mind function.
The brain structures, systems, and functions book assignment helps to empower students by providing them with the language and imagery surrounding neuroanatomy. Once counselors feel confident in their knowledge of basic brain regions and systems they can use it to empower clients by providing them a physiological explanation of their experiences. For example, knowledge about the autonomic nervous system can help a client struggling with generalized anxiety disorder. According to the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013), generalized anxiety disorder is characterized by excessive anxiety and worry that is difficult to control, with symptoms that might include restlessness, feeling on edge, being easily fatigued, difficulty with concentration, muscle tension, and sleep disruptions. Clients struggling with generalized anxiety disorder can feel as if they are in a constant state of emergency. Understanding how the sympathetic nervous system prepares the body for emergencies can help a client understand what they are experiencing at a physiological level. This can make them more receptive to interventions that activate their parasympathetic nervous system functions and move them from “fight or flight” to “rest and digest.” Once students in the course obtained content knowledge regarding the brain’s structures, systems, and functions, they applied that knowledge in dyads.
Dyads. Experiential learning takes careful planning, structuring of lessons, and intentionality in teaching practices (AEE, 2019). Experiential activities such as dyads can help students learn the material through the act of “doing.” Tollerud and Vernon (2011) described the benefits of experiential learning as “promoting interest in a topic, supporting student retention of the material, and involving students in their education” (p. 285).
Luke (2017) outlined neuroscience concepts that can be used as interventions with clients
(e.g., memory systems, Hebb’s rule, left and right brain processing, mirror neurons, attention, and mindfulness). In the neuroscience course, students practiced discussing neuroscience concepts in dyads where they took turns acting as counselor and client. The neuroscience concepts coincided with Chapters 3–10 in the textbook. This provided practice for students using the neuroscience concepts with specific theoretical approaches (e.g., contemporary psychodynamic, behavioral approaches, humanistic approaches, and constructivist approaches), but also could align with a particular mental health diagnosis (e.g., anxiety, depression, stress disorders, and substance use disorders). For example, discussion about Hebb’s rule may apply to counselors working from a behavioral approach or counselors working with clients struggling with specific issues such as substance use.
The instructor provided a dyad prompt for students relating to the chapter material for that class session. For instance, the prompt for Chapter 3, Contemporary Psychodynamic Approaches and Neuroscience, was, “Tell me more about your early memories pertaining to key relationships (i.e., parents, siblings, guardians)” and “How do you feel these early memories influence your key relationships today?” The discussion prompt provided the student counselor an avenue to discuss the neuroscience concepts identified in the chapter (i.e., relationships in the brain/interpersonal neurobiology, consciousness, and memory systems) with their mock client. Students were graded on their ability to use the neuro-concepts and attend to their fundamental counseling skills (e.g., unconditional positive regard and empathy).
The dyad activities also highlight the positive benefits of right hemisphere to right hemisphere connections validated through neuroscience. According to Badenoch (2008), right hemisphere to right hemisphere connections are at the root of change, as interpersonal connections are rooted in the neural processes of the right hemisphere. Practicing mock counseling sessions provides students the opportunity to develop healthy relationships with their peers in class. This experience can later become a parallel process by which they use the positive experience in class with their future clients.
In counseling, two approaches parallel the class experience. In the first, counselors can apply the same material described above with their clients, using process-based psychoeducation. For example, the counselor can present information on the neurobiology and role of early memories, relationships (past and present), and consciousness/unconsciousness in the client’s depression. They can then ask the questions described above directly to the client. The second approach involves a Gestalt technique wherein the client’s depression, their brain, and the client themselves all sit together in the room. The client is guided through a discussion with these constituent parts in order to better understand the role that each plays in the living of the client’s life. As students completed each dyad, a system was created for them to reflect on their experience as described below.
The N-PAL (Neuroscience-Personal Analysis Log). According to Faiver, Brennan, and Britton (2012), the purpose of a personal analysis log (PAL) “is to help students track their progress over the semester in terms of self-awareness and comfort level with the counseling process” (pp. 292–293). Students completed nine neuroscience personal analysis logs (N-PALS) throughout the course. Entries were made in class after each dyad. Students were given the opportunity to analyze and express their feelings in relation to the dyad activities and course material. The purpose of the N-PAL was to help students reflect on their counseling work while integrating neuroscience concepts into the mock counseling sessions with their classmates.
N-PALs consisted of five questions: (a) On a scale from 1–10, how confident do you feel applying the assigned theoretical approach for this dyad? (b) On a scale from 1–10, how confident did you feel using neuroscience concepts in this dyad? (c) What were some new areas of growth and development during this dyad? (d) Assess your own performance during this dyad and provide specific examples, and (e) What is your reaction to the course material (i.e., assigned reading, class lecture, videos, discussion)? The N-PAL’s structure is consistent with the experiential education principle, which states that experiences are structured to require the learner to take initiative and make decisions and be accountable for results (AEE, 2019). The questions were developed to encourage students to reflect on their dyadic experiences and think critically about their neuroscience-informed interventions while being held accountable for areas of growth and development.
Exploring neuroscience-informed technology. With the increased focus on neuroscience in popular culture and media, there has been an influx of new neuroscience-informed technology. Students were asked to find three technological tools that could inform their neuroscience-informed clinical work. The tools were to fall into three distinct categories: one app (e.g., mindfulness, anxiety, or brain information app), one video (e.g., YouTube, TedTalk), and one technological application (e.g., pulse oximeter, biofeedback equipment, EEG reader). After identifying the neuroscience-informed technology tools, students posted on an online discussion board describing how they would use their identified tools in a counseling session.
There is an abundance of neuroscience-informed technology on the market today. Counselors recommending meditation apps or assorted TedTalks to their clients may be using this technology without awareness of their neuroscientific implications. Counselors do not have to work from memory alone but can take advantage of the growing number of resources available today (e.g., journal articles, books, apps, videos). Counselors who take advantage of resources also must be savvy consumers. For example, prior to recommending apps or videos to clients with neuroscience-related material, counselors should check the source to confirm it is reputable and use the material themselves. Whereas the neuroscience-informed technology discussion post helped to build awareness of technological tools, the final case conceptualization paper served to showcase the content students gained throughout the course.
Case conceptualization. As a summative assignment, students completed a three-part case write-up that demonstrated their ability to conceptualize client issues and apply neuroscience-informed interventions. The instructor provided students with a fictional client case vignette, including biopsychosocial information. The first part of the assignment required students to use an 8-factor meta-model (Luke, 2017, 2019) to conceptualize their client’s case. This 8-factor model is a holistic model identifying eight components that every counselor must consider when working with clients: thoughts, feelings, behaviors, environments, experiences, biology and genetics, relationships, and the socio-cultural context in which the client lives.
Students were asked to include neuro-concepts in their discussion of each of the factors. For example, if the student identified that the client was experiencing anxious thoughts, they would include a description of how the amygdala modulates the client’s reactions to events perceived as dangerous or scary. This part of the assignment demonstrated the counseling student’s mastery of case conceptualization in conjunction with their understanding of how neuroscience concepts can influence the client’s symptoms.
The second part required students to review their conceptualization and write a phenomenological description of the client across the eight factors of the model. A phenomenological description provides an opportunity for students to consider, beyond the prescribed clinical note, what it might be like to “walk in this client’s shoes.” Writing a phenomenological description uses right-brain processing skills of creativity and intuitiveness. Although the description is the student’s interpretation of the client’s experience, the exercise can strengthen skills in empathic awareness and creative thinking. Thinking about the phenomenology of a client (i.e., what would it be like to walk in the client’s shoes?) can deepen therapeutic rapport, strengthen conceptualization skills, and help build empathy.
The third part of the assignment was for students to select a theoretical approach, along with a rationale for their choice, and create a transcript of a session with the client. The transcript had to include a brain-based counseling intervention (e.g., discussion about Hebb’s rule, neuroplasticity, or memory storage). Neuroscience is an essential tool for helping clients understand what is happening to them. For example, a client who has suffered a trauma and is struggling to understand why they cannot remember events clearly may find respite in knowledge regarding how traumatic memories are stored in their brain. Knowledge about neuroscience can help normalize and validate clients’ experiences.
In summary, six assignments were described above: neuroscience-informed guided metaphor; brain systems, structures, and functions book; dyads; the N-PAL; exploring neuroscience-informed technology; and a case conceptualization paper. The assignments were developed to build students’ understanding of the material and improve their ability to integrate neuroscience into their case conceptualization, treatment planning, and counseling skills. With the growth of neuroscience integration into the counseling profession, best practice dictates that ethical and cultural considerations are addressed.
Ethical Considerations
With nascent developments in the counseling profession, such as neuroscience-informed counseling, come potential risks to clients’ well-being. The ACA Code of Ethics (2014) states that “Counselors practice only within the boundaries of their competence, based on their education, training, supervised experience, state and national professional credentials, and appropriate professional experience” (Standard C.2.a). Scholarly literature has recognized the need for professional counselors to work within their scope of practice (Luke, 2019). As the counseling profession continues to integrate neuroscience into practice, the boundaries of that practice are not always clear. For instance, at what level of integration must counselors be educated in neuroscience explicitly? Who governs the practice of integration and ensures that counselors are following best practice, especially when best practice has not been established?
Each of the three areas described above—neuroeducation, neurofeedback, and metaphor—present distinct ethical challenges. Neuroeducation, like psychoeducation, can become too didactic and place counselors in the role of content expert, as opposed to process expert. It may be easy for counselors to share brain information with their clients, becoming dependent on sharing facts instead of sharing a process. Studies have demonstrated the potential for harm in the helping relationship when clients view helpers as aloof related to neuro-speak, as clients may feel powerless to change their neurobiology (Kim, Ahn, Johnson, & Knobe, 2016; Lebowitz & Ahn, 2014).
Neurofeedback can require advanced knowledge in technological interventions. For example, neurofeedback often requires the use of technological equipment to read and equalize brainwave activity. The Biofeedback Certification International Alliance (n.d.) offers a training program specifically for neurofeedback certification. With certification comes a level of oversight and guidance that promotes proper training of practitioners. However, certification is not a legal requirement to use neurofeedback in counseling practice. Therefore, what is a counselor’s ethical responsibility to acquire education in the use of neurofeedback equipment with clients? How much education is enough to be considered competent? Also, in terms of counselor identity, can neurofeedback be considered counseling or is it an adjunct to counseling?
Given these concerns, the use of metaphor may be a reasonable middle ground wherein counselors are still integrating neuroscience into counseling, but not to the extent that it becomes something different. The use of metaphor is less about teaching clients and more about coming to a mutual understanding of the client’s experience using terms that make sense and matter to the client (Tay, 2012). However, this approach requires the counselor to understand brain function and to stay current in the literature to ensure that the metaphor is accurate and apropos to the client situation. For example, memory has been likened to a video recording of events, yet the function of memory has been demonstrated as far more constructed than a recording of facts. In this case, memory is more like a movie wherein the recordings have been edited to tell the story based on the movie-maker’s experience and desire. It is imperative for professional counselors to consider standards of ethical practice in order to meet the ethical principles of beneficence and nonmaleficence. Similarly, counselors also have a responsibility to be aware of cultural considerations when integrating neuroscience into their counseling practice.
Cultural Considerations
There is a power differential in the therapeutic relationship, in part because of the needs and vulnerabilities that can accompany clients when seeking counseling. Clients might feel disempowered in the counseling relationship because of intersections of race, gender, age, spirituality, and social and economic status (Ratts, Singh, Nassar-McMillan, Butler, & McCullough, 2016). In addition, if counselors use language about the brain that may be perceived as intimidating or unsafe by clients, it could harm the therapeutic relationship. Integrating neuroscience into the counseling profession requires counselors to develop self-awareness surrounding neuroscience terminology and power inequalities in the counseling relationship. It is vital for counselor educators to consider the ethical and cultural implications of teaching a neuroscience-informed counseling course in order to help students learn how to facilitate a therapeutic environment where clients feel safe to process their experiences.
Conclusion
Given the benefits of neuroscience-informed counseling to treat behavioral and mental health concerns, counselor educators must begin to integrate neuroscience-informed counseling into the curriculum. Developing a neuroscience for counselors course using the aforementioned recommendations for course structure and methods for instruction is one approach to meeting this need. Assignments included a neuroscience-informed guided metaphor; development of a brain structures, systems, and functions book; dyads to practice using neuroscience-informed counseling interventions; N-PALs for reflection; a neuroscience-informed technology discussion post; and a summative case conceptualization paper. Integrating neuroscience-informed counseling into the counseling curriculum, while simultaneously addressing ethical and cultural considerations, has the potential to improve graduate students’ case conceptualizations, treatment planning, and counseling skills.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
References
American Counseling Association. (2014). ACA code of ethics. Alexandria, VA: Author.
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: Author.
Association for Experiential Education. (2019a). What is experiential education? Retrieved from https://www.aee.org
/what-is-ee
Association for Experiential Education. (2019b). The principles of practice. Retrieved from https://www.aee.org/what-is-
ee
Badenoch, B. (2008). Being a brain-wise therapist: A practical guide to interpersonal neurobiology. New York, NY:
W.W. Norton & Co.
Biofeedback Certification International Alliance. (n.d.). Neurofeedback certification. Retrieved from https://www.bcia.org
/i4a/pages/index.cfm?pageid=3431
Beeson, E. T., & Field, T. A. (2017). Neurocounseling: A new section of the Journal of Mental Health Counseling. Journal of Mental Health Counseling, 39, 71–83. doi:10.17744/mehc.39.1.06
Council for Accreditation of Counseling and Related Educational Programs. (2015). 2016 CACREP standards. Alexandria, VA: Author.
Dewey, J. (1938). Logic: The theory of inquiry. New York, NY: Holt, Rinehart and Winston.
Faiver, C. M., Brennan, M. C., & Britton, P. J. (2012). Field placement: “Where the rubber hits the road.” In D. M. Perera-Diltz & K. C. MacCluskie (Eds.), The counselor educator’s survival guide: Designing and teaching outstanding courses in community mental health counseling and school counseling (pp. 283–297). New York, NY: Routledge.
Field, T. A, Jones, L. K., & Russell-Chapin, L. A. (2017). Neurocounseling: Brain-based clinical approaches. Alexandria, VA: American Counseling Association.
Fishbane, M. D. (2013). Loving with the brain in mind: Neurobiology & couple therapy. New York, NY: W. W. Norton.
Hayes, S. C. (2004). Acceptance and commitment therapy, relational frame theory, and the third wave of behavioral and cognitive therapies. Behavior Therapy, 35, 639–665. doi:10.1016/S0005-7894(04)80013-3
Hebb, D. O. (1949). The organization of behavior: A neuropsychological theory. New York, NY: Wiley.
Jamrozik, A., McQuire, M., Cardillo, E. R., & Chatterjee, A. (2016). Metaphor: Bridging embodiment to abstraction. Psychonomic Bulletin & Review, 23(4), 1080–1089. doi:10.3758/s13423-015-0861-0
Kalat, J. W. (2019). Biological psychology (13th ed.). Belmont, CA: Cengage.
Kandel, E. R. (1976). Cellular basis of behavior: An introduction to behavioral neurobiology. Oxford, England: W. H. Freeman.
Kandel, E. R., Dudai, Y., & Mayford, M. R. (2014). The molecular and systems biology of memory. Cell, 157, 163–186. doi:10.1016/j.cell.2014.03.001
Kim, N. S., Ahn, W.-K., Johnson, S. G. B., & Knobe, J. (2016). The influence of framing on clinicians’ judgments of the biological basis of behaviors. Journal of Experimental Psychology: Applied, 22, 39–47. doi:10.1037/xap0000070
Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice Hall.
Lawson, G. (2005). The hero’s journey as a developmental metaphor in counseling. The Journal of Humanistic Counseling, Education and Development, 44, 134–144. doi:10.1002/j.2164-490X.2005.tb00026.x
Lebowitz, M. S., & Ahn, W.-K. (2014). Effects of biological explanations for mental disorders on clinicians’ empathy. Proceedings of the National Academy of Sciences, 111, 17786–17790. doi:10.1073/pnas.1414058111
Li, J., Park, E., Zhong, L. R., & Chen, L. (2019). Homeostatic synaptic plasticity as a metaplasticity mechanism—
A molecular and cellular perspective. Current Opinion in Neurobiology, 54, 44–53. doi:10.1016/j.conb.2018.08.010
Lorelle, S., & Michel, R. (2017). Neurocounseling: Promoting human growth and development throughout the
life span. Adultspan Journal, 16(2), 106–119. doi:10.1002/adsp.12039
Luke, C. (2016). Neuroscience for counselors and therapists: Integrating the sciences of mind and brain. Thousand Oaks, CA: SAGE.
Luke, C. (2017). Learner-centered counseling theory: An innovative perspective. Journal of Creativity in Mental Health, 12, 305–319. doi:10.1080/15401383.2016.1249445
Luke, C. (2019). Neuroscience for counselors and therapists: Integrating the sciences of mind and brain (2nd ed.). San Diego, CA: Cognella Academic Press.
Luke, C., Redekop, F., & Jones, L. K. (2018). Addiction, stress, and relational disorder: A neuro-informed
approach to intervention. Journal of Mental Health Counseling, 40, 172–186. doi.org/10.17744/mehc.40.2.06
Michael, T., & Luke, C. (2016). Utilizing a metaphoric approach to teach the neuroscience of play therapy: A pilot study. International Journal of Play Therapy, 25, 45–52.
Makinson, R. A., & Young, J. S. (2012). Cognitive behavioral therapy and the treatment of posttraumatic stress disorder: Where counseling and neuroscience meet. Journal of Counseling & Development, 90, 131–140. doi:10.1111/j.1556-6676.2012.00017.x
Miller, R. (2016). Neuroeducation: Integrating brain-based psychoeducation into clinical practice. Journal of Mental Health Counseling, 38(2), 103–115. doi:10.17744/mehc.38.2.02
Montes, S. (2013, November 25). The birth of the neuro-counselor? Counseling Today, 32–40.
Myers, J. E., & Young, J. S. (2012). Brain wave biofeedback: Benefits of integrating neurofeedback in counseling. Journal of Counseling & Development, 90, 20–28. doi:10.1111/j.1556-6676.2012.00003.x
Ratts, M. J., Singh, A. A., Nassar-McMillan, S., Butler, S. K., & McCullough, J. R. (2016). Multicultural and social justice counseling competencies: Guidelines for the counseling profession. Journal of Multicultural Counseling and Development, 44, 28–48. doi:10.1002/jmcd.12035
Rogers, C. R. (1969). Freedom to learn (1st ed.). Columbus, OH: Merrill.
Russell-Chapin, L. A. (2016). Integrating neurocounseling into the counseling profession: An introduction.
Journal of Mental Health Counseling, 38(2), 93–102. doi:10.17744/mehc.38.2.01
Sakofs, M. (2001). I shouldn’t have done it. Next time I won’t. Perspectives. The Journal of Experiential Education, 24, 5–6. doi:10.1177/105382590102400103
Schore, A. N. (2010). The right brain implicit self: A central mechanism of the psychotherapy change process. In J. Petrucelli (Ed.), Knowing, not-knowing and sort-of-knowing: Psychoanalysis and the experience of uncertainty (pp. 177–202). London, England: Karnac.
Siegel, D. J. (2015). The developing mind: How relationships and the brain interact to shape who we are (2nd ed.). New York, NY: Guilford.
Sweatt, J. D. (2016). Neural plasticity and behavior—Sixty years of conceptual advances. Journal of Neurochemistry, 139, 179–199. doi:10.1111/jnc.13580
Tang, Y. Y., Hölzel, B. K., & Posner, M. I. (2015). The neuroscience of mindfulness meditation. Nature Reviews Neuroscience, 16, 213–225. doi:10.1038/nrn3916
Tay, D. (2012). Applying the notion of metaphor types to enhance counseling protocols. Journal of Counseling & Development, 90, 142–149. doi:10.1111/j.1556-6676.2012.00019.x
Tay, D. (2017a). Exploring the metaphor–body–psychotherapy relationship. Metaphor and Symbol, 32(3), 178–191. doi:10.1080/10926488.2017.1338021
Tay, D. (2017b). The nuances of metaphor theory for constructivist psychotherapy. Journal of Constructivist
Psychology, 30, 165–181. doi:10.1080/10720537.2016.1161571
Tollerud, T. R., & Vernon, A. (2011). Teaching counseling children and adolescents. In K. Erikson (Ed.), Handbook of counselor preparation: Constructivist, developmental, and experiential approaches (pp. 277–293). Thousand Oaks, CA: SAGE.
Wammes, J. D., Meade, M. E., & Fernandes, M. A. (2016). The drawing effect: Evidence for reliable and robust memory benefits in free recall. The Quarterly Journal of Experimental Psychology, 69, 1752–1776. doi:10.4135/9781452230498.n18
World Health Organization. (2012, October 2). I had a black dog, his name was depression. Retrieved from
https://www.youtube.com/watch?v=XiCrniLQGYc
Deborah L. Duenyas is an assistant professor at Kutztown University of Pennsylvania. Chad Luke is an associate professor at Tennessee Technical Institute. Correspondence can be addressed to Deborah Duenyas, OMA Wing – Room 412, P.O. Box 730, Kutztown, PA 19530, duenyas@kutztown.edu.
Jun 6, 2019 | Volume 9 - Issue 2
Clare Merlin-Knoblich, Pamela N. Harris, Erin Chase McCarty Mason
Flipped learning is an innovative teaching approach in which students view pre-recorded video lectures outside of class, then engage in activities applying course concepts during class. By removing lecture from face-to-face class time, instructors free up time in class for students to explore and apply course content. Flipped learning is a particularly useful approach in counselor education, given the need for both content and practice in the discipline. In this study, we examined student classroom engagement in flipped and non-flipped counseling courses. Using a causal comparative method, we compared student engagement via the Classroom Engagement Inventory in four counseling theories course sections. Students in the flipped counseling courses (n = 30) reported statistically higher classroom engagement than students in the non-flipped courses (n = 37). These results lend additional support to the promotion of flipped learning in counselor education.
Keywords: flipped learning, classroom engagement, counselor education, flipped counseling courses, student engagement
Counselor educators are tasked with balancing students’ need to learn course content and their need to apply that content (Gladding & Ivers, 2012; Sommers-Flanagan & Heck, 2012). In recent decades, a new teaching approach has emerged that supports counselor educators in navigating that balance—flipped learning. In flipped learning, students individually view pre-recorded video lectures outside of class so that time spent in class is freed up solely for application-based learning activities (Bishop & Verleger, 2013; Gerstein, 2012; Wallace, Walker, Braseby, & Sweet, 2014). This approach appears especially valuable in counselor education because it allows counseling students to learn critical content relevant to the counseling profession (e.g., counseling theories, techniques), while providing them sufficient in-class time to apply, discuss, or practice content in classroom activities (Merlin, 2016).
Moreover, flipped learning appears worth consideration given its use of both online and face-to-face learning components. Researchers in a variety of disciplines (e.g., communications, political science, social work) have examined student perceptions of online versus face-to-face (F2F) course formats (Bolsen, Evans, & Fleming, 2016; Bristow, Shepherd, Humphreys, & Ziebell, 2011; Okech, Barner, Segoshi, & Carney, 2014; Platt, Yu, & Raile, 2014; Young & Duncan, 2014). Findings from most of the studies suggest that students have positive perceptions of online learning, though a few (Bristow et al., 2011; Young & Duncan, 2014) suggest that more traditional F2F formats are preferred for some subject areas (e.g., communications) and by some types of students (e.g., working vs. non-working). Other studies suggest that blended formats, which contain a mixture of F2F teaching methods and online instruction tools, could be a balanced compromise (Brown, 2016; Nguyen, 2013; Paechter, Kreisler, Luttenberger, Macher, & Wimmer, 2013; Thai, De Wever, & Valcke, 2017). Flipped learning represents one such blended learning approach because it combines teaching and learning efforts in both online spaces (via posted video lectures) and physical classroom spaces (via in-person activities; Brown, 2016).
The prevalence of flipped learning in higher education has increased since 2000, and the teaching approach has recently gained momentum in counselor education in addition to or instead of more traditional, lecture-focused approaches in non-flipped courses (Fulton & Gonzalez, 2015; Merlin, 2016; Merlin-Knoblich & Camp, 2018; Moran & Milsom, 2015). Despite this attention, no researchers have published a comparison of flipped and non-flipped courses in counselor education. In this article, we seek to fill this gap by describing the findings of a causal comparative study comparing one aspect of student experiences in flipped and non-flipped counseling courses—classroom engagement.
Classroom Engagement
Classroom engagement refers to “a student’s active involvement in classroom learning activities” (Wang, Bergin, & Bergin, 2014, p. 1). Researchers have determined that the construct is comprised of three components: affective engagement, behavioral engagement, and cognitive engagement (Archambault, Janosz, Fallu, & Pagani, 2009; Fredricks, Blumenfeld, & Paris, 2004). Since the 1990s, researchers have given substantial attention to student engagement in higher education classrooms (Trowler, 2010). This focus is due in large part to the strong relationships between engagement and positive student outcomes, such as student achievement and graduation rates (Elmaadaway, 2018; Harper & Quaye, 2009; O’Brien & Iannone, 2018; Trowler, 2010). Researchers have acknowledged that student classroom engagement is a multifaceted construct impacted by multiple variables, including instructors’ behaviors with students in the classroom (Krause & Coates, 2008; O’Brien & Iannone, 2018). Thus, we chose to study the potential relationship between instructors’ use of flipped learning and student classroom engagement. In this study, we sought to understand if students reported different perceptions of their classroom engagement levels in flipped and non-flipped counseling courses. Next, we present an overview of the flipped teaching approach and its research base.
Flipped Learning Underpinnings
Flipped learning is a teaching approach in which students view pre-recorded video lectures online outside of class, then meet in class for F2F learning activities in which they apply and explore course content. These activities can include group projects, discussions, skill practice, and experiential activities (Bishop & Verleger, 2013; Gerstein, 2012). Flipped classrooms are different from non-flipped classrooms in that non-flipped classrooms feature in-class lecture for all or part of each F2F class. Thus, students in non-flipped classrooms spend class time listening to an instructor lecture instead of viewing recorded material on course content outside of class and participating in activities in class (McGivney-Burelle & Xue, 2013; Murphy, Chang, & Suaray, 2016). In some non-flipped classrooms, instructors use lecture as the primary instructional approach, whereas in other non-flipped classrooms, instructors pair lecture with experiential activities in class (Cavanagh, 2011; Foldnes, 2016). Given the popularity of experiential learning in counselor education (McAuliffe & Eriksen, 2011), and for the purpose of this study, we define a non-flipped counseling classroom as one in which students engage in both in-class lecture and experiential activities when meeting F2F.
Flipped Learning Process
When designing a flipped classroom, instructors complete two primary tasks. First, they create or select a pre-recorded video lecture with the essential content students need to learn. Instructors can create such videos using screen capture software like Camtasia (www.camtasia.com) and Screencast-O-Matic (www.screencastomatic.com). These programs allow users to create videos with audio and video of an instructor explaining a presentation with slides (e.g., a PowerPoint presentation). Because experts recommend that video lectures are no more than 15–20 minutes in length, instructors must carefully select the most essential content that students would benefit from seeing and hearing explained.
After creating video lectures, instructors design a series of in-class F2F activities for their flipped classroom. In these activities, students apply, discuss, and practice the content they learned in the pre-recorded video lecture. Flipped F2F classroom activities can vary by discipline and instructor, but they often include collaborative group activities, shared projects, and practice sessions. Scholars note that although the video lectures associated with flipped learning often receive the most attention, it is actually the in-class activities that are most crucial to the student learning process (Bergmann & Sams, 2014; Merlin, 2016).
Flipped Learning in Higher Education
As flipped learning has grown in popularity, so too has its research base. Researchers have studied a range of constructs related to the approach, including student and instructor perspectives (Gilboy, Heinerichs, & Pazzaglia, 2015; Hao, 2016; Long, Cummins, & Waugh, 2017; Nouri, 2016; Wanner & Palmer, 2015) and student outcomes (Baepler, Walker, & Driessen, 2014; Davies, Dean, & Ball, 2013; Foldnes, 2016; McLaughlin et al., 2013; Murphy et al., 2016). Researchers also have studied flipped learning in a variety of disciplines, including chemistry (Baepler et al., 2014), engineering (Kim, Kim, Khera, & Getman, 2014), public health (Simpson & Richards, 2015), pharmacy (McLaughlin et al., 2013), and information systems (Davies et al., 2013). As described below, they have consistently found positive outcomes related to flipped learning, with occasional incongruences.
Research on student perceptions of flipped learning has indicated that this teaching approach is generally enjoyed (Gilboy et al., 2015; Hao, 2016; Nouri, 2016). For example, in a sample of 142 nutrition students, 62% of participants reported preferring flipped learning to a traditional lecture format (Gilboy et al., 2015). In a sample of 240 research methods students, 75% of participants reported having positive attitudes toward flipped learning after completing flipped courses (Nouri, 2016). Moreover, in literature reviews of flipped learning research, authors concluded that student perceptions of flipped learning are mostly positive (Bishop & Verleger, 2013; Zainuddin & Halili, 2016).
In general, researchers have found higher student achievement in flipped classrooms compared to non-flipped classrooms (Baepler et al., 2014; Davies et al., 2013; Foldnes, 2016; McLaughlin et al., 2013; Murphy et al., 2016). For example, Foldnes (2016) found that the exam scores of statistics students in a
flipped learning course were 12% higher compared to those in a non-flipped course. Murphy and colleagues (2016) also compared test scores in flipped and non-flipped undergraduate algebra classes and found that flipped classroom final exam scores increased 13% compared to non-flipped classroom scores.
Increased achievement in flipped classrooms may be due to increased student engagement (McLaughlin et al., 2013). Researchers have found a perceived increase in engagement in flipped classrooms from both student and instructor perspectives (Faculty Focus, 2015; Lucke, Dunn, & Christie, 2017; Simpson & Richards, 2015; Wanner & Palmer, 2015). For instance, in their study of engineering students who participated in a course before and after it was flipped, Lucke and colleagues (2017) found that students reported an increase in engagement. Instructors also noted “a substantial increase in the level of observed student engagement” after the course was flipped (p. 54). Similarly, Simpson and Richards (2015) surveyed students who completed a flipped undergraduate health course and found that students reported that the flipped format enhanced their course engagement.
Flipped learning is a valuable instructional approach in counselor education, given its student-focused nature. Despite this relevance, research on flipped learning in counselor education is limited (Merlin, 2016). To date, researchers have published only three studies on flipped learning in counselor education. Moran and Milsom (2015) described flipped learning with 15 graduate students in a school counseling foundations course. They assessed student perceptions of the flipped course using Likert scale ratings, and students reported that in-class activities facilitated their learning more than pre-class activities. Fulton and Gonzalez (2015) studied two flipped career development courses by distributing pre- and posttests to students. They found overall increases in attitudes about career counseling. Lastly, Merlin-Knoblich and Camp (2018) conducted a qualitative case study to explore counseling student experiences in a flipped life span development course. Their participants reported that the flipped course was enjoyable, beneficial, and engaged them in learning inside and outside of the classroom.
Purpose and Rationale for the Study
Previous studies about flipped learning in counselor education are useful in drawing attention to use of the teaching approach in the field (Fulton & Gonzalez, 2015; Merlin-Knoblich & Camp, 2018; Moran & Milsom, 2015). However, across these studies, researchers did not employ a comparison group to examine if flipped learning courses produce different outcomes than non-flipped courses. Given this critical variable in understanding the value of flipped learning, research is needed on the impact the approach has on counseling students compared to non-flipped teaching approaches. To fill this research gap, we chose to compare flipped and non-flipped counseling courses by examining student classroom engagement.
Classroom engagement is the amount of active involvement a student has in learning activities while completing a course (Wang et al., 2014). We chose to study classroom engagement for three reasons. First, due to our interest in comparing flipped and non-flipped counseling courses, it was imperative to measure a construct specific to the individual class setting. Student classroom engagement refers to student involvement at the classroom level, which is more specific than overall school engagement (Wang et al., 2014). Second, given the lack of research on outcomes related to flipped learning in counselor education, we sought to understand if the teaching approach appears to impact classroom engagement, which may contribute to greater student enjoyment and better comprehension of counseling concepts. Lastly, although researchers have studied classroom engagement in previous studies on flipped learning, the topic has not been widely reviewed, and a need exists for a greater understanding of how flipped learning impacts student classroom engagement (Faculty Focus, 2015; Lucke et al., 2017; McLaughlin et al., 2013; Simpson & Richards, 2015; Wanner & Palmer, 2015).
Our research question was: Do significant differences exist between student classroom engagement levels in flipped counseling course sections and non-flipped counseling course sections? We hypothesized that the classroom engagement levels of students in the flipped counseling course sections would be significantly higher statistically than those of students in the non-flipped counseling course sections.
Method
We used a causal comparative design (Creswell & Creswell, 2018) to study student engagement in flipped and non-flipped counseling courses at a medium-sized public university in the mid-Atlantic region. In a causal comparative study, researchers compare groups by a cause, or independent variable, that has already occurred (Creswell & Creswell, 2018). In this study, the cause was a flipped or non-flipped teaching approach in counseling theories courses.
Procedures
The university where we conducted this study has a small master’s counseling program accredited by the Council for Accreditation of Counseling & Related Educational Programs (CACREP) and holds one class section for every course taught each semester. In order to compare a similar counseling course taught in both a flipped and non-flipped approach, we compared a flipped Theories for Counseling Children and Adolescents course (“experimental group”) to a non-flipped Counseling Theories course (“control group”) at the same university. Both courses include parallel emphases on counseling theories, as shown in Table 1. To obtain a sample large enough for inferential statistical analysis, we collected data in two subsequent years from students in two flipped Theories for Counseling Children and Adolescents courses and two non-flipped Counseling Theories courses. All courses met weekly across a 15-week fall semester.
Table 1
Course Topics in Flipped and Non-Flipped Courses Studied
| Flipped Theories for Counseling Children and Adolescents |
Non-flipped Counseling Theories |
| Psychoanalytic Counseling |
Psychoanalytic Counseling |
| Person-Centered Counseling |
Person-Centered Counseling |
| Gestalt Therapy |
Gestalt Therapy |
| Adlerian Counseling |
Adlerian Counseling |
| Reality Therapy |
Reality Therapy |
| Cognitive Behavioral Therapy |
Cognitive Behavioral Therapy |
| Behavior Therapy |
Behavior Therapy |
| Solution-Focused Brief Therapy |
Postmodern Approaches |
| Strengths-Based Counseling |
Existential Counseling |
| Motivational Interviewing |
Feminist Therapy |
| Play Therapy |
Family Systems Therapy |
We did not randomly assign study participants to course sections, but instead recruited participants already in existing groups based on the university’s prescribed counseling program of study. Students in the Counseling Theories courses were in their first year and students in Theories for Counseling Children and Adolescents courses were in their second year. No participants were taking both courses at the same time. The flipped Theories for Counseling Children and Adolescents course was the only flipped course in the counseling program at the time of the study.
Flipped course sections. The first author taught Theories for Counseling Children and Adolescents during the first year of data collection, and the second author taught the course in the second year of data collection. Although the use of different instructors was not intentional (and instead due to hiring changes), the first and second authors used identical flipped learning approaches in an effort to ensure that the change in instructors did not impact the study results. They both used Bergmann and Sam’s (2014) traditional flipped learning model when teaching their courses and each recorded their own video lectures using Screencast-O-Matic software. The instructors assigned these video lectures as homework prior to attending class. Students also were required to read selected book chapters and research articles on the course topics. To ensure compliance, the instructors asked students to answer pre-class questions about the topics online before coming to class. Furthermore, students’ answers allowed the instructors to evaluate comprehension of the material prior to class and adjust class activities as needed. For example, pre-class questions often asked students to explain key concepts. If the majority of student answers revealed that they had a vague or incorrect understanding of a counseling theory, the instructor allotted more class time to addressing student misunderstanding.
During class, each instructor facilitated a range of activities to help students explore and apply course content. For example, groups of students were asked to rehearse and demonstrate counseling techniques to the class. Students also engaged in large and small group discussions about course topics. They sometimes analyzed case studies and watched videos of counseling demonstrations. Lastly, instructors frequently hosted guest speakers with expertise in the topics. Table 2 includes an example class lesson plan and corresponding assigned homework from an example flipped class the first author taught in Theories for Counseling Children and Adolescents.
Table 2
Example Flipped Learning Lesson Plan—Theories for Counseling Children and Adolescents
| Context |
Task |
Time Required |
| Out-of-class |
Video lecture – Gestalt and Adlerian Counseling Theories |
20 minutes |
|
Textbook chapters – Gestalt Counseling, Adlerian Counseling |
80 minutes |
| In-class |
Welcome – Overview and follow-ups |
5 minutes |
|
Viewing Gestalt Counseling – Students view and discuss two YouTube videos of Gestalt counselors.
Practicing Gestalt techniques – Students rehearse a role-play of a Gestalt technique and show the technique to the class. |
20 minutes
45 minutes |
|
Guest speaker – Adlerian counselor is guest speaker to describe and discuss his counseling approach. |
45 minutes |
|
Case studies – Students analyze case studies from an Adlerian perspective in groups, then discuss analyses with the class. |
30 minutes |
|
Counseling practice – Students form pairs and practice counseling using an Adlerian or Gestalt approach. |
30 minutes |
|
Closing – Questions and review |
5 minutes |
Non-flipped course sections. The non-flipped counseling course in this study was Counseling Theories, taught by the same faculty member for both semesters in which the researchers collected data. This faculty member was not an author on the manuscript. Table 1 shows a comparison of the counseling theories taught in the flipped (experimental) and non-flipped (control) counseling courses studied. Students read textbook chapters for homework prior to attending each class. The instructor spent the first half of each class lecturing about the course material, then the second half engaging students in group discussion and hosting guest speakers who were experts in the topics. In this way, the course was not flipped, but it also was not strictly a lecture course. It was “lecture-based,” and regularly involved in-class student activities, as is often the case in counselor education (Cavanagh, 2011; Foldnes, 2016). Table 3 includes an example lesson plan for a non-flipped class session in Counseling Theories.
Table 3
Example Non-Flipped Learning Lesson Plan—Counseling Theories
Context Task Time Required
Out-of-class Textbook chapters – Gestalt Counseling, Adlerian Counseling 80 minutes
In-class Welcome – Overview and follow-ups 5 minutes
Lecture – Didactically present information about Gestalt and 120 minutes
Adlerian counseling approaches
Guest speaker – Adlerian counselor is guest speaker to 45 minutes
describe and discuss his counseling approach.
Closing – Questions and review 10 minutes
Data collection. After obtaining IRB approval, we recruited participants during the final week of each semester by explaining the study to course participants. We described the purpose of the study as “to examine student engagement in counseling courses” in an attempt to prevent participant bias that could have emerged if students knew we were studying engagement related to flipped or non-flipped teaching approaches. We informed students that study participation was voluntary and anonymous and emphasized that participation had no impact on course grades. We distributed paper-and-pencil questionnaires to students in both sections of Theories for Counseling Children and Adolescents and the first section of Counseling Theories. We distributed the questionnaire electronically to students in the second section of Counseling Theories due to in-person scheduling conflicts. All participants signed an informed consent form prior to participating.
Participants
Sixty-seven master’s students participated in the study. Thirty participants were in the experimental group, completing the flipped theories course (100% participation rate). Thirty-seven participants were in the control group, completing the non-flipped theories course (93% participation rate). Given the first and second authors’ familiarity with the participants as students, we chose not to collect participants’ individual identifying demographic information (including degree specialty) because doing so might identify students as participants and cause participant bias. For example, a small number of students in the courses identified as male, African American, or Asian American, and if we asked these students to report their demographic information in the study, this information may have unintentionally identified the participants. We can report, though, that the control group participants included first-year school, clinical mental health, couples and family, and addictions counseling students. The experimental group participants included second-year school counseling and school psychology students. The average number of video lectures reportedly viewed by the experimental group participants was 7.4 (out of eight). Video lectures were not a part of the non-flipped course (control group).
Instrumentation
We distributed the Classroom Engagement Inventory (CEI; Wang et al., 2014) to participants to measure student classroom engagement because it comprehensively measures affective, behavioral, and cognitive engagement. Moreover, it can be used to measure engagement specific to the classroom level, rather than overall school or program engagement (Wang et al., 2014). Although Wang and colleagues (2014) developed the instrument with students in grades 4 through 12, they found that its factor structure was invariant when used with participants of different ages and grade levels, suggesting its relevance in higher education settings.
The CEI consists of five subscales. They are: Affective Engagement (positive emotions students could encounter in class, ω = .90), Behavioral Engagement–Compliance (students’ compliance with classroom norms, ω = .82), Behavioral Engagement–Effortful Class Participation (students’ self-directed classroom behaviors, ω = .82), Cognitive Engagement (mental effort expended, ω = .88), and Disengagement (cognitive and behavioral aspects of not engaging in class, ω = .82; Wang et al., 2014). Example items are: “I get really involved in class activities” (Behavioral Engagement–Effortful Class Participation), “I feel excited” (Affective Engagement), and “I go back over things when I don’t understand” (Cognitive Engagement; Wang et al., 2014, p. 5).
The instrument has 21 items and a 5-point frequency Likert-type scale ranging from never to hardly ever, monthly, weekly, and each day of class. We adapted the scale to be a 4-point scale by removing the answer choice each day of class because both courses only met once per week, therefore each day of class was synonymous with weekly.
Data Analysis
Using SPSS, we first analyzed internal consistency using Cronbach’s alpha to ensure that reducing the 5-point scale to a 4-point scale did not weaken reliability to an unacceptable degree. Then we ran independent samples t-tests to test for statistical significance at p < .05 in order to determine if experimental and control group scores differed by chance. We also ran Cohen’s d in SPSS to measure effect size, which quantifies the extent that the control group and experimental group diverged in the study (Thompson, 2006). We followed Cohen’s (1969) interpretation guidelines of small (0.2), medium (0.5), and large (0.8) effect sizes. We tested for significance among items grouped by scale, as well as overall measure of classroom engagement.
Results
The internal consistency for our results was deemed acceptable (α = .85). We then compared classroom engagement for students in the flipped counseling courses to students in the non-flipped counseling courses in six ways. Table 4 contains a summary of each of these comparisons.
Table 4
Statistical and Practical Significance from Experimental and Control Group Comparisons
CEI Scale p Cohen’s d
Affective Engagement .013 0.61
Behavioral Engagement–Compliance .038 0.50
Behavioral Engagement–Effortful Class Participation .344
Cognitive Engagement .013 0.64
Disengagement .005 -0.70
Overall Classroom Engagement .005 0.70
Affective and Behavioral Engagement
First, we compared the affective engagement between students in the experimental group (flipped) and the control group (non-flipped) courses. Based on a scale of 1 (never) to 4 (weekly), scores on the Affective Engagement subscale averaged 3.68 (SD = 0.32) for the experimental group and 3.44 (SD = 0.48) for the control group. This was a statistically significant difference (p = .013) with a medium effect size (Cohen’s d = 0.61), indicating that students in the flipped course self-reported significantly more affective engagement than students in the non-flipped course. We also compared Behavioral Engagement–Compliance subscale scores among both groups. Experimental group participants had an average Behavioral Engagement–Compliance score of 3.93 (SD = 0.18), whereas control group participants had a lower average Behavioral Engagement–Compliance score of 3.79 (SD = 0.35). This was a statistically significant difference (p = .038) with a medium effect size (Cohen’s d = 0.50), indicating that students in the flipped course self-reported significantly more behavioral engagement in terms of compliance compared to the students in the non-flipped course. We further compared Behavioral Engagement–Effortful Class Participation subscale scores. Although the average experimental group score for this dimension (M = 3.40, SD = 0.50) was higher than the average control group score (M = 3.28, SD = 0.47), the difference was not statistically significant (p = .344), indicating the students in the flipped counseling course were not significantly different in regards to their reported effort in class.
Cognitive Engagement and Disengagement
Next, we examined cognitive engagement for both groups. Students in the experimental group had an average Cognitive Engagement subscale score of 3.43 (SD = 0.38), and those in the control group had a lower average Cognitive Engagement score of 3.13 (SD = 0.54). This was a statistically significant difference in cognitive engagement levels (p = .013) with a medium effect size (Cohen’s d = 0.64). Students in the flipped course self-reported significantly more cognitive engagement than students in the non-flipped course. We also compared classroom disengagement among participants in both groups. Experimental group participants had an average Disengagement subscale score of 1.81 (SD = 0.50), and control group participants had a higher average Disengagement score of 2.25 (SD = 0.68). These scores indicate that experimental group participants had lower perceived levels of disengagement, a difference that was statistically significant (p = .005) and had a medium effect size (Cohen’s d = -0.70). In other words, students in the non-flipped course self-reported significantly more disengagement than those in the flipped course.
Overall Classroom Engagement
Lastly, we examined overall classroom engagement between both groups; despite its dimensions, classroom engagement can be considered a single overall construct (Wang et al., 2014). To do so, we combined and averaged participants’ responses for all subscales except Disengagement. This resulted in an Overall Classroom Engagement score of 3.55 (SD = 0.24) for the experimental group and 3.34 (SD = 0.35) for the control group. These scores represent a statistically significant difference between groups (p = .005) with a medium effect size (Cohen’s d = 0.70). That is to say, students in the flipped course had significantly higher perceptions of overall engagement than did the students in the non-flipped course.
Discussion
This study represented the first of its kind comparing students’ self-reported engagement in related flipped and non-flipped counseling courses. We sought to answer the question: Do significant differences exist between student classroom engagement levels in flipped counseling course sections and non-flipped counseling course sections? Our hypothesis that the classroom engagement levels of participants in the flipped counseling course sections would be significantly higher statistically than those of participants in the non-flipped counseling course sections was confirmed for all but one of the measures we examined.
Average perceived classroom engagement ratings were relatively high across all sections studied, including the non-flipped sections, with engagement levels measured by the CEI ranging from 3.13 to 3.93. These values indicate that participants perceived themselves to be engaged in their classrooms at least monthly if not weekly. Such high engagement ratings suggest that master’s counseling and school psychology students in our sample were generally interested and involved in the learning process in their classrooms. When separated, however, findings indicate that students in the flipped learning course sections may have felt even more frequently engaged than their non-flipped course section counterparts. Specifically, in five of the six measures examined (Affective Engagement, Behavioral Engagement–Compliance, Cognitive Engagement, Disengagement, and Overall Classroom Engagement), participants in the flipped counseling course reported significantly greater classroom engagement than in the non-flipped counseling course. This is the first study in which researchers found increased engagement among a sample of students in a flipped counseling course, and it builds a growing case for flipped learning in counselor education.
Participants in the flipped learning course sections may have reported more frequent classroom engagement given differences in the way class time was spent in the flipped and non-flipped courses. In the flipped course sections, participants spent nominal time in class listening to lecture. Instead, their F2F class time consisted of active application-based activities, such as group discussions, skills practice, and guest speakers. Although participants in the non-flipped course sections also engaged in some of these activities during class (i.e., discussion and guest speakers), they only spent part of class engaged in activities, as at least half of class was reserved for lecture by the instructor. Participants’ higher reported classroom engagement in the flipped course sections might indicate that they found a full class period of application-based activities more engaging than spending only part of class on these activities.
Although no previous studies have used the CEI to measure student engagement in flipped and non-flipped counseling courses, researchers have studied student and instructor perceptions of student engagement in flipped classrooms. The overall increased student engagement in the flipped course sections aligns with the findings of Simpson and Richards (2015) and Lucke and colleagues (2017), who found that students reported increased classroom engagement in flipped learning courses. Although we only surveyed students about their perceived classroom engagement, findings also reflect previous research on instructor perceptions that flipped classrooms increase student classroom engagement (Faculty Focus, 2015; Wanner & Palmer, 2015). For example, in a survey of 1,087 Faculty Focus (2015) readers who utilized flipped learning, 75% of participants indicated observing improved student engagement in flipped classrooms compared to those that were not flipped.
Findings also support previous research indicating that hybrid learning approaches like flipped learning may be more appealing to students than courses held solely online or solely through F2F means. Further research is needed to understand if preferences for flipped learning courses vary by student characteristics, such as working or non-working status. These characteristics have been correlated with preferences for online learning instead of F2F learning, and associations between working status and flipped learning preferences have not previously been examined (Brown, 2016; Nguyen, 2013; Paechter et al., 2013; Thai et al., 2017).
One subscale we compared, Behavioral Engagement–Effortful Class Participation, was not significantly different among students in the flipped and non-flipped counseling courses. This construct refers to students’ self-directed behavioral engagement in class versus behaviors that are compliant with classroom norms (Fredricks et al., 2004; Wang et al., 2014). Effortful class participation includes self-directed behaviors and efforts to become invested in learning (Wang et al., 2014). It might not have differed among students due to the student population used in this study—graduate counseling and school psychology students. Students were voluntarily pursuing master’s degrees in their areas of choice and subsequently had high levels of motivation toward the courses. Students in both sections were likely invested in their coursework, and this investment may not have been affected by whether or not the courses were flipped.
This study’s findings add to a growing body of research demonstrating positive findings when flipped courses are compared to non-flipped ones. Researchers have consistently found that students in flipped courses perform better than those in non-flipped courses (Day & Foley, 2006; Foldnes, 2016; Murphy et al., 2016; Thai et al., 2017). Given that higher classroom engagement is associated with better academic performance (O’Brien & Iannone, 2018; Trowler, 2010; Wang et al., 2014), the findings in our study may indicate that flipped learning could lead to enhanced academic performance for counseling students.
In counselor education, our findings provide further tentative support for the use of flipped learning within the discipline. They align with Moran and Milsom’s (2015) survey research with school counseling students, Fulton and Gonzalez’s (2015) survey research with career counseling students, and Merlin-Knoblich and Camp’s (2018) case study with life span students demonstrating positive findings on flipped learning in counselor education. The findings from these studies begin to build a credible case for the positive impact that the flipped learning approach might have on graduate counseling students.
Implications for Counselor Education
Pedagogy
Results of this study beg a larger question about the importance of pedagogy in counselor education. If programs are to graduate competent practitioners into the profession, then they must understand how to optimize students’ learning of the counseling discipline. Authors of a journal content analysis of pedagogy in counselor education over a 10-year period revealed that only 14.78% of the articles had a clear basis in learning theory or instructional research (Barrio Minton, Wachter Morris, & Yaites, 2014). Other researchers have called for the need for much more attention to teaching and learning in counselor education (Baltrinic, Jencius, & McGlothlin, 2016; Brackette, 2014; Malott, Hall, Sheely-Moore, Krell, & Cardaciotto, 2014).
Flipped learning is one type of teaching format that is a recognized practice at both the K–12 and undergraduate levels (Kurt, 2017; Sezer, 2016; Zainuddin & Halili, 2016). As students progress in their education, counselor educators need to be aware of how teaching practices must evolve in order to meet the expectations of students at the graduate level. Findings from this study suggest that it is worthwhile to consider flipped learning as a way to engage future students. Furthermore, the significance of findings related to the affective, behavioral, and cognitive engagement in flipped learning might be especially important because the practice of counseling requires simultaneous use of emotional, behavioral, and cognitive skills. The opportunity to preview lecture content before a class allows students to engage in initial cognitive processing and frees up class time for more complex and application tasks engaging with course material (Earley, 2016; Hoffman, 2014; Zainuddin & Halili, 2016). Given the cognitive complexity and skills-oriented nature of counseling courses, it seems preferable to have more time spent on higher-order thinking processes and skills practice. In this way, flipped learning may provide the additional class time needed to increase students’ counseling competence.
Counseling Student Competence
Students’ counseling competence might manifest in both counseling abilities and academic achievement. Academic achievement in counseling programs is reflected in assignment and course grades, as well as counselor examinations like the National Counselor Examination for Licensure and Certification and the Counselor Preparation Comprehensive Examination. Given research in non-counseling disciplines indicating significantly better academic achievement in flipped courses compared to non-flipped courses (Day & Foley, 2006; Foldnes, 2016; Murphy et al., 2016; Thai et al., 2017), counselor educators may want to consider the use of flipped learning in order to improve counseling course grades and exam scores. This improved academic achievement for counseling students could lead to greater numbers of students completing counseling programs and might lead to improved graduation rates among counseling programs with flipped courses.
Counselor Education Training
In addition to the implications for students’ learning in the master’s-level counseling classroom, this study has implications for the training of current and future counselor educators. Previous literature demonstrates a lack of counselor education’s attention to pedagogy and learning theory (Barrio Minton et al., 2014; Brackette, 2014; Malott et al., 2014; McAuliffe & Eriksen, 2011), much less to teaching approaches like flipped learning. Thus, one might conclude that counseling professors either have had little training in teaching and learning or are not publishing about their training in this area. Thankfully, the 2016 CACREP standards include nine standards that address pedagogy in doctoral programs (CACREP, 2016), whereas the former 2009 standards only included two in this area (CACREP, 2009). It is likely that many counselor education doctoral programs are working to better incorporate the revised standards. As such, program coordinators and faculty would be encouraged to expose doctoral students to the literature on, and examples of, flipped learning. They also would be wise to encourage doctoral students to research and publish on pedagogy in counselor education, including flipped learning, to help fill this gap in previous literature.
Limitations and Future Directions
We recognize limitations in this study that ought to be considered. First, the study was limited by its data collection measures. We measured participants’ perceived classroom engagement, which they reported via questionnaires. This self-report nature could reflect student biases or inaccuracies that observed classroom engagement measures might not reflect. Furthermore, experimental group participants were students in courses taught by the first and second authors, and despite the anonymity assured to participants, they might have felt compelled to provide favorable questionnaire responses. Although we did not collect data on participant demographics to ensure anonymity, this lack of demographic data also serves as a limitation, as such information could inform the interpretation of results. In addition, the study is limited by its two types of data collection, as one class completed the questionnaire electronically, whereas all other participants completed the questionnaire in a paper-and-pencil format.
Second, the courses we compared contained similar, though not identical content. Although the content in both courses was similar, as a causal comparative study, we were unable to manipulate course content to ensure that instructors in both courses delivered identical content. For example, the Theories for Counseling Children and Adolescents instructors taught one unit on play therapy, which the Counseling Theories instructor did not teach in her sections.
Third, the flipped course section instructors in this study were different. The first author taught the first flipped learning course section, and one year later, the second author taught the second flipped learning course section. Although they used the same instructional approach, differences in their teaching styles might have impacted student experiences in their courses and consequently, the study results as well. They tried to control for differences in their teaching by meeting to discuss the course and flipped learning teaching in between the two flipped course sections. The first author also shared all course materials (e.g., syllabus, video lectures, lesson plans) with the second author, who used or adapted the materials when she taught the course. We chose not to analyze statistical differences between these course sections due to the small sample size of each section (n = 17 and n = 13).
In addition, the student composition in the flipped and non-flipped courses varied and sample sizes were limited. Due to the causal comparative method used in the study, sample sizes could not be altered and a post hoc power analysis using G*Power indicated that the observed power in our study was 0.64. Additionally, the Counseling Theories class consisted of first-year counseling students in different specialties, whereas the Theories for Counseling Children and Adolescents course consisted of second-year school counseling and school psychology graduate students. The latter course was required in the program of study of both school counseling and school psychology students, and the former course was required in the program of study of all counseling students. These differences might have contributed to different levels of classroom engagement. Admissions standards are the same for master’s counseling and psychology students at the university where the study took place, yet qualitative differences between the counseling and school psychology students might have existed and impacted participants’ reported engagement levels. Furthermore, although no previous literature has indicated that classroom engagement is variable by year or specialty in a master’s program, school counseling and school psychology students may inherently be more engaged in a course specifically about children and adolescents, compared to counseling students in different counseling specialties in a course about counseling theories applied to any population. Similarly, students in their second year of study in a master’s program might be more engaged in classrooms than students in their first year of study because the former are closer to beginning their chosen careers. Students also could have been more engaged in the flipped learning course given that it was the only flipped course in the department at the time this study took place. The novelty of such a class format could have impacted student engagement beyond the nature of the course itself.
Lastly, the CEI was not developed with a sample of graduate students; hence, instrument reliability and validity with this sample is not certain. In their development of the instrument, however, Wang and colleagues (2014) found that the instrument factor structure was invariant by student age, grade level, and other characteristics, indicating it might be statistically sound for populations outside of students in grades 4 through 12.
Despite these limitations, the findings from the study serve as a foundation for continued research. Given that we found significant differences in levels of reported classroom engagement among participants, these differences could be even more substantial if the comparison groups were to consist of identical course content and the same instructor. That is, external validity issues could be reduced if a single instructor taught two sections of the same course, implementing flipped learning in one class but using a traditional lecture-based approach for the other class. An instructor could also teach a flipped counseling course one semester, then teach the same course with a non-flipped approach in a subsequent semester and compare student outcomes from each course.
Future research also could include expanded data collection. In the present study, we distributed the CEI at the end of the semester for all course sections; however, researchers could distribute instruments both during the middle of the semester as well as at the end of the semester to examine significant changes in student engagement. Researchers could also study student outcomes related to flipped learning to assess cognitive changes. For example, does flipped learning impact student achievement? In counselor education, such research could assess student content knowledge through comprehensive exams. Researchers also ought to address the behavioral and affective impacts of flipped learning in counselor education. To examine affective change, researchers could query students about their emotions in flipped counseling courses and how these emotions impact their development as counselors. To assess behavior, researchers could observe counseling students’ behaviors in flipped and non-flipped counseling courses, measuring constructs such as class participation and observed engagement. Finally, the counseling profession would benefit from understanding if flipped learning in counselor education impacts the attainment of actual counseling skills. Researchers might assess counseling performances of students in flipped counseling courses versus those in non-flipped courses.
Conclusion
In this causal comparative study, we measured the classroom engagement levels of master’s students in flipped and non-flipped counseling classrooms. In all but one area measured, we found that participants in the flipped counseling course sections reported significantly higher classroom engagement than participants in the non-flipped counseling course sections. Such research indicates that students may find the flipped classroom experience more engaging than a classroom experience that is lecture-based. Although this is the first study of its kind in counselor education, findings contribute to a case for the use of flipped learning in counseling courses. Counselor educators will benefit from considering applying flipped learning in the courses they teach.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
References
Archambault, I., Janosz, M., Fallu, J. S., & Pagani, L. S. (2009). Student engagement and its relationship with early high school dropout. Journal of Adolescence, 32, 651–670. doi:10.1016/j.adolescence.2008.06.007
Baepler, P., Walker, J. D., & Driessen, M. (2014). It’s not about seat time: Blending, flipping, and efficiency in active learning classrooms. Computers & Education, 78, 227–236. doi:10.1016/j.compedu.2014.06.006
Baltrinic, E. R., Jencius, M., & McGlothlin, J. (2016). Coteaching in counselor education: Preparing doctoral students for future teaching. Counselor Education & Supervision, 55, 31–45. doi:10.1002/ceas.12031
Barrio Minton, C. A., Wachter Morris, C. A., & Yaites, L. D. (2014). Pedagogy in counselor education: A 10-year content analysis of journals. Counselor Education & Supervision, 53, 162–177.
doi:10.1002/j.1556-6978.2014.00055.x
Bergmann, J., & Sams, A. (2014). Flipped learning: Gateway to student engagement. Eugene, OR: International Society for Technology in Education.
Bishop, J. L., & Verleger, M. A. (June, 2013). The flipped classroom: A survey of the research. Paper presented at the meeting of the American Society for Engineering Education Annual Conference and Expo, Atlanta, GA.
Bolsen, T., Evans, M., & Fleming, A. M. (2016). A comparison of online and face-to-face approaches to teaching introduction to American government. Journal of Political Science Education, 12, 302–317. doi:10.1080/15512169.2015.1090905
Brackette, C. M. (2014). The scholarship of teaching and learning in clinical mental health counseling. New Directions for Teaching & Learning, 139, 37–48. doi:10.1002/tl.20103
Bristow, D., Shepherd, C. D., Humphreys, M., & Ziebell, M. (2011). To be or not to be: That isn’t the question! An empirical look at online versus traditional brick-and-mortar courses at the university level. Marketing Education Review, 21, 241–250. doi:10.2753/MER1052-8008210304
Brown, M. G. (2016). Blended instructional practice: A review of the empirical literature on instructors’ adoption and use of online tools in face-to-face teaching. The Internet and Higher Education, 31, 1–10. doi:10.1016/j.iheduc.2016.05.001
Cavanagh, M. (2011). Students’ experiences of active engagement through cooperative learning activities in lectures. Active Learning in Higher Education, 12, 23–33. doi:10.1177/1469787410387724
Cohen, J. (1969). Statistical power analysis for the behavioral sciences. New York, NY: Academic Press.
Council for Accreditation of Counseling and Related Educational Programs. (2009). 2009 CACREP Accreditation Manual. Alexandria, VA: Author.
Council for Accreditation of Counseling and Related Educational Programs. (2016). 2016 CACREP Accreditation Manual. Alexandria, VA: Author.
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Thousand Oaks, CA: SAGE.
Davies, R. S., Dean, D. L., & Ball, N. (2013). Flipping the classroom and instructional technology integration in a college-level information systems spreadsheet course. Educational Technology Research and Development, 61, 563–580. doi:10.1007/s11423-013-9305-6
Day, J. A., & Foley, J. D. (2006). Evaluating a web lecture intervention in a human–computer interaction course. IEEE Transactions on Education, 49, 420–431. doi:10.1109/TE.2006.879792
Earley, M. (2016). Flipping the graduate qualitative research methods classroom: Did it lead to flipped learning? International Journal of Teaching and Learning in Higher Education, 28, 139–147.
Elmaadaway, M. A. N. (2018). The effects of a flipped classroom approach on class engagement and skill performance in a Blackboard course. British Journal of Educational Technology, 49, 479–491.
doi:10.1111/bjet.12553
Faculty Focus. (2015). Special report: Flipped classroom trends: A survey of college faculty. Retrieved from https://www.facultyfocus.com/free-reports/flipped-classroom-trends-a-survey-of-college-faculty/
Foldnes, N. (2016). The flipped classroom and cooperative learning: Evidence from a randomised experiment. Active Learning in Higher Education, 17, 39–49. doi:10.1177/1469787415616726
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74, 59–109. doi:10.3102/00346543074001059
Fulton, C. L., & Gonzalez, L. M. (2015). Making career counseling relevant: Enhancing experiential learning using a “flipped” course design. Journal of Counselor Preparation & Supervision, 7(2), 38–67. doi:10.7729/72.1126
Gerstein, J. (2012). The flipped classroom: The full picture. Retrieved from https://read.amazon.com/?asin=B008ENPEP6
Gilboy, M. B., Heinerichs, S., & Pazzaglia, G. (2015). Enhancing student engagement using the flipped classroom. Journal of Nutrition Education and Behavior, 47, 109–114. doi:10.1016/j.jneb.2014.08.008
Gladding, S. T., & Ivers, N. N. (2012). Group work: Standards, techniques, practice, and resources. In D. M. Perera-Diltz and K. C. MacCluskie (Eds.), The counselor educator’s survival guide: Designing and teaching outstanding courses in community mental health counseling and school counseling (pp. 171–186). New York, NY: Routledge.
Hao, Y. (2016). Exploring undergraduates’ perspectives and flipped learning readiness in their flipped classrooms. Computers in Human Behavior, 59, 82–92. doi:10.1016/j.chb.2016.01.032
Harper, S. R., & Quaye, S. J. (Eds.). (2009). Student engagement in higher education: Theoretical perspectives and practical approaches for diverse populations. New York, NY: Routledge.
Hoffman, E. S. (2014). Beyond the flipped classroom: Redesigning a research methods course for e3 instruction. Contemporary Issues in Education Research, 7, 51–62.
Kim, M. K., Kim, S. M., Khera, O., & Getman, J. (2014). The experience of three flipped classrooms in an urban university: An exploration of design principles. The Internet and Higher Education, 22, 37–50. doi:10.1016/j.iheduc.2014.04.003
Krause, K.-L., & Coates, H. (2008). Students’ engagement in first-year university. Assessment & Evaluation in Higher Education, 33, 493–505. doi:10.1080/02602930701698892
Kurt, G. (2017). Implementing the flipped classroom in teacher education: Evidence from Turkey. Journal of Educational Technology & Society, 20, 211–221.
Long, T., Cummins, J., & Waugh, M. (2017). Use of the flipped classroom instructional model in higher education: Instructors’ perspectives. Journal of Computing in Higher Education, 29, 179–200.
doi:10.1007/s12528-016-9119-8
Lucke, T., Dunn, P. K., & Christie, M. (2017). Activating learning in engineering education using ICT and the concept of ‘Flipping the classroom’. European Journal of Engineering Education, 42, 45–57. doi:10.1080/03043797.2016.1201460
Malott, K. M., Hall, K. H., Sheely-Moore, A., Krell, M. M., & Cardaciotto, L. (2014). Evidence-based teaching in higher education: Application to counselor education. Counselor Education and Supervision, 53, 294–305. doi:10.1002/j.1556-6978.2014.00064.x
McAuliffe, G., & Eriksen, K. (Eds.). (2011). Handbook of counselor preparation: Constructivist, developmental, and experiential approaches. Thousand Oaks, CA: SAGE.
McGivney-Burelle, J., & Xue, F. (2013). Flipping calculus. Problems, Resources, and Issues in Mathematics Undergraduate Studies, 23, 477–486.
McLaughlin, J. E., Griffin, L. M., Esserman, D. A., Davidson, C. A., Glatt, D. M., Roth, M. T., . . . Mumper, R. J. (2013). Pharmacy student engagement, performance, and perception in a flipped satellite classroom. American Journal of Pharmaceutical Education, 77, 1–8. doi:10.5688/ajpe779196
Merlin, C. (2016). Flipping the counseling classroom to enhance application-based learning activities. Journal of Counselor Preparation and Supervision, 8(3), 1–28. doi:10.7729/83.1127
Merlin-Knoblich, C., & Camp, A. (2018). A case study exploring students’ experiences in a flipped counseling course. Counselor Education and Supervision, 57, 301–316. doi:10.1002/ceas.12118
Moran, K., & Milsom, A. (2015). The flipped classroom in counselor education. Counselor Education and Supervision, 54, 32–43. doi:10.1002/j.1556-6978.2015.00068.x
Murphy, J., Chang, J.-M., & Suaray, K. (2016). Student performance and attitudes in a collaborative and flipped linear algebra course. International Journal of Mathematical Education in Science and Technology, 47, 653–673. doi:10.1080/0020739X.2015.1102979
Nguyen, B. T. (2013). Face-to-face, blended, and online instruction: Comparison of student performance and retention in higher education. Dissertation Abstracts International Section A: Humanities and Social Sciences, 73(7-A(E)).
Nouri, J. (2016). The flipped classroom: For active, effective and increased learning—especially for low achievers. International Journal of Educational Technology in Higher Education, 13, 1–10.
doi:10.1186/s41239-016-0032-z
O’Brien, B., & Iannone, P. (2018). Students’ experiences of teaching at secondary school and university: Sharing responsibility for classroom engagement. Journal of Further and Higher Education, 42, 922–936. doi:10.1080/0309877X.2017.1332352
Okech, D., Barner, J., Segoshi, M., & Carney, M. (2014). MSW student experiences in online vs. face-to-face teaching formats. Social Work Education, 33, 121–134. doi:10.1080/02615479.2012.738661
Paechter, M., Kreisler, M., Luttenberger, S., Macher, D., & Wimmer, S. (2013). Communication in e-learning courses. The Internet and Higher Education, 44, 429–433.
doi:10.1007/s11612-013-0223-1
Platt, C. A., Raile, A. N. W., & Yu, N. (2014). Virtually the same? Student perceptions of the equivalence of online classes to face-to-face classes. Journal of Online Learning and Teaching, 10, 489–503.
Sezer, B. (2016). The effectiveness of a technology-enhanced flipped science classroom. Journal of Educational Computing Research, 55, 471–494. doi:10.1177/0735633116671325
Simpson, V., & Richards, E. (2015). Flipping the classroom to teach population health: Increasing the relevance. Nurse Education in Practice, 15, 162–167. doi:10.1016/j.nepr.2014.12.001
Sommers-Flanagan, J., & Heck, N. (2012). Counseling skills: Building the pillars of professional counseling. In D. M. Perera-Diltz and K. C. MacCluskie (Eds.), The counselor educator’s survival guide: Designing and teaching outstanding courses in community mental health counseling and school counseling (pp. 153–170). New York, NY: Routledge.
Thai, N. T. T., De Wever, B., & Valcke, M. (2017). The impact of a flipped classroom design on learning performance in higher education: Looking for the best “blend” of lectures and guiding questions with feedback. Computers & Education, 107, 113–126. doi:10.1016/j.compedu.2017.01.00
Thompson, B. (2006). Role of effect sizes in contemporary research in counseling. Counseling and Values, 50, 176–186. doi:10.1002/j.2161-007X.2006.tb00054.x
Trowler, V. (2010). Student engagement literature review. The Higher Education Academy. Retrieved from http://www.academia.edu/743769/Student_engagement_literature_review
Wallace, M. L., Walker, J. D., Braseby, A. M., & Sweet, M. S. (2014). “Now, what happens during class?” Using team-based learning to optimize the role of expertise within the flipped classroom. Journal on Excellence in College Teaching, 25, 253–273.
Wang, Z., Bergin, C., & Bergin, D. A. (2014). Measuring engagement in fourth to twelfth graded classrooms: The Classroom Engagement Inventory. School Psychology Quarterly, 29, 517–535. doi:10.1037/spq0000050
Wanner, T., & Palmer, E. (2015). Personalizing learning: Exploring student and teacher perceptions about flexible learning and assessment in a flipped university course. Computers and Education, 88, 354–369. doi:10.1016/j.compedu.2015.07.008
Young, S., & Duncan, H. E. (2014). Online and face-to-face teaching: How do student ratings differ? Journal of Online Learning and Teaching, 10, 70–79.
Zainuddin, Z., & Halili, S. H. (2016). Flipped classroom research and trends from different fields of study. International Review of Research in Open and Distributed Learning, 17, 313–340.
doi:10.19173/irrodl.v17i3.2274
Clare Merlin-Knoblich, NCC, is an assistant professor at the University of North Carolina at Charlotte. Pamela N. Harris is an assistant professor at the University of North Carolina at Greensboro. Erin Chase McCarty Mason is an assistant professor at Georgia State University. Correspondence can be addressed to Clare Merlin-Knoblich, 9201 University City Blvd., Charlotte, NC 28223, claremerlin@uncc.edu.
Nov 10, 2018 | Volume 8 - Issue 4
Zachary D. Bloom, Victoria A. McNeil, Paulina Flasch, Faith Sanders
Empathy plays an integral role in the facilitation of therapeutic relationships and promotion of positive client outcomes. Researchers and scholars agree that some components of empathy might be dispositional in nature and that empathy can be developed through empathy training. However, although empathy is an essential part of the counseling process, literature reviewing the development of counseling students’ empathy is limited. Thus, we examined empathy and sympathy scores in counselors-in-training (CITs) in comparison to students from other academic disciplines (N = 868) to determine if CITs possess greater levels of empathy than their non-counseling academic peers. We conducted a MANOVA and failed to identify differences in levels of empathy or sympathy across participants regardless of academic discipline, potentially indicating that counselor education programs might be missing opportunities to further develop empathy in their CITs. We call for counselor education training programs to promote empathy development in their CITs.
Keywords: empathy, sympathy, counselor education, counselors-in-training, therapeutic relationships
Empathy is considered an essential component of the human experience as it relates to how individuals socially and emotionally connect to one another (Goleman, 1995; Szalavitz & Perry, 2010). Although empathy can be difficult to define (Konrath, O’Brien, & Hsing, 2011; Spreng, McKinnon, Mar, & Levine, 2009), within the counseling profession there is agreement that empathy includes both cognitive and affective components (Clark, 2004; Davis, 1980, 1983). When discussing the difference between affective and cognitive empathy, Vossen, Piotrowski, and Valkenburg (2015) described that “whereas the affective component pertains to the experience of another person’s emotional state, the cognitive component refers to the comprehension of another person’s emotions” (p. 66). Regardless of specific nuances among researchers’ definitions of empathy, most appear to agree that “empathy-related responding is believed to influence whether or not, as well as whom, individuals help or hurt” (Eisenberg, Eggum, & Di Giunta, 2010, p. 144). Furthermore, empathy can be viewed as a motivating factor of altruistic behavior (Batson & Shaw, 1991) and is essential to clients’ experiences of care (Flasch et al., in press). As such, empathy is foundational to interpersonal relationships (Siegel, 2010; Szalavitz & Perry, 2010), including the relationships facilitated in a counseling setting (Norcross, 2011; Rogers, 1957).
Rogers (1957) intuitively understood the necessity of empathy in a counseling relationship, which has been verified by the understanding of the physiology of the brain (Badenoch, 2008; Decety & Ickes, 2009; Siegel, 2010) and validated in the counseling literature (Elliott, Bohart, Watson, & Greenberg, 2011). In a clinical context, empathy can be described as both a personal characteristic and a clinical skill (Clark, 2010; Elliott et al., 2011; Rogers, 1957) that contributes to positive client outcomes (Norcross, 2011; Watson, Steckley, & McMullen, 2014). For example, empathy has been identified as a factor that leads to changes in clients’ attachment styles, treatment of self (Watson et al., 2014), and self-esteem development (McWhirter, Besett-Alesch, Horibata, & Gat, 2002). Moreover, researchers regularly identify empathy as a fundamental component of helpful responses to clients’ experiences (Beder, 2004; Flasch et al., in press; Kirchberg, Neimeyer, & James, 1998).
Although empathy is lauded and encouraged in the counseling profession, empathy development is not necessarily an explicit focus or even a mandated component of clinical training programs. The Council for Accreditation of Counseling and Related Educational Programs (CACREP; 2016) identifies diverse training standards for content knowledge and practice among master’s-level and doctoral-level counselors-in-training (CITs), but does not mention the word empathy in its manual for counseling programs. One of the reasons for this could be that empathy is often understood and taught as a microskill (e.g., reflection of feeling and meaning) rather than as its own construct (Bayne & Jangha, 2016). Yet empathy is more than a component of a skillset, and CITs might benefit from a programmatic development of empathy to enhance their work with future clients (DePue & Lambie, 2014).
The application of empathy, or a counselor’s use of empathy-based responses in a therapeutic relationship, requires skill and practice (Barrett-Lennard, 1986; Truax & Carkhuff, 1967). Clark (2010) cautioned, for example, that counselors’ empathic responses need to be congruent with the client’s experience, and that the misapplication of sympathetic responses as empathic responses can interfere in the counseling relationship. In regard to sympathy, Eisenberg and colleagues (2010) explained, “sympathy, like empathy, involves an understanding of another’s emotion and includes an emotional response, but it consists of feelings of sorrow or concern for the distressed or needy other rather than merely feeling the same emotion” (p. 145). Thus, researchers call for counselor educators to do more than increase CITs’ affective or cognitive understanding of another’s experience, and to assist them in differentiating between empathic responses and sympathetic responses in order to better convey empathic understanding and relating (Bloom & Lambie, in press; Clark, 2010).
With the understanding that a counselor’s misuse of sympathetic responses might interrupt a therapeutic dialogue and that empathy is vital to the therapeutic alliance, researchers call for counselor educators to promote empathy development in CITs (Bloom & Lambie, in press; DePue & Lambie, 2014). Although there is evidence that some aspects of empathy are dispositional in nature (Badenoch, 2008; Konrath et al., 2011), which might make the counseling profession a strong fit for empathic individuals, empathy training in counseling programs can increase students’ levels of empathy (Ivey, 1971). However, the specific empathy-promoting components of empathy training are less understood (Teding van Berkhout & Malouff, 2016). Overall, empathy is an essential component of the counseling relationship, counselor competency, and the promotion of client outcomes (DePue & Lambie, 2014; Norcross, 2011). However, little is known about the training aspect of empathy and whether or not counselor training programs are effective in enhancing empathy or reducing sympathy among CITs. Thus, the following question guided this research investigation: Are CITs’ levels of empathy or sympathy different from their academic peers? Specifically, do CITs possess greater levels of empathy or sympathy than students from other academic majors?
Empathy in Counseling
Researchers have established continuous support for the importance of the therapeutic relationship in the facilitation of positive client outcomes (Lambert & Bergin, 1994; Norcross, 2011; Norcross & Lambert, 2011). In fact, the therapeutic relationship is predictive of positive client outcomes (Connors, Carroll, DiClemente, Longabaugh, & Donovan, 1997; Krupnick et al., 1996), accounting for about 30% of the variance (Lambert & Barley, 2001). That is, clients who perceive the counseling relationship to be meaningful will have more positive treatment outcomes (Bell, Hagedorn, & Robinson, 2016; Norcross & Lambert, 2011). One of the key factors in the establishment of a strong therapeutic relationship is a counselor’s ability to experience and communicate empathy. Researchers estimate that empathy alone may account for as much as 7–10% of overall treatment outcomes (Bohart, Elliott, Greenberg, & Watson, 2002; Sachse & Elliott, 2002), making it an important construct to foster in counselors.
Despite the importance of empathy in the counseling process, much of the literature on empathy training in counseling is outdated. Thus, little is known about the training aspect of empathy; that is, how is empathy taught to and learned by counselors? Nevertheless, early scholars (Barrett-Lennard, 1986; Ivey, 1971; Ivey, Normington, Miller, Morrill, & Haase, 1968; Truax & Carkhuff, 1967) posited that counselor empathy is a clinical skill that may be practiced and learned, and there is supporting evidence that empathy training may be efficacious.
In one seminal study, Truax and Lister (1971) conducted a 40-hour empathy training program with 12 counselor participants and identified statistically significant increases in participants’ levels of empathy. In their investigation, the researchers employed methods in which (a) the facilitator modeled empathy, warmth, and genuineness throughout the training program; (b) therapeutic groups were used to integrate empathy skills with personal values; and (c) researchers coded three of participants’ 4-minute counseling clips using scales of accurate empathy and non-possessive warmth (Truax & Carkhuff, 1967). Despite identifying statistically significant changes in participants’ scores of empathy, it is necessary to note that participants who initially demonstrated low levels of empathy remained lower than participants who initially scored high on the empathy measures. In a later study modeled after the Truax and Lister study, Silva (2001) utilized a combination of didactic, experiential, and practice components in her empathy training program, and found that counselor trainee participants (N = 45) improved their overall empathy scores on Truax’s Accurate Empathy Scale (Truax & Carkhuff, 1967). These findings contribute to the idea that empathy increases as a result of empathy training.
More recent researchers (Lam, Kolomitro, & Alamparambil, 2011; Ridley, Kelly, & Mollen, 2011) have identified the most common methods in empathy training programs as experiential training, didactic (lecture), skills training, and other mixed methods such as role play and reflection. In their meta-analysis, Teding van Berkhout and Malouff (2016) examined the effect of empathy training programs across various populations (e.g., university students, health professionals, patients, other adults, teens, and children) using the training methods identified above. The researchers investigated the effect of cognitive, affective, and behavioral empathy training and found a statistically significant medium effect size overall (g ranged from 0.51 to 0.73). The effect size was larger in health professionals and university students compared to other groups such as teenagers and adult community members. Though empathy increased as a result of empathy training studies, the specific mechanisms that facilitated positive outcomes remain largely unknown.
Although research indicates that empathy training can be effective, specific empathy-fostering skills are still not fully understood. Programmatically, empathy is taught to counselors within basic counseling skills (Bayne & Jangha, 2016), specifically because empathy is believed to lie in the accurate reflection of feeling and meaning (Truax & Carkhuff, 1967). But scholars argue that there is more to empathy than the verbal communication of understanding (Davis, 1980; Vossen et al., 2015). For example, in a more recent study, DePue and Lambie (2014) reported that counselor trainees’ scores on the Empathic Concern subscale of the Interpersonal Reactivity Index (IRI; Davis, 1980) increased as a result of engaging in counseling practicum experience under live supervision in a university-based clinical counseling and research center. In their study, the researchers did not actively engage in empathy training. Rather, they measured counseling students’ pre- and post-scores on an empathy measure as a result of students’ engagement in supervised counseling work to foster general counseling skills. Implications of these findings mirror those described by Teding van Berkhout and Malouff (2016), namely that it is difficult to identify specific empathy-promoting mechanisms. In other words, it appears that empathy training, when employed, produces successful outcomes in CITs. However, counseling students’ empathy also increases in the absence of specific empathy-promoting programs. This begs the question: Are counseling programs successfully training their counselors to be empathic, and is there a difference between CITs’ empathy or sympathy levels compared to students in other academic majors? Thus, the purpose of the present study was to (a) examine differences in empathy (i.e., affective empathy and cognitive empathy) and sympathy levels among emerging adult college students, and (b) determine whether CITs had different levels of empathy and sympathy when compared to their academic peers.
Methods
Participants
We identified master’s-level CITs as the population of interest in this investigation. We intended to compare CITs to other graduate and undergraduate college student populations. Thus, we utilized a convenience sample from a larger data set that included emerging adult college students between the ages of 18 and 29 who were enrolled in at least one undergraduate- or graduate-level course at nine colleges and universities throughout the United States. Participants were included regardless of demographic variables (e.g., gender, race, ethnicity).
Participants were recruited from three sources: online survey distribution (n = 448; 51.6%), face-to-face data collection (n = 361; 41.6%), and email solicitation (n = 34; 3.9%). In total, 10,157 potential participants had access to participate in the investigation by online survey distribution through the psychology department at a large Southeastern university; however, the automated system limited responses to 999 participants. We and our contacts (i.e., faculty at other institutions) distributed an additional 800 physical data collection packets to potential participants, and 105 additional potential participants were solicited by email. Overall, 1,713 data packets were completed, resulting in a sample of 1,598 participants after data cleaning. However, in order to conduct the analyses for this study, it was necessary to limit our sample to groups of approximately equal sizes (Hair, Black, Babin, & Anderson, 2010). Therefore, we were limited to the use of a subsample of 868 participants. Our sample appeared similar to other samples included in investigations exploring empathy with emerging adult college students (e.g., White, heterosexual, female; Konrath et al., 2011).
The participants included in this investigation were enrolled in one of six majors and programs of study, including Athletic Training/Health Sciences (n = 115; 13.2%); Biology/Biomedical Sciences/Preclinical Health Sciences (n = 167; 19.2%); Communication (n = 163; 18.8%); Counseling (n = 153; 17.6%); Nursing (n = 128; 14.7%); and Psychology (n = 142; 16.4%). It is necessary to note that students self-identified their major rather than selecting it from a preexisting prompt. Therefore, the researchers examined responses and categorized similar responses to one uniform title. For example, responses of psych were included with psychology. Further, in order to attain homogeneity among group sizes, we included multiple tracks within one program. For example, counseling included participants enrolled in either clinical mental health counseling (n = 115), marriage and family counseling (n = 24), or school counseling (n = 14) tracks. Table 1 presents additional demographic information (e.g., age, race, ethnicity, graduate-level status). It is necessary to note that, because of the constraints of the dataset, counseling students consisted of master’s-level graduate students, whereas all other groups consisted of undergraduate students.
Table 1
Participants’ Demographic Characteristics
| Characteristic |
|
n
|
Total %
|
|
| Age |
18–19 |
460
|
52.4
|
|
|
20–21 |
155
|
17.9
|
|
|
22–23 |
130
|
15.0
|
|
|
24–25 |
58
|
6.7
|
|
|
26–27 |
36
|
4.1
|
|
|
28–29 |
27
|
3.1
|
|
| Gender |
Female |
692
|
79.7
|
|
|
Male |
167
|
19.2
|
|
|
Other |
8
|
0.9
|
|
| Racial |
Caucasian |
624
|
71.9
|
|
| Background |
African American/African/Black |
101
|
11.6
|
|
|
Biracial/Multiracial |
65
|
7.5
|
|
|
Asian/Asian American |
40
|
4.6
|
|
|
Native American |
3
|
0.3
|
|
|
Other |
25
|
2.9
|
|
| Ethnicity |
Hispanic |
172
|
19.8
|
|
|
Non-Hispanic |
689
|
79.4
|
|
| Academic |
Undergraduate |
709
|
81.7
|
|
| Enrollment |
Graduate |
152
|
17.5
|
|
|
Other |
5
|
0.6
|
|
| Academic Major |
Athletic Training/Health Sciences |
115
|
13.2
|
|
|
Biology/Biomedical Sciences/Preclinical Health Sciences |
167
|
19.2
|
|
|
Counseling |
153
|
17.6
|
|
|
Communication |
163
|
18.8
|
|
|
Nursing |
128
|
14.7
|
|
|
Psychology |
142
|
16.4
|
|
Note. N
= 868.
Procedure
The data utilized in this study were collected as part of a larger study that was approved by the authors’ institutional review board (IRB) as well as additional university IRBs where data was collected, as requested. We followed the Tailored Design Method (Dillman, Smyth, & Christian, 2009), a series of recommendations for conducting survey research to increase participant motivation and decrease attrition, throughout the data collection process for both web-based survey and face-to-face administration. Participants received informed consent, assuring potential participants that their responses would be confidential and their anonymity would be protected. We also made the survey convenient and accessible to potential participants by making it available either in person or online, and by avoiding the use of technical language (Dillman et al., 2009).
We received approval from the authors of the Adolescent Measure of Empathy and Sympathy (AMES; Vossen et al., 2015; personal communication with H. G. M. Vossen, July 10, 2015) to use the instrument and converted the data collection packet (e.g., demographic questionnaire, AMES) into Qualtrics (2013) for survey distribution. We solicited feedback from 10 colleagues regarding the legibility and parsimony of the physical data collection packets and the accuracy of the survey links. We implemented all recommendations and changes (e.g., clarifying directions on the demographic questionnaire) prior to data collection.
All completed data collection packets were assigned a unique ID, and we entered the data into the IBM SPSS software package for Windows, Version 22. No identifying information was collected (e.g., participants’ names). Having collected data both in person and online via web-based survey, we applied rigorous data collection procedures to increase response rates, reduce attrition, and to mitigate the potential influence of external confounding factors that might contribute to measurement error.
Data Instrumentation
Demographics profile. We included a general demographic questionnaire to facilitate a comprehensive understanding of the participants in our study. We included items related to various demographic variables (e.g., age, race, ethnicity). Regarding participants’ identified academic program, participants were prompted to respond to an open-ended question asking “What is your major area of study?”
AMES. Multiple assessments exist to measure empathy (e.g., the IRI, Davis, 1980, 1983; The Basic Empathy Scale [BES], Jolliffe & Farrington, 2006), but each is limited by several shortcomings (Carré, Stefaniak, D’Ambrosio, Bensalah, & Besche-Richard, 2013). First, many scales measure empathy as a single construct without distinguishing cognitive empathy from affective empathy (Vossen et al., 2015). Moreover, the wording used in most scales is ambiguous, such as items from other assessments that use words like “swept up” or “touched by” (Vossen et al., 2015), and few scales differentiate empathy from sympathy. Therefore, Vossen and colleagues designed the AMES as an empathy assessment that addresses problems related to ambiguous wording and differentiates empathy from sympathy.
The AMES is a 12-item empathy assessment with three factors: (a) Cognitive Empathy, (b) Affective Empathy, and (c) Sympathy. Each factor consists of four items rated on a 5-point Likert scale with ratings of 1 (never), 2 (almost never), 3 (sometimes), 4 (often), and 5 (always). Higher AMES scores indicate greater levels of cognitive empathy (e.g., “I can tell when someone acts happy, when they actually are not”), affective empathy (e.g., “When my friend is sad, I become sad too”), and sympathy (e.g., “I feel concerned for other people who are sick”). The AMES was developed in two studies with Dutch adolescents (Vossen et al., 2015). The researchers identified a 3-factor model with acceptable to good internal consistency per factor: (a) Cognitive Empathy (α = 0.86), (b) Affective Empathy (α = 0.75), and (c) Sympathy (α = 0.76). Further, Vossen et al. (2015) established evidence of strong test-retest reliability, construct validity, and discriminant validity when using the AMES to measure scores of empathy and sympathy with their samples. Despite being normed with samples of Dutch adolescents, Vossen and colleagues suggested the AMES might be an effective measure of empathy and sympathy with alternate samples as well.
Bloom and Lambie (in press) examined the factor structure and internal consistency of the AMES with a sample of emerging adult college students in the United States (N = 1,598) and identified a 3-factor model fitted to nine items that demonstrated strong psychometric properties and accounted for over 60% of the variance explained (Hair et al., 2010). The modified 3-factor model included the same three factors as the original AMES. Therefore, we followed Bloom and Lambie’s modifications for our use of the instrument.
Data Screening
Before running the main analysis on the variables of interest, we assessed the data for meeting the assumptions necessary to conduct a one-way between-subjects MANOVA. First, we conducted a series of tests to evaluate the presence of patterns in missing data and determined that data were missing completely at random (MCAR) and ignorable (e.g., < 5%; Kline, 2011). Because of the robust size of these data (e.g., > 20 observations per cell) and the minimal amount of missing data, we determined listwise deletion to be best practice to conduct a MANOVA and to maintain fidelity to the data (Hair et al., 2010; Osborne, 2013).
Next, we utilized histograms, Q-Q plots, and boxplots to assess for normality and identified non-normal data patterns. However, MANOVA is considered “robust” to violations of normality with a sample size of at least 20 in each cell (Tabachnick & Fidell, 2013). Thus, with our smallest cell size possessing a sample size of 115, we considered our data robust to this violation. Following this, we assumed our data violated the assumption for multivariate normality. However, Hair et al. (2010) stated “violations of this assumption have little impact with larger sample sizes” (p. 366) and cautioned that our data might have problems achieving a non-significant score for Box’s M Test. Indeed, our data violated the assumption of homogeneity of variance-covariance matrices (p < .01). However, this was not a concern with these data because “a violation of this assumption has minimal impact if the groups are of approximately equal size (i.e., largest group size ÷ smallest group size < 1.5)” (Hair et al., 2010, p. 365).
It is necessary to note that MANOVA is sensitive to outlier values. To mitigate against the negative effects of extreme scores, we removed values (n = 3) with standardized z-scores greater than +4 or less than -4 (Hair et al., 2010). This resulted in a final sample size of 868 participants.
We also utilized scatterplots to detect the patterns of non-linear relationships between the dependent variables and failed to identify evidence of non-linearity. Therefore, we proceeded with the assumption that our data shared linear relationships. We also evaluated the data for multicollinearity. Participants’ scores of Affective Empathy shared statistically significant and appropriate relationships with their scores of Cognitive Empathy (r = .24) and Sympathy (r = .43). Similarly, participants’ scores of Cognitive Empathy were appropriately related to their scores of Sympathy (r = .36; p < .01). Overall, we determined these data to be appropriate to conduct a MANOVA. Table 2 presents participants’ scores by academic discipline.
Table 2
AMES Scores by Academic Major
|
Scale
|
Mean (M)
|
SD
|
Range
|
| Athletic Training |
|
|
|
|
Affective Empathy
|
3.20
|
0.80
|
4.00 |
|
Cognitive Empathy
|
3.80
|
0.62
|
3.33 |
|
Sympathy
|
4.34
|
0.55
|
2.67 |
| Biomedical Sciences |
|
|
|
|
Affective Empathy
|
3.12
|
0.76
|
4.00 |
|
Cognitive Empathy
|
3.66
|
0.59
|
3.00 |
|
Sympathy
|
4.30
|
0.61
|
2.00 |
| Communication |
|
|
|
|
Affective Empathy
|
3.18
|
0.87
|
4.00 |
|
Cognitive Empathy
|
3.80
|
0.62
|
2.67 |
|
Sympathy
|
4.27
|
0.69
|
3.00 |
| Counseling |
|
|
|
|
Affective Empathy
|
3.32
|
0.60
|
3.33 |
|
Cognitive Empathy
|
3.83
|
0.48
|
4.00 |
|
Sympathy
|
4.32
|
0.54
|
2.00 |
| Nursing |
|
|
|
|
Affective Empathy
|
3.37
|
0.71
|
3.67 |
|
Cognitive Empathy
|
3.80
|
0.59
|
2.67 |
|
Sympathy
|
4.46
|
0.49
|
2.00 |
| Psychology |
|
|
|
|
Affective Empathy
|
3.28
|
0.78
|
4.00 |
|
Cognitive Empathy
|
3.86
|
0.59
|
2.67 |
|
Sympathy
|
4.35
|
0.65
|
2.67 |
Note. N
= 868.
Results
Participants’ scores on the AMES were used to measure participants’ levels of empathy and sympathy. Descriptive statistics were used to compare empathy and sympathy levels between counseling students and emerging college students from other disciplines. CITs recorded the second highest levels of affective empathy (M = 3.32, SD = .60) and cognitive empathy (M = 3.83, SD = 0.48), and the fourth highest levels of sympathy (M = 4.32, SD = 0.54) when compared to students from other disciplines. Nursing students demonstrated the highest levels of affective empathy (M = 3.37, SD = .71) and sympathy (M = 4.46, SD = .49), and psychology students recorded the highest levels of cognitive empathy (M = 3.86, SD = 0.59) when compared to students from other disciplines. The internal consistency values for each empathy and sympathy subscale on the AMES were as follows: Cognitive Empathy (α = 0.86), Affective Empathy (α = 0.75), and Sympathy (α = 0.76).
We performed a MANOVA to examine differences in empathy and sympathy in emerging adult college students by academic major, including counseling. Three dependent variables were included: affective empathy, cognitive empathy, and sympathy. The predictor for the MANOVA was the 6-level categorical “academic major” variable. The criterion variables for the MANOVA were the levels of affective empathy (M = 3.24, SD = .76), cognitive empathy (M = 3.80, SD = .58), and sympathy
(M = 4.34, SD = .60), respectively. The multivariate effect of major was statistically non-significant:
p = .062, Wilks’s lambda = .972, F (15, 2374.483) = 1.615, η2 = .009. Furthermore, the univariate F scores for affective empathy (p = .139), cognitive empathy (p = .074), and sympathy (p = .113) were statistically non-significant. That is, there was no difference in levels of affective empathy, cognitive empathy, or sympathy based on academic major, including counseling. Thus, these data indicated that CITs were no more empathic or sympathetic than students in other majors, as measured by the AMES.
We also examined these data for differences in affective empathy, cognitive empathy, and sympathy based on data collection method and educational level. However, we failed to identify a statistically significant difference between groups in empathy or sympathy based on data collection method
(e.g., online survey distribution, face-to-face data collection, email solicitation) or by educational level (e.g., master’s level or undergraduate status). Thus, these data indicate that data collection methods and participants’ educational level did not influence our results.
Discussion
The purpose of the present study was to (a) examine differences in empathy (i.e., affective empathy and cognitive empathy) and sympathy levels among emerging adult college students, and (b) determine whether CITs demonstrate different levels of empathy and sympathy when compared to their academic peers. We hypothesized that CITs would record greater levels of empathy and lower levels of sympathy when compared to their non-counseling peers, because of either their clinical training from their counselor education program or the possibility that the counseling profession might attract individuals with strong levels of dispositional empathy. Participants’ scores on the AMES were used to measure participants’ levels of empathy and sympathy. We conducted a MANOVA to determine if participants’ levels of empathy and sympathy differed when grouped by academic majors. CITs did not exhibit statistically significant differences in levels of empathy or sympathy when compared to students from other academic programs. In fact, CITs recorded levels of empathy that appeared comparable to students from other academic disciplines. This finding is consistent with literature indicating that even if empathy training is effective, counselor education programs might not be emphasizing empathy development in CITs or employing empathy training sufficiently. We also failed to identify statistically significant differences in participants’ AMES scores when grouping data by collection method or participants’ educational level. Thus, we believe our results were not influenced by our data collection method or by participants’ educational level.
Implications for Counselor Educators
The results from this investigation indicated that there was not a statistically significant difference in participants’ levels of cognitive or affective empathy or sympathy regardless of academic program, suggesting that CITs do not possess more or less empathy or sympathy than their academic peers. This was true for students in all majors under investigation (i.e., athletic training/health sciences, biology/biomedical sciences/preclinical health sciences, communication, counseling, nursing, and psychology), regardless of age and whether or not they belonged to professions considered helping professions (i.e., counseling, nursing, psychology). Although students in helping professions tended to have higher scores on the AMES than their peers, these differences were not statistically significant.
One might hypothesize that students in helping professions (especially in professions in which individuals have direct contact with clients or patients, such as counseling) would have significantly higher levels of empathy. However, counseling programs may not attract individuals who possess greater levels of trait empathy, or training programs might not be as effective in training their students as previously thought. Although microskills are taught in counselor preparation programs (e.g., reflection of content, reflection of feeling), microskill training might not overlap with material that is taught as part of an empathy training or enhance such training. Thus, microskill training might not be any more impactful for CITs’ development of empathy and sympathy than material included in training programs of other academic disciplines (e.g., athletic training, nursing).
Another potential reason for the lack of recorded differences between CITs and their non-counseling peers could be that counseling students are inherently anxious, skill-focused, self-focused, or have limited self-other awareness (Stoltenberg, 1981; Stoltenberg & McNeill, 2010). We wonder if CITs might not be focused on utilizing relationship-building approaches as much as they are on doing work that promotes introspection and reflection. Another inquiry for consideration is whether CITs potentially possess a greater understanding of empathy as a construct that inadvertently leads CITs to rate themselves lower in empathy than their non-counseling peers. Further, it is possible that CITs potentially minimize their own levels of empathy in an effort to demonstrate modesty, a phenomenon related to altruism and understood as the modesty bias (McGuire, 2003). Future research would be helpful to better understand various mitigating factors. Nevertheless, we suggest that counseling programs might be able to do more to foster empathy-facilitating experiences in counselors by being more proactive and effective in promoting empathy development in CITs. Through a review of the literature, we found support that empathy training is possible, and we wonder if there is a missed opportunity to effectively train counselors if counselor education programs do not intentionally facilitate empathy development in their CITs.
Counselor training programs are not charged to develop empathy in CITs; however, given the importance of empathy in the formation and maintenance of a therapeutic relationship, we propose that counseling training programs consider ways in which empathy is or is not being developed in their specific program. As such, we urge counselor educators to consider strategies to emphasize empathy development in their CITs. For example, reviewing developmental aspects of empathy in children, adolescents, and adults might fit well in a human development course, and the subject can be used to facilitate a conversation with CITs regarding their experiences of empathy development.
Similarly, because empathy consists of cognitive and affective components, CITs might benefit from work that assists them in gaining insight into areas of strengths and limitations in regard to both cognitive and affective aspects of empathy. Students who appear stronger in one area of empathy might benefit from practicing skills related to the other aspect of empathy. For example, if a student has a strong awareness of a client’s experience (i.e., cognitive empathy) but appears to have limitations in their felt sense of a client’s experience (i.e., affective empathy), a counselor educator might utilize live supervision opportunities to assist the student in recognizing present emotions or sensations in their body when working with the client or in a role play. Alternatively, to assist a student with developing a greater intellectual understanding of their client’s experience, a counselor educator might employ interpersonal process recall when reviewing their clinical work to help the student identify what their client might be experiencing as a result of their lived experience. To echo recommendations made by Bayne and Jangha (2016), we encourage counselor educators to move away from an exclusive focus on microskills for teaching empathy and to provide opportunities to teach CITs how to foster a connecting experience through creative means (e.g., improvisational skills).
Furthermore, the results from this study indicated that CITs possess higher levels of sympathy than of both cognitive and affective components of empathy. We recommend that counselor educators facilitate CITs’ understanding of the differences between empathy and sympathy and bring awareness to their use of sympathetic responses rather than empathic responses. It is our hope that CITs will possess a strong enough understanding between empathy and sympathy to be able to choose to use either response as it fits within a counseling context (Clark, 2010). We also encourage counselor educators to consider recommendations made by Bloom and Lambie (in press) to employ the AMES with CITs. The AMES could be a valuable and accessible tool to assist counselor educators in evaluating CITs’ levels of empathy and sympathy in regard to course assignments, in response to clinical situations, or as a wholesale measure of empathy development. As Bloom and Lambie encouraged, clinical training programs might benefit from using the AMES as a tool to programmatically measure CITs’ levels of empathy throughout their experience in their training program (i.e., transition points) as a way to collect programmatic data.
Limitations
Although this study produced important findings, some limitations exist. It is noted that the majority of participants from this study attended universities located within the Southeastern United States. As a result, the sample might not be representative of students nationwide. Similarly, demographic characteristics of the present study including the race, age, and gender composition of the sample limit the generalizability of the findings.
This study also is limited in that the instrument used to assess empathy and sympathy was a self-report measure. Although self-report measures have been shown to be reliable and are widely used within research, these measures might result in the under- or over-reporting of the variables of interest (Gall, Gall, & Borg, 2007). It is necessary to note that we employed the AMES, which was normed with adolescents and not undergraduate or graduate students. Although we recognize that inherent differences exist between adolescent and emerging adult populations, we believed the AMES was an effective choice to measure empathy because of Vossen and colleagues’ (2015) intentional development of the instrument to address existing weaknesses in other empathy assessment instruments. Nonetheless, it is necessary to interpret our results with caution.
Recommendations for Future Research
We recommend future researchers address some of the limitations of this study. Specifically, we recommend continuing to compare CITs’ levels of empathy with students from other academic disciplines, but to include a more diverse array of academic backgrounds. Similarly, we suggest future researchers not limit themselves to an emerging adult population, as both undergraduate and graduate populations include individuals over the age of 29. Further, researchers should aim to collect data from students across the country and to include a more demographically diverse sample in their research designs.
Additionally, it is necessary to note that limitations exist to using self-report measures (Gall et al., 2007), and measures of empathy are vulnerable to a myriad of complications (Bloom & Lambie, in press; Vossen et al., 2015). Thus, we encourage future researchers to consider using different measures of empathy that move away from a self-report format (e.g., clients’ perceptions of cognitive and affective empathy within a therapeutic relationship; Flasch et al., in press). Another area for future research is to track counseling students’ levels of empathy as they enter the counseling profession after graduation. It is possible that as they become more comfortable and competent as counselors, and as anxiety and self-focus decrease, their ability to empathize increases.
There is agreement in the counseling profession that empathy is an important characteristic for counselors to embody in order to facilitate positive client outcomes and to meet counselor competency standards (DePue & Lambie, 2014). Yet scholars have grappled with how to identify the necessary skills to foster empathy in counselor trainees and remain torn on which approaches to use. Although empathy training programs seem effective, little is known about which aspects of such programs are the effective ingredients that promote empathy-building, and we lack understanding about whether such programs are more effective than simply engaging in clinical work or having life experiences. Thus, we encourage researchers to explore if counseling programs are effective at teaching empathy to CITs and to further explore mechanisms that may or may not be valuable in empathy development.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.
References
Badenoch, B. (2008). Being a brain-wise therapist: A practical guide to interpersonal neurobiology. New York, NY:
W. W. Norton & Company, Inc.
Barrett-Lennard, G. T. (1986). The Relationship Inventory now: Issues and advances in theory, method, and use. In L. S. Greenberg & W. M. Pinsof (Eds.), The psychotherapeutic process: A research handbook (pp. 439–476). New York, NY: Guilford Press.
Batson, C. D., & Shaw, L. L. (1991). Evidence for altruism: Toward a pluralism of prosocial motives. Psychological Inquiry, 2(2), 107–122. doi:10.1207/s15327965pli0202_1
Bayne, H. B., & Jangha, A. (2016). Utilizing improvisation to teach empathy skills in counselor education. Counselor Education and Supervision, 55(4), 250–262. doi:10.1002/ceas.12052
Beder, J. (2004). Lessons about bereavement. Journal of Loss & Trauma, 9, 383–387. doi:10.1080/15325020490491014
Bell, H., Hagedorn, W. B., & Robinson, E. H. M. (2016). An exploration of supervisory and therapeutic relationships and client outcomes. Counselor Education and Supervision, 55(3), 182–197. doi:10.1002/ceas.12044
Bloom, Z. D., & Lambie, G. W. (in press). The Adolescent Measure of Empathy and Sympathy in a sample of emerging adults. Measurement and Evaluation in Counseling and Development.
Bohart, A. C., Elliott, R., Greenberg, L. S., & Watson, J. C. (2002). Empathy. In J. C. Norcross (Ed.), Psychotherapy relationships that work: Therapist contributions and responsiveness to patients (pp. 89–108). New York, NY: Oxford University Press.
Carré, A., Stefaniak, N., D’Ambrosio, F., Bensalah, L., & Besche-Richard, C. (2013). The Basic Empathy Scale in Adults (BES-A): Factor structure of a revised form. Psychological Assessment, 25, 679–691.
doi:10.1037/a0032297
Clark, A. J. (2004). Empathy: Implications of three ways of knowing in counseling. The Journal of Humanistic Counseling, Education & Development, 43, 141–151. doi:10.1002/j.2164-490X.2004.tb00014.x
Clark, A. J. (2010). Empathy and sympathy: Therapeutic distinctions in counseling. Journal of Mental Health Counseling, 32(2), 95–101. doi:10.17744/mehc.32.2.228n116thw397504
Connors, G. J., Carroll, K. M., DiClemente, C. C., Longabaugh, R., & Donovan, D. M. (1997). The therapeutic alliance and its relationship to alcoholism treatment participation and outcome. Journal of Consulting and Clinical Psychology, 65, 588–598. doi:10.1037/0022-006X.65.4.588
Council for Accreditation of Counseling and Related Educational Programs. (2016). 2016 Standards. Alexandria,
VA: Author.
Davis, M. H. (1980). A multidimensional approach to individual differences in empathy. JSAS Catalog of Selected Documents in Psychology, 10, 85.
Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. Journal of Personality and Social Psychology, 44, 113–126. doi:10.1037/0022-3514.44.1.113
Decety, J., & Ickes, W. (Eds.). (2009). The social neuroscience of empathy. Cambridge, MA: MIT Press.
DePue, M. K., & Lambie, G. W. (2014). Impact of a university-based practicum experience on counseling students’ levels of empathy and assessed counseling competences. Counseling Outcome Research and Evaluation, 5(2), 89–101. doi:10.1177/2150137814548509
Dillman, D. A., Smyth, J. D., & Christian, L. M. (2009). Internet, mail, and mixed-mode surveys: The tailored design method (3rd ed.). Hoboken, NJ: Wiley.
Eisenberg, N., Eggum, N. D., & Di Giunta, L. (2010). Empathy-related responding: Associations with prosocial behavior, aggression, and intergroup relations. Social Issues and Policy Review, 4, 143–180.
doi:10.1111/j.1751-2409.2010.01020.x
Elliott, R., Bohart, A. C., Watson, J. C., & Greenberg, L. S. (2011). Empathy. Psychotherapy, 48, 43–49.
doi:10.1037/a0022187
Flasch, P. S., Limberg-Ohrt, D., Fox, J., Ohrt, J., Crunk, E., & Robinson, E. (in press). Experiences of altruistic caring by clients and their counselors in the counseling session. Counseling & Values Journal.
Gall, M. D., Gall, J. P., & Borg, W. R. (2007). Educational research: An introduction (8th ed.). Boston, MA: Allyn & Bacon.
Goleman, D. (1995). Emotional intelligence: Why it can matter more than IQ for character, health and lifelong achievement. New York, NY: Bantam Books.
Hair, J. F., Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: Prentice Hall.
Ivey, A. E. (1971). Microcounseling: Innovations in interviewing training. Oxford, England: Charles C. Thomas.
Ivey, A. E., Normington, C. J., Miller, C. D., Morrill, W. H., & Haase, R. F. (1968). Microcounseling and attending behavior: An approach to prepracticum counselor training. Journal of Counseling Psychology, 15(5), 1–12.
Jolliffe, D., & Farrington, D. P. (2006). Development and validation of the Basic Empathy Scale. Journal of Adolescence, 29, 589–611. doi:10.1016/j.adolescence.205.08.010
Kirchberg, T. M., Neimeyer, R. A., & James, R. K. (1998). Beginning counselors’ death concerns and empathic responses to client situations involving death and grief. Death Studies, 22(2), 99–120.
Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York, NY: Guilford Press.
Konrath, S. H., O’Brien, E. H., & Hsing, C. (2011). Changes in dispositional empathy in American college
students over time: A meta-analysis. Personality and Social Psychology Review, 15, 180–198. doi:10.1177/1088868310377395
Krupnick, J. L., Sotsky, S. M., Simmens, S., Moyer, J., Elkin, I., Watkins, J., & Pilkonis, P. A. (1996). The role of a therapeutic alliance in psychotherapy and pharmacotherapy outcome: Findings in the National Institute of Mental Health Treatment of Depression Collaborative Research Program. Journal of Consulting and Clinical Psychology, 64, 532–539.
Lam, T. C. M., Kolomitro, K., & Alamparambil, F. C. (2011). Empathy training: Methods, evaluation practices, and validity. Journal of Multidisciplinary Evaluation, 7(16), 162–200.
Lambert, M. J., & Barley, D. E. (2001). Research summary on the therapeutic relationship and psychotherapy outcome. Psychotherapy: Theory, Research, Practice, Training, 38, 357–361. doi:10.1037/0033-3204.38.4.357
Lambert, M. J., & Bergin, A. E. (1994). The effectiveness of psychotherapy. In A. E. Bergin & S. L. Garfield (Eds.), Handbook of psychotherapy and behavior change (4th ed.; pp. 143–189). Oxford, England: John Wiley & Sons.
McGuire, A. M. (2003). “It was nothing”: Extending evolutionary models of altruism by two social cognitive biases in judgment of the costs and benefits of helping. Social Cognition, 21, 363–394.
doi:10.1521/soco.21.5.363.28685
McWhirter, B. T., Besett-Alesch, T. M., Horibata, J., & Gat, I. (2002). Loneliness in high risk adolescents: The role of coping, self-esteem, and empathy. Journal of Youth Studies, 5, 69–84. doi:10.1080/13676260120111779
Norcross, J. C. (Ed.). (2011). Psychotherapy relationships that work: Evidence-based responsiveness (2nd ed.). New York, NY: Oxford University Press.
Norcross, J. C., & Lambert, M. J. (2011). Psychotherapy relationships that work II. Psychotherapy: Theory, Research, Practice, Training, 48, 4–8.
Osborne, J. W. (2013). Best practices in data cleaning: A complete guide to everything you need to do before and after collecting your data. Thousand Oaks, CA: Sage.
Qualtrics. (2013). Qualtrics software (Version 37,892) [Computer software]. Provo, UT: Qualtrics Research Suite.
Ridley, C. R., Kelly, S. M., & Mollen, D. (2011). Microskills training: Evolution, reexamination, and call for reform. The Counseling Psychologist, 39, 800–824. doi:10.1177/0011000010378438
Rogers, C. R. (1957). The necessary and sufficient conditions of therapeutic personality change. Journal of Consulting Psychology, 21, 95–103. doi:10.1037/h0045357
Sachse, R., & Elliott, R. (2002). Process–outcome research on humanistic therapy variables. In D. J. Cain & J. Seeman (Eds.), Humanistic psychotherapies: Handbook of research and practice (pp. 83–115). Washington, DC: American Psychological Association.
Siegel, D. J. (2010). Mindsight: The new science of personal transformation. New York: Bantam.
Silva, N. W. (2001). Effect of empathy training on masters-level counseling students. (Unpublished doctoral dissertation). University of Florida, Gainesville, FL.
Spreng, R. N., McKinnon, M. C., Mar, R. A., & Levine, B. (2009). The Toronto Empathy Questionnaire: Scale development and initial validation of a factor-analytic solution to multiple empathy measures. Journal of Personality Assessment, 91, 62–71. doi:10.1080/00223890802484381
Stoltenberg, C. (1981). Approaching supervision from a developmental perspective: The counselor complexity model. Journal of Counseling Psychology, 28, 59–65. doi:10.1037/0022-0167.28.1.59
Stoltenberg, C. D., & McNeill, B. W. (2010). IDM supervision: An integrative developmental model for supervising counselors & therapists (3rd ed.). New York, NY: Routledge.
Szalavitz, M., & Perry, B. D. (2010). Born for love: Why empathy is essential—and endangered. New York, NY: Harper Collins.
Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed). Upper Saddle River, NJ: Pearson.
Teding van Berkhout, E., & Malouff, J. M. (2016). The efficacy of empathy training: A meta-analysis of randomized controlled trials. Journal of Counseling Psychology, 63, 32–41. doi:10.1037/cou0000093
Truax, C. B., & Carkhuff, R. R. (1967). Toward effective counseling and psychotherapy: Training and practice. Chicago, IL: Aldine Publishing.
Truax, C. B., & Lister, J. L. (1971). Effects of short-term training upon accurate empathy and non-possessive warmth. Counselor Education and Supervision, 10(2), 120–125. doi:10.1002/j.1556-6978.1971.tb01430.x
Vossen, H. G. M., Piotrowski, J. T., & Valkenburg, P. M. (2015). Development of the Adolescent Measure of Empathy and Sympathy (AMES). Personality and Individual Differences, 74, 66–71.
doi:10.1016/j.paid.2014.09.040
Watson, J. C., Steckley, P. L., & McMullen, E. J. (2014). The role of empathy in promoting change. Psychotherapy Research, 24, 286–298. doi:10.1080/10503307.2013.802823
Zachary D. Bloom is an assistant professor at Northeastern Illinois University. Victoria A. McNeil is a doctoral candidate at the University of Florida. Paulina Flasch is an assistant professor at Texas State University. Faith Sanders is a mental health counselor at Neuropeace Wellness Counseling in Orlando, Florida. Correspondence can be addressed to Zachary Bloom, 5500 North St. Louis Avenue, Chicago, IL 60625, z-bloom@neiu.edu.
Jun 28, 2018 | Volume 8 - Issue 2
William H. Snow, Margaret R. Lamar, J. Scott Hinkle, Megan Speciale
The Council for Accreditation of Counseling & Related Educational Programs (CACREP) database of institutions revealed that as of March 2018 there were 36 CACREP-accredited institutions offering 64 online degree programs. As the number of online programs with CACREP accreditation continues to grow, there is an expanding body of research supporting best practices in digital remote instruction that refutes the ongoing perception that online or remote instruction is inherently inferior to residential programming. The purpose of this article is to explore the current literature, outline the features of current online programs and report the survey results of 31 online counselor educators describing their distance education experience to include the challenges they face and the methods they use to ensure student success.
Keywords: online, distance education, remote instruction, counselor education, CACREP
Counselor education programs are being increasingly offered via distance education, or what is commonly referred to as distance learning or online education. Growth in online counselor education has followed a similar trend to that in higher education in general (Allen & Seaman, 2016). Adult learners prefer varied methods of obtaining education, which is especially important in counselor education among students who work full-time, have families, and prefer the flexibility of distance learning (Renfro-Michel, O’Halloran, & Delaney, 2010). Students choose online counselor education programs for many reasons, including geographic isolation, student immobility, time-intensive work commitments, childcare responsibilities, and physical limitations (The College Atlas, 2017). Others may choose online learning simply because it fits their learning style (Renfro-Michel, O’Halloran, & Delaney, 2010). Additionally, education and training for underserved and marginalized populations may benefit from the flexibility and accessibility of online counselor education.
The Council for Accreditation of Counseling & Related Educational Programs (CACREP; 2015) accredits online programs and has determined that these programs meet the same standards as residential programs. Consequently, counselor education needs a greater awareness of how online programs deliver instruction and actually meet CACREP standards. Specifically, existing online programs will benefit from the experience of other online programs by learning how to exceed and surpass minimum accreditation expectations by utilizing the newest technologies and pedagogical approaches (Furlonger & Gencic, 2014). The current study provides information regarding the current state of online counselor education in the United States by exploring faculty’s descriptions of their online programs, including their current technologies, student and program community building approaches, and challenges faced.
Distance Education Defined
Despite its common usage throughout higher education, the U.S. Department of Education (DOE) does not use the terms distance learning, online learning, or online education; rather, it has adopted the term distance education (DOE, 2012). However, in practice, the terms distance education, distance learning, online learning, and online education are used interchangeably. The DOE has defined distance education as the use of one or more technologies that deliver instruction to students who are separated from the instructor and that supports “regular and substantive interaction between the students and the instructor, either synchronously or asynchronously” (2012, p. 5). The DOE has specified that technologies may include the internet, one-way and two-way transmissions through open broadcast and other communications devices, audioconferencing, videocassettes, DVDs, and CD-ROMs. Programs are considered distance education programs if at least 50% or more of their instruction is via distance learning technologies. Additionally, residential programs may contain distance education elements and still characterize themselves as residential if less than 50% of their instruction is via distance education. Traditional on-ground universities are incorporating online components at increasing rates; in fact, 67% of students in public universities took at least one distance education course in 2014, further reflecting the growth in this teaching modality (Allen & Seaman, 2016).
Enrollment in online education continues to grow, with nearly 6 million students in the United States engaged in distance education courses (Allen & Seaman, 2016). Approximately 2.8 million students are taking online classes exclusively. In a conservative estimate, over 25% of students enrolled in CACREP programs are considered distance learning students. In a March 2018 review of the CACREP database of accredited institutions, there were 36 accredited institutions offering 64 degree programs. Although accurate numbers are not available from any official sources, it is a conservative estimate that over 12,000 students are enrolled in a CACREP-accredited online program. When comparing this estimate to the latest published 2016 CACREP enrollment figure of 45,820 (CACREP, 2017), online students now constitute over 25% of the total. This does not include many other residential counselor education students in hybrid programs who may take one or more classes through distance learning means.
At the time of this writing, an additional three institutions were currently listed as under CACREP review, and soon their students will likely be added to this growing online enrollment. As this trend continues, it is essential for counselor education programs to understand issues, trends, and best practices in online education in order to make informed choices regarding counselor education and training, as well as preparing graduates for employment. It also is important for hiring managers in mental health agencies to understand the nature and quality of the training graduates of these programs have received.
One important factor contributing to the increasing trends in online learning is the accessibility it can bring to diverse populations throughout the world (Sells, Tan, Brogan, Dahlen, & Stupart, 2012). For instance, populations without access to traditional residential, brick-and-mortar classroom experiences can benefit from the greater flexibility and ease of attendance that distance learning has to offer (Bennet-Levy, Cromarty, Hawkins, & Mills, 2012). Remote areas in the United States, including rural and frontier regions, often lack physical access to counselor education programs, which limits the numbers of service providers to remote and traditionally underserved areas of the country. Additionally, the online counselor education environment makes it possible for commuters to take some of their course work remotely, especially in winter when travel can become a safety issue, and in urban areas where travel is lengthy and stressful because of traffic.
The Online Counselor Education Environment
The Association for Counselor Education and Supervision (ACES) Technology Interest Network (2017) recently published guidelines for distance education within counselor education that offer useful suggestions to online counselor education programs or to those programs looking to establish online courses. Current research supports that successful distance education programs include active and engaged faculty–student collaboration, frequent communications, sound pedagogical frameworks, and interactive and technically uncomplicated support and resources (Benshoff & Gibbons, 2011; Murdock & Williams, 2011). Physical distance and the associated lack of student–faculty connection has been a concern in the development of online counselor education programs. In its infancy, videoconferencing was unreliable, unaffordable, and often a technological distraction to the learning process. The newest wave of technology—enhanced distance education—has improved interactions using email, e-learning platforms, and threaded discussion boards to make asynchronous messaging virtually instantaneous (Hall, Nielsen, Nelson, & Buchholz, 2010). Today, with the availability of affordable and reliable technical products such as GoToMeeting, Zoom, and Adobe Connect, online counselor educators are holding live, synchronous meetings with students on a regular basis. This includes individual advising, group supervision, and entire class sessions.
It is important to convey that online interactions are different than face-to-face, but they are not inferior to an in-person faculty–student learning relationship (Hickey, McAleer, & Khalili, 2015). Students and faculty prefer one method to the other, often contingent upon their personal belief in the effectiveness of the modality overall and their belief in their own personal fit for this style of teaching and learning (Watson, 2012). In the actual practice of distance education, professors and students are an email, phone call, or videoconference away; thus, communication with peers and instructors is readily accessible (Murdock & Williams, 2011; Trepal, Haberstroh, Duffey, & Evans, 2007). When communicating online, students may feel more relaxed and less inhibited, which may facilitate more self-disclosure, reflexivity, and rapport via increased dialogue (Cummings, Foels, & Chaffin, 2013; Watson, 2012). Subsequently, faculty who are well-organized, technologically proficient, and more responsive to students’ requests may prefer online teaching opportunities and find their online student connections more engaging and satisfying (Meyer, 2015). Upon Institutional Research Board approval, an exploratory survey of online counselor educators was conducted in 2016 and 2017 to better understand the current state of distance counselor education in the United States.
Method
Participants
Recruitment of participants was conducted via the ACES Listserv (CESNET). No financial incentive or other reward was offered for participation. The 31 participants comprised a sample of convenience, a common first step in preliminary research efforts (Kerlinger & Lee, 1999). Participants of the study categorized themselves as full-time faculty members (55.6%), part-time faculty members (11.1%), academic chairs and department heads (22.2%), academic administrators (3.7%), and serving in other roles (7.4%).
Study Design and Procedure
The survey was written and administered using Qualtrics, a commercial web-based product. The survey contained questions aimed at exploring online counselor education programs, including current technologies utilized, approaches to reducing social distance, development of community among students, major challenges in conducting online counselor education, and current practices in meeting these challenges. The survey was composed of one demographic question, 15 multiple-response questions, and two open-ended survey questions. The demographic question asked about the respondent’s role in the university. The 15 multiple-response questions included items such as: (a) How does online counselor education fit into your department’s educational mission? (b) Do you provide a residential program in which to compare your students? (c) How successful are your online graduates in gaining postgraduate clinical placements and licensure? (d) What is the average size of an online class with one instructor? and (e) How do online students engage with faculty and staff at your university? Two open-ended questions were asked: “What are the top 3 to 5 best practices you believe are most important for the successful online education of counselors?” and “What are the top 3 to 5 lessons learned from your engagement in the online education of counselors?”
Additional questions focused on type of department and its organization, graduates’ acceptance to doctoral programs, amount of time required on the physical campus, e-learning platforms and technologies, online challenges, and best practices for online education and lessons learned. The 18 survey questions were designed for completion in no more than 20 minutes and the survey was active for 10 months, during which time there were three appeals for responses yielding 31 respondents.
Procedure
An initial recruiting email and three follow-ups were sent via CESNET. Potential participants were invited to visit a web page that first led to an introductory paragraph and informed consent page. An embedded skip logic system required consent before allowing access to the actual survey questions.
The results were exported from the Qualtrics web-based survey product, and the analysis of the 15 fixed-response questions produced descriptive statistics. Cross tabulations and chi square statistics further compared the perceptions of faculty and those identifying themselves as departmental chairs and administrators.
The two open-ended questions—“What are the top 3 to 5 best practices you believe are most important for the successful online education of counselors?” and “What are the top 3 to 5 lessons learned from your engagement in the online education of counselors?”—yielded 78 statements about lessons learned and 80 statements about best practices for a total of 158 statements. The analysis of the 158 narrative comments initially consisted of individually analyzing each response by identifying and extracting the common words and phrases. It is noted that many responses contained more than one suggestion or comment. Some responses were a paragraph in length and thus more than one key word or phrase could come from a single narrative response. This first step yielded a master list of 18 common words and phrases. The second step was to again review each comment, compare it to this master list, and place a check mark for each category. The third step was to look for similarities in the 18 common words and group them into a smaller number of meaningful categories. These steps were checked among the researchers for fidelity of reporting and trustworthiness.
Results
Thirty-one distance learning counselor education faculty, department chairs, and administrators responded to the survey. They reported their maximum class sizes ranged from 10 to 40 with a mean of 20.6 (SD = 6.5), and the average class size was 15.5 (SD = 3.7). When asked how online students are organized within their university, 26% reported that students choose classes on an individual basis, 38% said students are individually assigned classes using an organized schedule, and 32% indicated that students take assigned classes together as a cohort.
Additionally, respondents were asked how online students engage with faculty and staff at their university. Email was the most popular, used by all (100%), and second was phone calls (94%). Synchronous live group discussions using videoconferencing technologies were used by 87%, while individual video calls were reported by 77%. Asynchronous electronic discussion boards were utilized by 87% of the counselor education programs.
Ninety percent of respondents indicated that remote or distance counseling students were required to attend the residential campus at least once during their program, with 13% requiring students to come to campus only once, 52% requiring students to attend twice, and 26% requiring students to come to a physical campus location four or more times during their program.
All participants indicated using some form of online learning platform with Blackboard (65%), Canvas (23%), Pearson E-College (6%), and Moodle (3%) among the ones most often listed. Respondents indicated the satisfaction levels of their current online learning platform as: very dissatisfied (6.5%), dissatisfied (3.2%), somewhat dissatisfied (6.5%), neutral (9.7%), somewhat satisfied (16.1%), satisfied (41.9%), and very satisfied (9.7%). There was no significant relationship between the platform used and the level of satisfaction or dissatisfaction (X2 (18,30) = 11.036, p > .05), with all platforms faring equally well. Ninety-seven percent of respondents indicated using videoconferencing for teaching and individual advising using such programs as Adobe Connect (45%), Zoom (26%), or GoToMeeting (11%), while 19% reported using an assortment of other related technologies.
Participants were asked about their university’s greatest challenges in providing quality online counselor education. They were given five pre-defined options and a sixth option of “other” with a text box for further elaboration, and were allowed to choose more than one category. Responses included making online students feel a sense of connection to the university (62%), changing faculty teaching styles from traditional classroom models to those better suited for online coursework (52%), providing experiential clinical training to online students (48%), supporting quality practicum and internship experiences for online students residing at a distance from the physical campus (38%), convincing faculty that quality outcomes are possible with online programs (31%), and other (10%).
Each participant was asked what their institution did to ensure students could succeed in online counselor education. They were given three pre-defined options and a fourth option of “other” with a text box for further elaboration, and were allowed to choose more than one option. The responses included specific screening through the admissions process (58%), technology and learning platform support for online students (48%), and assessment for online learning aptitude (26%). Twenty-three percent chose the category of other and mentioned small classes, individual meetings with students, providing student feedback, offering tutorials, and ensuring accessibility to faculty and institutional resources.
Two open-ended questions were asked and narrative comments were analyzed, sorted, and grouped into categories. The first open-ended question was: “What are the top 3 to 5 best practices that are the most important for the successful online education of counselors?” This yielded 78 narrative comments that fit into the categories of fostering student engagement (n = 19), building community and facilitating dialogue (n = 14), supporting clinical training and supervision (n = 11), ensuring courses are well planned and organized (n = 10), providing timely and robust feedback (n = 6), ensuring excellent student screening and advising (n = 6), investing in technology (n = 6), ensuring expectations are clear and set at a high standard (n = 5), investing in top-quality learning materials (n = 4), believing that online counselor education works (n = 3), and other miscellaneous comments (n = 4). Some narrative responses contained more than one suggestion or comment that fit multiple categories.
The second open-ended question—“What are the top 3 to 5 lessons learned from the online education of counselors?”—yielded 80 narrative comments that fit into the categories of fostering student engagement (n = 11), ensuring excellent student screening and advising (n = 11), recognizing that online learning has its own unique workload challenges for students and faculty (n = 11), providing timely and robust feedback (n = 8), building community and facilitating dialogue (n = 7), ensuring courses are well planned and organized (n = 7), investing in technology (n = 6), believing that online counselor education works (n = 6), ensuring expectations are clear and set at a high standard (n = 5), investing in top-quality learning materials (n = 3), supporting clinical training and supervision (n = 2), and other miscellaneous comments (n = 8).
Each participant was asked how online counselor education fit into their department’s educational mission and was given three categorical choices. Nineteen percent stated it was a minor focus of their department’s educational mission, 48% stated it was a major focus, and 32% stated it was the primary focus of their department’s educational mission.
The 55% of participants indicating they had both residential and online programs were asked to respond to three follow-up multiple-choice questions gauging the success rates of their online graduates (versus residential graduates) in attaining: (1) postgraduate clinical placements, (2) postgraduate clinical licensure, and (3) acceptance into doctoral programs. Ninety-three percent stated that online graduates were as successful as residential students in gaining postgraduate clinical placements. Ninety-three percent stated online graduates were equally successful in obtaining state licensure. Eighty-five percent stated online graduates were equally successful in getting acceptance into doctoral programs.
There were some small differences in perception that were further analyzed. Upon using a chi square analysis, there were no statistically significant differences in the positive perceptions of online graduates in gaining postgraduate clinical placements (X2 (2, 13) = .709, p > .05), the positive perceptions regarding the relative success of online versus residential graduates in gaining postgraduate clinical licensure (X2 (2, 13) = .701, p > .05), or perceptions of the relative success of online graduates in becoming accepted in doctoral programs (X2 (2, 12) = 1.33, p > .05).
Discussion
The respondents reported that their distance learning courses had a mean class size of 15.5. Students in these classes likely benefit from the small class sizes and the relatively low faculty–student ratio. These numbers are lower than many residential classes that can average 25 students or more. It is not clear what the optimal online class size should be, but there is evidence that the challenge of larger classes may introduce burdens difficult for some students to overcome (Chapman & Ludlow, 2010). Beattie and Thiele (2016) found first-generation students in larger classes were less likely to talk to their professor or teaching assistants about class-related ideas. In addition, Black and Latinx students in larger classes were less likely to talk with their professors about their careers and futures (Beattie & Thiele, 2016).
Programs appeared to have no consistent approach to organizing students and scheduling courses. The three dominant models present different balances of flexibility and predictability with advantages and disadvantages for both. Some counselor education programs provide students the utmost flexibility in selecting classes, others assign classes using a more controlled schedule, and others are more rigid and assign students to all classes.
The model for organizing students impacts the social connections students make with one another. In concept, models that provide students with more opportunities to engage each other in a consistent and effective pattern of positive interactions result in students more comfortable working with one another, and requesting and receiving constructive feedback from their peers and instructors.
Cohort models, in which students take all courses together over the life of a degree program, are the least flexible but most predictable and have the greatest potential for fostering strong connections. When effectively implemented, cohort models can foster a supportive learning environment and greater student collaboration and cohesion with higher rates of student retention and ultimately higher graduation rates (Barnett & Muse, 1993; Maher, 2005). Advising loads can decrease as cohort students support one another as informal peer mentors. However, cohorts are not without their disadvantages and can develop problematic interpersonal dynamics, splinter into sub-groups, and lead to students assuming negative roles (Hubbell & Hubbell, 2010; Pemberton & Akkary, 2010). An alternative model in which students make their own schedules and choose their own classes provides greater flexibility but fewer opportunities to build social cohesion with others in their program. At the same time, these students may not demonstrate the negative dynamics regarding interpersonal engagement that can occur with close cohort groups.
Faculty–Student Engagement
Remote students want to stay in touch with their faculty advisors, course instructors, and fellow students. Numerous social engagement opportunities exist through technological tools including email, cell phone texts, phone calls, and videoconference advising. These fast and efficient tools provide the same benefits of in-person meetings without the lag time and commute requirements. Faculty and staff obviously need to make this a priority to use these tools and respond to online students in a timely manner.
All technological tools referred to in the survey responses provide excellent connectivity and communication if used appropriately. Students want timely responses, but for a busy faculty or staff member it is easy to allow emails and voicemails to go unattended. Emails not responded to and unanswered voicemail messages can create anxiety for students whose only interaction is through electronic means. This also might reinforce a sense of isolation for students who are just “hanging out there” on their own and having to be resourceful to get their needs met. It is recommended that the term timely needs to be defined and communicated so faculty and students understand response expectations. It is less important that responses are expected in 24, 48, or even 72 hours; what students need to know is when to expect a response.
Survey responses indicated that remote counselor education students are dependent upon technology, including the internet and associated web-based e-learning platforms. When the internet is down, passwords do not work, or computers fail, the remote student’s learning is stalled. Counselor education programs offering online programming must provide administrative services, technology, and learning support for online students in order to quickly remediate technology issues when they occur. It is imperative that standard practice for institutions include the provision of robust technology support to reduce down-time and ensure continuity of operations and connection for remote students.
Fostering Program and Institutional Connections
Faculty were asked how often online students were required to come to a physical campus location as part of their program. Programs often refer to short-term campus visits as limited residencies to clarify that students will need to come to the campus. Limited residencies are standard, with 90% responding that students were required to come to campus at least once. Short-term intensive residencies are excellent opportunities for online students to make connections with their faculty and fellow students (Kops, 2014). Residential intensives also provide opportunities for the university student life office, alumni department, business office, financial aid office, registrar, and other university personnel to connect with students and link a human face to an email address.
Distance learning students want to engage with their university, as well as fellow students and faculty. They want to feel a sense of connection in a similar manner as residential students (Murdock & Williams, 2011). Institutions should think creatively about opportunities to include online learners in activities beyond the classroom. An example of promoting inclusiveness is when one university moved the traditional weekday residential town halls to a Sunday evening teleconference webinar. This allowed for greater access, boosted attendance, and served to make online counselor education students feel like a part of the larger institution.
As brick-and-mortar institutions consider how to better engage distance learning students, they need to understand that a majority of students (53%) taking exclusively distance education courses reside in the same state as the university they are attending (Allen & Seaman, 2016). Given that most are within driving distance of the physical campus, students are more open to coming to campus for special events, feel their presence is valued, and know that they are not just part of an electronic platform (Murdock & Williams, 2011).
E-Learning Platforms as Critical Online Infrastructure
All participants (100%) reported using an online learning platform. E-learning platforms are standard for sharing syllabi, course organization, schedules, announcements, assignments, discussion boards, homework submissions, tests, and grades. They are foundational in supporting faculty instruction and student success with numerous quality options available. Overall, online faculty were pleased with their technological platforms and there was no clear best platform.
Online learning platforms are rich in technological features. For example, threaded discussions allow for rich, thoughtful dialogue among students and faculty, and they are often valued by less verbally competitive students who might express reluctance to speak up in class but are willing to share their comments in writing. Course examinations and quizzes in a variety of formats can be produced and delivered online through e-learning platforms such as Blackboard, Canvas, and Moodle. Faculty have flexibility for when exams are offered and how much time students have to complete them. When used in conjunction with proctoring services such as Respondus, ProctorU, and B-Virtual, integrity in the examination process can be assured. Once students complete their exam, software can automatically score and grade objective questions, and provide immediate feedback to students.
Videoconferencing and Virtual Remote Classrooms
Videoconferencing for teaching and individual advising through Adobe Connect, Zoom, GoToMeeting, and related technologies is now standard practice and changing the nature of remote learning. Distance learning can now employ virtual classroom models with synchronous audio and video communication that closely parallels what occurs in a residential classroom. Videoconferencing platforms provide tools to share PowerPoints, graphics, and videos as might occur in a residential class. Class participants can write on virtual whiteboards with color markers, annotating almost anything on their screen. Group and private chat functionality can provide faculty with real-time feedback during a class session. Newer videoconferencing features now allow faculty to break students into smaller, private discussion groups and move around to each group virtually, just like what often occurs in a residential classroom. With preparation, faculty can execute integrated survey polls during a video class session. Essentially, videoconferencing tools reduce the distance in distance education.
Videoconference platforms allow faculty to teach clinical skills in nearly the same manner as in residential programs. Counselor education faculty can model skills such as active listening in real time to their online class. Faculty can then have students individually demonstrate those skills while being observed. Embedded features allow faculty to record the video and audio features of any conversation for playback and analysis. Videoconference platforms now offer “breakout” rooms to place students in sub-groups for skills practice and debriefing, similar to working in small groups in residential classrooms. Faculty members and teaching assistants can visit each breakout room to ensure students are on task and properly demonstrating counseling skills. Just as in a residential class, students can reconvene and share the challenges and lessons learned from their small group experience.
Challenges in Providing Remote Counselor Education
Participants were asked to select one or more of their top challenges in providing quality online counselor education. In order of frequency, they reported the greatest challenges as making online students feel a sense of connection to the university (62%), changing faculty teaching styles from brick-and-mortar classroom models to those better suited for online coursework (52%), providing experiential clinical training to online students (48%), supporting quality practicum and internship experiences for online students residing at a distance from the physical campus (38%), and convincing faculty members that quality outcomes are possible with online programs (31%).
Creating a sense of university connection. Counselor education faculty did not report having major concerns with faculty–student engagement. Faculty seemed confident with student learning outcomes using e-learning platforms and videoconferencing tools that serve to reduce social distance between faculty and students and facilitate quality learning experiences. This confidence could be the result of counselor educators’ focus on fostering relationships as a foundational counseling skill (Kaplan, Tarvydas, & Gladding, 2014).
However, faculty felt challenged to foster a student’s sense of connection with the larger university. For example, remote students not receiving emails and announcements about opportunities available only to residential students can feel left out. Remote students might find it difficult to navigate the university student life office, business department, financial aid office, registration system, and other university systems initially designed for residential students. Highly dependent on their smartphone and computer, remote students can feel neglected as they anxiously wait for responses to email and voicemail inquiries (Milman, Posey, Pintz, Wright, & Zhou, 2015).
In the online environment, there are extracurricular options for participating in town halls, special webinars, and open discussion forums with departmental and university leaders. Ninety percent of the programs require students to come to their physical campus one or more times. These short-term residencies are opportunities for students to meet the faculty, departmental chairs, and university leaders face-to-face and further build a sense of connection.
A majority of online students (53%) reside in the same state as the university they are attending (Allen & Seaman, 2016), with many within commuting distance of their brick-and- mortar campus. These students will appreciate hearing about the same opportunities afforded to residential students, and under the right circumstances and scheduling they will participate.
Changing faculty teaching styles. Not all residential teaching styles and methods, such as authority-based lecture formats, work well with all students (Donche, Maeyer, Coertjens, Van Daal, & Van Petegem, 2013). Distance learning students present their own challenges and preferences. Successful distance education programs require active and engaged faculty who frequently communicate with their students, use sound pedagogical frameworks, and maintain a collaborative and interactive style (Benshoff & Gibbons, 2011; Murdock & Williams, 2011). Discovery orientation, discussion, debriefing, action research, and flipped classrooms where content is delivered outside the classroom and the classroom is used to discuss the material are good examples of more collaborative styles (Brewer & Movahedazarhouligh, 2018; Donche et al., 2013).
Organization is critical for all students, but more so for remote students who often are working adults with busy schedules. They want to integrate their coursework into other life commitments and want a clear, well-organized, and thoughtfully planned course with all the requirements published in advance, including specific assignment due dates. Distance counselor education faculty will find their syllabi growing longer with more detail as they work to integrate traditional assignments with the e-learning and videoconferencing tools in order to create engaging, predictable, and enjoyable interactive learning experiences.
Providing experiential clinical training. Counselor educators ideally provide multimodal learning opportunities for counseling students to understand, internalize, and demonstrate clinical skills for a diverse clientele. In residential classrooms, the knowledge component is usually imparted through textbooks, supplemental readings, course assignments, video demonstration, and instructor-led lecture and discussions. All remote programs provide similar opportunities for students and replicate residential teaching models with their use of asynchronous e-learning platforms and synchronous videoconferencing technologies.
Asynchronous methods are not well suited for modeling, teaching, and assessing interpersonal skills. However, synchronous videoconferencing technologies provide the same opportunity as residential settings to conduct “fishbowl” class exercises, break students into groups to practice clinical skills, conduct role plays, apply procedural learning, and give students immediate, meaningful feedback about their skills development.
The majority of surveyed programs required remote students to come to campus at least once to assess students for clinical potential, impart critical skills, and monitor student progress in achieving prerequisite clinical competencies required to start practicum. Courses that teach and assess clinical interviewing skills are well suited for these intensive experiences and provide an important gatekeeping function. Faculty not only have the opportunity to see and hear students engage in role plays, but also to see them interact with other students.
Supporting quality practicum and internship experiences. Remote counselor educators report that their programs are challenged in supporting quality practicum and internship experiences. Residential students benefit from the relationships universities develop over time with local public and nonprofit mental health agencies in which practicum and internship students may cluster at one or more sites. Although online students living close enough to the residential campus may benefit from the same opportunities, remote students living at a distance typically do not experience this benefit. They often have to seek out, interview, and compete for a clinical position at a site unfamiliar to their academic program’s field placement coordinator. Thus, online counselor education students will need field placement coordination that can help with unique practicum and internship requirements. The placement coordinator will need to know how to review and approve distance sites without a physical assessment. Relationships with placement sites will need to rely upon email, phone, and teleconference meetings. Furthermore, online students can live in a state other than where the university is located, requiring the field placement coordinator to be aware of various state laws and regulations.
Convincing faculty that quality outcomes are possible. Approximately one-third of the surveyed counselor education faculty reported the need to convince other faculty that quality outcomes are possible with remote counselor education. Changing the minds of skeptical colleagues is challenging but naturally subject to improvement over time as online learning increases, matures, and becomes integrated into the fabric of counselor education. In the interim, programs would be wise to invest in assisting faculty skeptics to understand that online counselor education can be managed effectively (Sibley & Whitaker, 2015). First, rather than just telling faculty that online counselor education works, programs should demonstrate high levels of interactivity that are comparable to face-to-face engagement by using state-of-the-art videoconferencing platforms. Second, it is worth sharing positive research outcomes related to remote education. Third, it is best to start small by encouraging residential faculty to first try a hybrid course by holding only one or two of their total class sessions online. Fourth, it is important to provide robust support for reluctant but willing faculty who agree to integrate at least one or two online sessions into their residential coursework. Finally, institutions will find more willing faculty if they offer incentives for those who give online counselor education a chance.
Ensuring Online Student Success
Student success is defined by the DOE as related to student retention, graduation rates, time to completion, academic success, and gainful employment (Bailey et al., 2011). Counselor education programs would likely add clinical success in practicum and internship and post-master’s licensure to these critical success outcomes.
The survey respondents reported that student success begins with making sure that the students they accept have the aptitude to learn via online distance education. Students may have unrealistic perceptions that remote distance education is somehow less academically strenuous. Programs need to ensure students are prepared for the unique aspects of online versus residential learning. Fifty-eight percent of the programs engaged in student screening beginning with the admissions process. A quarter of the respondents used a formal assessment tool to assess students for success factors such as motivation, learning style, study habits, access to technology, and technological skills. A commonly used instrument was the Online Readiness Assessment developed by Williams (2017).
Lessons Learned and Best Practices
The 158 statements regarding best practices and lessons learned were further refined to yield the top six imperatives for success in online counselor education, namely: (1) fostering student–faculty–community engagement (57.4%); (2) providing high expectations, excellent screening, advising, and feedback (36%); (3) investing in quality instructional materials, course development, and technology support (30.5%); (4) providing excellent support for online clinical training and supervision (14.6%); (5) recognizing the workload requirements and time constraints of online students; (6) working to instill the belief in others that quality outcomes are possible with online counselor education programs (10.1%); and (7) other assorted responses (13.5%).
An indicator of success for many counselor education programs is the rate at which students graduate, obtain clinical placement, and become licensed. There is also an interest in how successful graduates are in becoming admitted into doctoral programs. For online programs, a further benchmark test is to compare online student graduation, licensure, and doctoral admissions rates to those in residential programs. Fifty-five percent of the respondents served in programs with residential as well as online students. These respondents were able to compare their online student outcomes to residential student outcomes. Their perception was that online graduates were as successful as residential students in gaining postgraduate clinical placements (93%), obtaining state licensure (93%), and acceptance into doctoral programs (85%). They generally believed online graduates were competitive with residential graduates.
Limitations, Recommendations, and Conclusion
Limitations of the Study
When this study began in 2016, there were 11 CACREP-accredited institutions offering online counselor education programs, and by March 2018, there were 36. This study represents a single snapshot of the online counselor education experience during a time of tremendous growth.
This study focused on the reported experience of faculty, departmental chairs, and administrators who have some commitment and investment in online learning. Some would point out the bias of those who advocate for remote counselor education in relaying their own experiences, anecdotal evidence, and personal comparisons of online and residential teaching.
The exploratory nature of this study was clearly not comprehensive in its inclusion of all the factors associated with online counselor education. Specific details of online counselor education programs were not emphasized and could have offered more information about university and departmental resources for remote education, faculty training for online educational formats, and student evaluations of online courses. The numerous technologies used were identified, but this says nothing about their differential effectiveness. Future studies should include these variables as well as other factors that will provide further information about the successes and challenges of online counselor education.
This survey assessed the informed opinions of counselor education faculty and administrators who responded that they were generally satisfied with the various aspects of their programs, including student outcomes. What was not assessed was the actual quality of the education itself. In order to change the mind of skeptics, more than opinions and testimonies will be needed. Future studies need to objectively compare learning outcomes, demonstrate quality, and delineate how remote counselor education programs are meeting the challenges of training counselors within distance learning modalities.
Recommendations
The dynamic nature of the field of online counselor education requires ongoing study. As more programs offer courses and full programs through distance learning modalities, they can contribute their own unique expertise and lessons learned to inform and enrich the broader field.
The challenge of faculty skepticism and possible mixed motives regarding online learning will continue to be problematic. There is a lingering perception by some faculty that online counselor education programs are not equivalent to residential training. An inherent faculty bias might exist in which residential means higher quality and online means lower quality. Some faculty may teach online courses only for additional compensation while privately having reservations. In contrast, departmental chairs and academic administrators might want the same high levels of quality, but may find themselves more driven by the responsibility for meeting enrollment numbers and budgets. In times of scarcity, these individuals may see online counselor education as the answer for new revenue sources (Jones, 2015). For others, online education may present concerns while providing an appeal for its innovative qualities or providing social justice through increasing access to higher education by underserved populations. The best way to clarify the issues and better inform the minds of skeptics is to present them with objective data regarding the nature and positive contributions of remote counselor education learning outcomes.
Aside from the modality of their instructional platform, it is important to understand if effective remote counselor educators are different from equally effective residential course instructors. Remote teaching effectiveness might be associated with some combination of attributes, interests, and motivations, and thus self-selection to teach remote students. Further studies will need to tease out what works, what does not work, and what type of faculty and faculty training make someone best suited for participation in remote counselor education.
Technology is critical to the advances in remote counselor education. Email, smartphones, texting, and e-learning platforms have helped faculty create engaging courses with extensive faculty–student interactions. Videoconferencing in particular has served to reduce the social distance between faculty and remote students. As aforementioned, innovative programs are taking the distance out of distance counselor education, where the virtual remote classroom modality provides similar experiences to those of residential classes. The nature of these technologically facilitated online relationships deserves further study to determine which technologies and related protocols enhance learning and which impede it.
A logical next step is to build on the work that has been accomplished and conduct more head-to-head comparisons of student outcomes among remote and residential programs. This is very feasible, as 34 of the 36 institutions currently offering online counselor education programs also have a residential program with which to make comparisons. These within-institution comparisons will be inherently quasi-experimental. Effective program comparisons of delivery models will require systematically implemented reliable and valid measures of student learning outcomes at strategic points in the counselor training program. The Counselor Competency Scale (Lambie, Mullen, Swank, & Blount, 2018) is a commonly used standardized assessment for graduate students engaged in clinical practicum and internship. The National Counseling Exam scores of current students and recent graduates can provide standardized measures to compare outcomes of graduates across programs.
Finally, although we can learn from institutional best practices and student success stories, we also could benefit from understanding why some programs, faculty, and students struggle. Challenges are certainly faced in remote counselor education and training, but it is likely that one or more programs have developed innovative concepts to surmount these obstacles. The 31 respondents were able to articulate many best practices to manage challenges and believed they were achieving the same learning objectives achieved by residential counseling students. Many faculty members, departmental chairs, and administrators believed that remote counselor education graduates are as successful as those attending residential programs, but this opinion is not universally shared. What is clear is that despite some reservations, a growing number of counselors are trained via a remote modality. It is time to embrace distance counselor education; learn from best practices, successes, and struggles; and continue to improve outcomes for the benefit of programs, the profession of counseling, and the consumers of the services our graduates provide.
Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest or funding contributions for the development of this manuscript.
References
Allen, I. E., & Seaman, J. (2016). Online report card: Tracking online education in the United States. Babson Survey Research Group. Retrieved from https://onlinelearningsurvey.com/reports/onlinereportcard.pdf
Association for Counselor Education and Supervision Technology Interest Network. (2017). ACES guidelines for online learning in counselor education. Retrieved from https://www.acesonline.net/sites/default/files/Online%20Learning%20CES%20Guidelines%20May%202017%20(1).pdf
Bailey, M., Benitiz, M., Burton, W., Carey, K., Cunningham, A., Fraire, J., . . . Wheelan, B. (2011). Committee on measures of student success: A report to Secretary of Education Arne Duncan. U.S. Department of Education. Retrieved from https://www2.ed.gov/about/bdscomm/list/cmss-committee-report-final.pdf
Barnett, B. G., & Muse, I. D. (1993). Cohort groups in educational administration: Promises and challenges. Journal of School Leadership, 3, 400–415.
Beattie, I. R., & Thiele, M. (2016). Connecting in class? College class size and inequality in academic social capital. The Journal of Higher Education, 87, 332–362.
Bennett-Levy, J., Hawkins, R., Perry, H., Cromarty, P., & Mills, J. (2012). Online cognitive behavioural therapy training for therapists: Outcomes, acceptability, and impact of support: Online CBT training. Australian Psychologist, 47(3), 174–182. doi:10.1111/j.1742-9544.2012.00089.x
Benshoff, J. M., & Gibbons, M. M. (2011). Bringing life to e-learning: Incorporating a synchronous approach to online teaching in counselor education. The Professional Counselor, 1, 21–28. doi:10.15241/jmb.1.1.21
Brewer, R., & Movahedazarhouligh, S. (2018). Successful stories and conflicts: A literature review on the effectiveness of flipped learning in higher education. Journal of Computer Assisted Learning, 1–8. doi:10.1111/jcal.12250
Chapman, L., & Ludlow, L. (2010). Can downsizing college class sizes augment student outcomes? An investigation of the effects of class size on student learning. Journal of General Education, 59(2), 105–123. doi:10.5325/jgeneeduc.59.2.0105
The College Atlas. (2017). 41 facts about online students. Retrieved from https://www.collegeatlas.org/41-surprising-facts-about-online-students.html
Council for Accreditation of Counseling & Related Educational Programs. (2015). 2016 CACREP standards. Washington, DC: Author.
Council for Accreditation of Counseling & Related Educational Programs. (2017). Annual report 2016. Washington, DC: Author.
Cummings, S. M., Foels, L., & Chaffin, K. M. (2013). Comparative analysis of distance education and classroom-based formats for a clinical social work practice course. Social Work Education, 32, 68–80.
doi:10.1080/02615479.2011.648179
Donche, V., De Maeyer, S., Coertjens, L., Van Daal, T., & Van Petegem, P. (2013). Differential use of learning strategies in first-year higher education: The impact of personality, academic motivation, and teaching strategies. British Journal of Educational Psychology, 83, 238–251. doi:10.1111/bjep.12016
Furlonger, B., & Gencic, E. (2014). Comparing satisfaction, life-stress, coping and academic performance of counselling students in on-campus and distance education learning environments. Australian Journal of Guidance and Counselling, 24, 76–89. doi:10.1017/jgc.2014.2
Hall, B. S., Nielsen, R. C., Nelson, J. R., & Buchholz, C. E. (2010). A humanistic framework for distance education. The Journal of Humanistic Counseling, 49, 45–57. doi:10.1002/j.2161-1939.2010.tb00086.x
Hickey, C., McAleer, S. J., & Khalili, D. (2015). E-learning and traditional approaches in psychotherapy education: Comparison. Archives of Psychiatry and Psychotherapy, 4, 48–52.
Hubbell, L., & Hubbell, K. (2010). When a college class becomes a mob: Coping with student cohorts. College Student Journal, 44, 340–353.
Jones, C. (2015). Openness, technologies, business models and austerity. Learning, Media and Technology, 40, 328–349. doi:10.1080/17439884.2015.1051307
Kaplan, D. M., Tarvydas, V. M., & Gladding, S. T. (2014). 20/20: A vision for the future of counseling: The new consensus definition of counseling. Journal of Counseling & Development, 92, 366–372.
doi:10.1002/j.1556-6676.2014.00164.x
Kerlinger, F. N., & Lee, H. B. (1999). Foundations of behavioral research (4th ed). Fort Worth, TX: Wadsworth.
Kops, W. J. (2014). Teaching compressed-format courses: Teacher-based best practices. Canadian Journal of University Continuing Education, 40, 1–18.
Lambie, G. W., Mullen, P. R., Swank, J. M., & Blount, A. (2018). The Counseling Competencies Scale: Validation and refinement. Measurement and Evaluation in Counseling and Development, 51, 1–15.
doi:10.1080/07481756.2017.1358964
Maher, M. A. (2005). The evolving meaning and influence of cohort membership. Innovative Higher Education, 30(3), 195–211.
Meyer, J. M. (2015). Counseling self-efficacy: On-campus and distance education students. Rehabilitation Counseling Bulletin, 58(3), 165–172. doi:10.1177/0034355214537385
Milman, N. B., Posey, L., Pintz, C., Wright, K., & Zhou, P. (2015). Online master’s students’ perceptions of institutional supports and resources: Initial survey results. Online Learning, 19(4), 45–66.
Murdock, J. L., & Williams, A. M. (2011). Creating an online learning community: Is it possible? Innovative Higher Education, 36, 305–315. doi:10.1007/s10755-011-9188-6
Pemberton, C. L. A., & Akkary, R. K. (2010). A cohort, is a cohort, is a cohort . . . Or is it? Journal of Research on Leadership Education, 5(5), 179–208.
Renfro-Michel, E. L., O’Halloran, K. C., & Delaney, M. E. (2010). Using technology to enhance adult learning in the counselor education classroom. Adultspan Journal, 9, 14–25. doi:10.1002/j.2161-0029.2010.tb00068.x
Sells, J., Tan, A., Brogan, J., Dahlen, U., & Stupart, Y. (2012). Preparing international counselor educators through online distance learning. International Journal for the Advancement of Counselling, 34, 39–54. doi:10.1007/s10447-011-9126-4
Sibley, K., & Whitaker, R. (2015, March 16). Engaging faculty in online education. Educause Review. Retrieved from https://er.educause.edu/articles/2015/3/engaging-faculty-in-online-education
Trepal, H., Haberstroh, S., Duffey, T., & Evans, M. (2007). Considerations and strategies for teaching online counseling skills: Establishing relationships in cyberspace. Counselor Education and Supervision, 46(4), 266–279. doi:10.1002/j.1556-6978.2007.tb00031.x
U.S. Department of Education Office of Postsecondary Education Accreditation Division. (2012). Guidelines for Preparing/Reviewing Petitions and Compliance Reports. Retrieved from https://www.asccc.org/sites/default/files/USDE%20_agency-guidelines.pdf
Watson, J. C. (2012). Online learning and the development of counseling self-efficacy beliefs. The Professional Counselor, 2, 143–151. doi:10.15241/jcw.2.2.143
Williams, V. (2017). Online readiness assessment. Penn State University. Retrieved from https://pennstate.qualtrics.com/jfe/form/SV_7QCNUPsyH9f012B
William H. Snow is an associate professor at Palo Alto University. Margaret R. Lamar is an assistant professor at Palo Alto University. J. Scott Hinkle, NCC, is Director of Professional Development at the National Board for Certified Counselors. Megan Speciale, NCC, is an assistant professor at Palo Alto University. Correspondence can be addressed to William Snow, 1791 Arastradero Road, Palo Alto, CA 94304, wsnow@paloaltou.edu.
