A Q Methodology Study of Supervisee Roles Within a Counseling Practicum Course

Eric R. Baltrinic, Ryan M. Cook, Heather J. Fye

Counseling students often experience clinical supervision for the first time during their participation in practicum courses. Counseling practicum supervisees new to supervision rely on their supervisors to provide direction and structure in supervision experiences to help them grow professionally and personally. Yet little is known about how students view their roles as new supervisees. Supervisors can benefit from structuring and delivering their courses informed by new supervisees’ perspectives on their roles. Accordingly, the authors conducted a Q methodology study with a purposeful sample of seven counseling practicum students, a doctoral co-instructor, and a counseling practicum instructor engaged in a first-semester counseling practicum course. Principal components analysis with varimax rotation of Q-sort data revealed three factors depicting supervisee roles (i.e., Dutiful, Discerning, and Expressive Learners). Implications for applying findings to improve supervision instruction and student learning are discussed, including limitations and future research suggestions.

Keywords: counseling practicum supervisees, supervisee roles, Q methodology, counseling practicum instructors, student learning


Supervision is generally understood as a relational and evaluative process between a senior and junior member of a profession, which is intended to foster the junior member’s learning and professional skill development while also ensuring the welfare of clients they serve (Bernard & Goodyear, 2019). Supervision is also a key pedagogical and curricular feature of counseling training programs (Council for Accreditation of Counseling and Related Educational Programs [CACREP], 2015) within which students develop into entry-level counselors. Although supervision is often considered a hierarchal relationship, supervisees are active participants in the supervision process (Stark, 2017). Thus, as part of counselor training, it is important for counseling students to understand what supervision is and what is expected of them (Bernard & Goodyear, 2019). Counseling students’ learning about the supervision process and supervisee roles commonly begins during their participation in field experience courses, the first of which is the counseling practicum course (CACREP, 2015). However, little is known about how counseling practicum supervisees come to understand their roles (Pearson, 2004) and, consequently, how counseling students use their understanding of roles to contribute to the learning process in supervision (Borders, 2019; Stark, 2017). This lack of understanding is compounded by a preponderance of supervision research grounded in expert perspectives and less so from the perspectives of counseling students new to supervision (Stark, 2017).

Thus, there are clear advantages to investigating counseling practicum supervisees’ understanding of their supervisee roles, particularly while they are engaged in their first field experience (i.e., practicum) course. First, practicum experiences offer supervisees applied learning environments (CACREP, 2015) where they can apply prior learning under supervision to their work with actual clients (Moate et al., 2017). To that end, this is the first time that these novice supervisees are ethically responsible for their clients’ care, which includes adequately conveying their professional needs to their supervisors (Bernard & Goodyear, 2019). Second, practicum supervisees may become anxious if they are unsure of their roles and what is expected of them by their supervisors and want to feel competent regardless of their actual competency levels (Ellis et al., 2015). Third and finally, the focus and process of supervision changes over time as supervisees develop (Stoltenberg & McNeill, 2010), including changes to how they function in their expected roles (Bernard & Goodyear, 2019). These early learning experiences are important for supervisees because they shape their understanding of clinical supervision (Borders, 2019), which they will engage in throughout their field placement experiences and post-degree, pre-licensure clinical training (Cook & Sackett, 2018). Therefore, it is important to understand supervisees’ initial understanding of their roles within the counseling practicum environment, including the degree to which these views align with or diverge from their supervisors’ (Bernard & Goodyear, 2019).

Student Learning and the Counseling Practicum Classroom
For supervision to be a valuable learning experience, it is assumed that supervisees will be able to adequately self-identify and articulate their client concerns as well as their own developmental needs to supervisors (Cook & Sackett, 2018). However, because practicum supervisees have no prior supervision experience, the way in which they come to understand their roles as supervisees is largely informed by the framework created by the instructor within a practicum course. To that end, practicum course instructors may align their course structure and requirements with accreditation standards (e.g., CACREP, 2015) and professional best practices (e.g., Association for Counselor Education and Supervision Best Practices in Clinical Supervision; Borders et al., 2014) in order to ensure that supervisees are informed of their responsibilities. This information is often conveyed to supervisees via an informed consent or supervision contract (Borders et al., 2014) as well as a course syllabus (CACREP, 2015). However, some supervisees may not fully understand the purpose of supervision nor grasp their roles as supervisees, even though they reviewed an informed consent with their supervisors (Cook et al., 2019).

Counseling practicum courses present students with new opportunities to apply learning from content courses (Moate et al., 2017), refine reflective practice (Neufeldt, 2007), and work with actual clients under supervision (Bernard & Goodyear, 2019). During this unique and critical learning time, supervisees are closely monitored by supervisors whose expectations and responsibilities are rooted in both supervisors’ and supervisees’ roles (Bernard & Goodyear, 2019; CACREP, 2015). Practicum course instructors are charged with facilitating supervisees’ learning to develop as professional counselors while safeguarding the welfare of the clients they serve (Borders et al., 2014). Borders (2019) delineated seven process-of-learning principles for use by training supervisors in the supervision classroom. This model is rooted in learning theories, with a particular focus on understanding how supervisors help supervisees in training based on the process of how students learn. We contend that implementation of practicum instruction guided by learning principles could help instructors to scaffold learning processes and teach counseling practicum supervisees about their supervisee roles, which is needed to help them navigate early career challenges (Loganbill et al., 1982).

Ultimately, if supervisees are to be effective with clients, more examination of their understanding of roles and related learning is needed. This information will provide instructors with the necessary knowledge to build effective learning environments and scaffold supervisees’ learning experiences in the supervision classroom (Borders, 2019; Moate et al., 2017). Thus, by examining how supervisees understand their supervisee roles, instructors can better teach them how to eventually self-direct their supervision experiences (Stoltenberg & McNeill, 2010) and effectively utilize supervision (Norem et al., 2006; Pearson, 2004), with the goal of transferring learning from supervision to counseling encounters with clients.

Counseling Practicum Supervisee Roles
Novice supervisees (i.e., practicum supervisees) desire to quickly acquire skills so that they can best serve their clients by utilizing the “correct” counseling technique or approach (Stoltenberg & McNeill, 2010). Further, supervisees experience a high degree of anxiety and confusion as they begin to develop their own counseling style and competencies (Rønnestad & Skovholt, 2003). Relatedly, Loganbill et al. (1982) suggested that novice supervisees, like counseling practicum supervisees, regularly feel “stuck” in their work with clients and confused as to how best to make progress with their clients. To that end, supervisees benefit from instructors who provide supportive feedback and explicit instructions in a highly structured supervision environment (Ellis et al., 2015; Loganbill et al., 1982; Stoltenberg & McNeill, 2010) that promotes role clarity (i.e., clearly understanding what is expected and how to meet those expectations).

Failure to determine whether there is alignment between supervisees’ and instructors’ perspectives on roles may yield unintended but potentially detrimental consequences (Stark, 2017). For example, from an educational perspective, instructors can best attend to their students’ learning needs when they understand what it is that their students perceive as being important to their learning (Moate et al., 2017). Furthermore, asking supervisees to engage in evaluations of their performance based on poorly understood roles (Ladany & Friedlander, 1995) could undermine the purposes of clinical supervision (e.g., professional development, client welfare; Borders et al., 2014) and threaten their right to a fair evaluation as students and supervisees (American Counseling Association [ACA], 2014; CACREP, 2015). Providing supervisees with clear information on their roles can assist with reducing nondisclosure (Cook et al. 2019) and lowering anxiety about their performance (Ellis et al., 2015). These practices allow for safeguarding supervisees and clients, fair supervision evaluation practices (Stark, 2017), and assuring quality supervision instruction grounded in student and instructor perspectives and adult learning processes (Borders, 2019).

Much of the current supervision literature contains guidelines for instructors to effectively conduct supervision (Stark, 2017). For example, Best Practices in Clinical Supervision (Borders et al., 2014) offers specific recommendations for those providing clinical supervision (i.e., supervisors). The expectations of supervisees are implied in the guiding document (e.g., arrive on time to supervision, engage in the supervision process), but the specific roles and responsibilities for supervisees are not explicitly addressed. Whereas others (e.g., Homrich et al., 2014) have conceptualized standards relevant to supervisees’ roles in clinical supervision, including self-reflection and self-exploration, communicating information truthfully and accurately, and engaging actively in opportunities for personal and professional development. The importance of supervisees’ contributions have also been noted by scholars (e.g., Norem et al., 2006; Stark, 2017; Wilcoxon et al., 2005). For instance, several authors identified supervisee characteristics that are helpful to the learning process in supervision, such as being self-directed, motivated, mature, autonomous, proactive, and open to new learning experiences, all of which are perceived as helping supervisees successfully navigate supervision (Norem et al., 2006; Stark, 2017; Wilcoxon et al., 2005). In an earlier effort to clarify roles and expectations for the supervision process, Munson (2002) identified several supervisee rights, including (a) meeting consistently and regularly with a supervisor, (b) engaging in growth-oriented supervision that considers one’s personal privacy, (c) participating in theoretically grounded supervision, (d) receiving clear evaluation criteria and evaluations informed by direct observation, and (e) having a supervisor who is adequately trained. Additionally, Munson suggested that supervisees ought to be able to speak freely in supervision, need encouragement to integrate prior learning from other counseling classes (which supports Borders, 2019), and should remain open and curious about the learning process. Overall, the author’s work supports the need for providing supervision based on expectations for both supervisor and supervisee performance. Despite these documented guidelines and expectations, there is a notable lack of input from supervisees’ perspectives of their roles and related expectations. This is concerning because instructors need to structure their learning environments grounded in evidence supporting student engagement (Malott et al., 2014), which is strengthened by identifying students’ prior learning experiences (Borders, 2019).

The Current Study
Learning to be a supervisee is a process in which counseling students gain experience starting in their practicum courses. It is critical for the supervisor (i.e., instructor) to understand their supervisees’ perceptions of their roles in supervision, which have been informed by accreditation requirements (e.g., CACREP, 2015), professional standards (e.g., Best Practices in Clinical Supervision, Borders, 2014), and scholarly literature (e.g., Munson, 2002). Yet, supervisors lack access to information from student perspectives for increasing supervisee engagement and meaningfulness of roles, particularly from the counseling practicum course context where students often experience supervision for the first time. In the current study, we sought to understand the expected roles and responsibilities of new supervisees from the perspectives of supervisees within a counseling practicum course. We also included perspectives from the instructional team (i.e., a doctoral student co-instructor, and a counseling practicum instructor) to illustrate the degree of alignment between instructors and students and to illustrate any nuances between instructor and co-instructor views. Using this research, supervisors and counselor educators may be able to offer developmentally appropriate solutions to address supervisee concerns and to provide support to counseling practicum instructors based on both expert and novice perspectives. Accordingly, our study was guided by the following research question: What are counseling practicum supervisees’ views of their roles and responsibilities in the practicum classroom environment?


Q methodology is a unique research method containing the depth of qualitative data reduction and the objective rigor of by-person factor analysis (Brown, 1996), which can be used effectively in the classroom setting to facilitate students’ subject matter understanding (Watts & Stenner, 2012). Specifically, students’ self-perspectives can be revealed in relation to their peers’ and instructors’ views using Q methodology (Good, 2003). Q methodology has also been used successfully to investigate phenomena in the counselor education classroom (Baltrinic & Suddeath, 2020) and program settings (Baltrinic et al., 2013) that favor both student and instructor views. Accordingly, we selected Q methodology for this study to obtain perspectives from a participant sample of counseling practicum supervisees and their instructional team.

Concourse and Q Sample
Specific steps were taken to develop a rigorous Q sample, which is the set of statements used to assist participants with expressing their views on supervisee roles via the Q-sorting process (Brown, 1980). The first step was selecting a concourse, which is a collection of opinion statements about any topic (Stephenson, 1978). Many routes of communication contribute to the form and content of a concourse (Brown, 1980). The concourse for this study was composed of statements we took from select supervision literature and documents (i.e., Borders et al., 2014; Homrich et al., 2014; Kangos et al., 2018; Munson, 2002; Stark, 2017). We searched within these sources and selected concourse statements specifically containing supervision experts’ views on supervisees’ roles. We needed 100% consensus on each statement for it to be included in the concourse. The concourse selection process resulted in over 240 concourse statements, which was too many for the final Q sample (Paige & Morin, 2016).

Second, we proceeded with selecting, evaluating, and reducing the final Q sample items in line with Brown (1980) and Paige and Morin (2016). Initially, we had our first and second authors, Baltrinic and Cook, eliminate all duplicate, unclear, fragmented, or unrelated statements from the 240 concourse statements, which resulted in 160 statements. Baltrinic and Cook then used a structured sample design (Brown, 1980) to reduce the 160 concourse statements to a representative 48-item Q sample (Brown, 1980; see Appendix). Representativeness of a Q sample refers to whether the subset of items represent the broader population of statements in the concourse. Third, the 48-item Q sample was then evaluated by three experts (two supervision experts and one Q methodology expert) using a content validity index (Paige & Morin, 2016). The expert reviewers rated each of the 48 items on a 4-point scale using three criterion items: 1) Is the statement clear and unambiguous for counselor educators? 2) Is the statement clear and unambiguous for counseling practicum students? and 3) Is the statement distinct from the other statements? Scores across expert reviewers’ item ratings were averaged with only scores of 3 (mostly) or 4 (completely) indicating consensus on the content validity index. Items receiving a score of 3 or 4 were included, items receiving a score of 2 (somewhat) were reviewed and modified by our research team for appropriateness, and items receiving a score of 1 (not at all) were discarded from the sample. Accordingly, 45 items received scores of 3 or 4. Baltrinic completed additional Q sample refinements for the remaining three items that received scores of 2 (n = 2) and 1 (n = 1); two items were rewritten to improve clarity, one duplicate item was eliminated, and one new item was added. All refinements were confirmed by the second author before accepting the items in the final Q sample. For the final step, two of the experts completed Q sorts to ensure the final Q sample facilitated the expression of views on supervisee roles. The results of these two pilot Q sorts were not included in the data analysis.

Participant Sample
We followed McKeown and Thomas’s (2013) recommendations for selecting an intensive participant sample. Therefore, we purposefully selected an intensive participant sample composed of seven master’s-level clinical mental health counseling practicum supervisees, one doctoral co-instructor, and one faculty instructor; all of whom represented a purposeful sample of individuals (Patton, 2015) holding similar theoretical interests and having the ability to provide insight into the topic of investigation (Brown, 1980; McKeown & Thomas, 2013).

Three of the master’s-level counseling students identified as male and four identified as female, and their ages ranged from 23 to 37 years old (M = 30, SD = 10.06). Regarding race/ethnicity, five of the counseling students identified as European American and two identified as African American. The counselor educator and course instructor identified as a European American male. He holds a PhD in Counselor Education with 5 years of counseling experience and 6 years of supervision experience. Additionally, the instructor is a licensed professional counselor and an Approved Clinical Supervisor, and he publishes regularly on the topic of clinical supervision. The doctoral student co-instructor identified as a European American female who has 3 years of clinical experience as a school counselor and 1 year of supervision experience.

Data Collection
After receiving IRB approval, Baltrinic collected the initial consents, demographics, Q sorts, and post–Q sort interview data. The students and course instructors (N = 9) were asked to rank-order the 48 items under the following condition of instruction: “Select the statements with which you most agree (+4) to those with which you most disagree (-4) that represent a beginning counselor practicum student’s supervisee roles.” After completing the Q sorts, each participant was asked to provide written responses for the top three items with which they most and least agreed and were asked to comment on any other items of significance. Baltrinic obtained these post-sort questionnaires in person. The purpose of gathering post-sort data is to provide qualitative context for the factor interpretations (Brown, 1996).

Data Analysis
Nine Q sorts were completed by the instructional team and the counseling practicum students under a single condition of instruction, all of which were entered into the PQMethod software program V. 2.35 (Schmolck, 2014). A 3-factor solution was selected using the principle components method with varimax rotation, which yields the highest number of significant factor loadings and because Baltrinic, who analyzed the data, was blinded from participants’ identifying information (Watts & Stenner, 2012). Being blinded to participant information renders approaches such as theoretical rotation moot in favor of varimax rotation, given the lack of contextual information related to factor exemplars (i.e., those participants with the highest factor loading on a factor; McKeown & Thomas, 2013).


Data analysis revealed three significantly different viewpoints (i.e., Factors 1, 2, and 3) on supervisee roles. For Q methodology, factor loadings are not used for factor interpretation. Instead, the individual significant factor loadings associated with each of the factors are weighted and averaged, resulting in an ideal Q sort representing each factor, which are presented chronologically in a factor array. Factor arrays contain the scores that are used for factor interpretation (see Appendix). Parenthetical reference to specific Q-sample items and their associated factor scores located in the factor array (e.g., Item 23, +2) will be provided within the factor interpretations below. Select participant quotes from post-sort questionnaires are incorporated into the factor interpretations.

Factor 1: The Dutiful Learner
Factor 1, which we have named the Dutiful Learner, represents a conceptualization of supervisee roles as predominantly adhering to the ethical codes, guidelines, and models of ethical behavior (Item 15, +4). One of seven supervisees, the course co-instructor, and the course instructor were significantly associated with Factor 1 (i.e., had factor loadings of .50 or higher; Brown, 1996) with factor loadings of .70, .82, and .70, respectively. Supervisee roles attributed to the Dutiful Learner are understood as aspects of the learning process provided that student learning adheres to the code of ethics. Additionally, supervisee roles were viewed in terms of supervisees following the procedures and policies of their graduate programs (Item 36, +4), which as one participant noted “are really non-negotiable.” Supervisee roles, including the demonstration of healthy professional boundaries in supervision sessions and with clients, were also highly preferred by participants aligning with this factor (Item 25, +4). When reflecting on Item 25, the supervisee participant emphasized, “Healthy boundaries are paramount for legally and emotionally protecting oneself.” Finally, the Dutiful Learner viewpoint entails emphasis on the importance of supervisees arriving on time for supervision (Item 7, +3), including the need to be prepared for every supervision session (e.g., individual, triadic, group; Item 18, +2).

Participants ascribing to the Dutiful Learner view of supervisee roles were less concerned about the demonstration of awareness of strengths and weaknesses to instructors (Item 1, 0), which according to one participant would “occur as part of the process over time.” Dutiful Learners are viewed as favoring ethically guided supervisee roles versus simply being pleasant to work with in supervision (Item 30, -4) or gratuitously asking questions regarding counseling-related issues (Item 32, -3). Dutiful Learner viewpoints may be related to having a sense of responsibility for other supervisees’ learning that includes a desire for students to develop a strong ethical compass, which is needed “throughout their development as counselors.” For example, according to the co-instructor, who noted in her post-sort interview questionnaire, “It seems items I ranked highest were ‘rules’ and ‘guidelines,’ which I feel is influenced by the need to be an ethical practitioner and influenced by being in the co-teacher role.” Overall, supervisees, according to the course instructor, are reminded to “trust the process” in their beginning roles, given it is most critical that they have a “willingness” to learn.

Factor 2: The Discerning Learner
Factor 2 characterized supervisees as having a penchant for seeking feedback, a spirit of willingness, and thoughtful reasoning; therefore, we have named this factor the Discerning Learner. For Factor 2, three of the seven supervisees had significant factor loadings (.67, .83, and .58, respectively). In general, the Discerning Learner represents a conceptualization of supervisee roles in which supervisees feel their supervisors provide them with feedback about counseling skills (Item 40, +4), which according to one participant is the “purpose of supervision.” The supervisees whose viewpoints aligned with this factor valued supervisee roles that included asking for help when needed (Item 35, +4), which is related to recognizing and regularly seeking feedback from their supervisors (Item 20, +2). Throughout the supervision process, Discerning Learners are viewed as valuing organization and exercising good judgement when approaching supervision situations (Item 43, +4). Overall, a willingness to work with their supervisors (Item 33, +3) was deemed important given the interpersonal nature of the supervision process.

Further, the Discerning Learner view favored the acquisition of counseling skills as central to supervisee roles. With a focus on skill acquisition, the need to manage ambiguity and uncertainty as a function of their roles was considered less important for Discerning Learners (Item 14, -4). As one participant noted, “The whole point of supervision is to take what the supervisor is telling us and apply it to our practice.” Additionally, for participants whose views aligned to this factor, recognizing and managing anxiety (Item 12, -4) was not considered central to supervisee roles in practicum because anxiety is commonly accepted as “part of the learning process in supervision.” One participant normalized the presence of anxiety and the need to “discuss it in supervision,” further suggesting, “It is good to express anxiety about the supervision process instead of bottling it in.” Overall, supervisees who view supervisee roles from the viewpoint of the Discerning Learner accept anxiety and ambiguity as those things that “should be expected” when using good judgement to acquire and refine counseling skills and initiate discussions about the process in supervision.

Factor 3: The Expressive Learner
Factor 3 favored the personal and interpersonal expression of needs in the interest of learning; therefore, we have named this factor the Expressive Learner. Three of seven supervisees had significant factor loadings on Factor 3 (.73, .50, and .63, respectively). Supervisees whose views aligned with the Expressive Learner factor favored supervisee roles emphasizing opportunities to be vulnerable in sessions with their supervisor (Item 34, +4). This factor entailed supervisee acknowledgment of the emotional context for learning and growth; as suggested by one supervisee, “If I don’t feel vulnerable, then I’m not going to have an experience where I truly learn.” Another non–traditional age male supervisee elaborated, “Older students often bring work experience and personal experience to the supervisee role,” which according to another participant (also a non-traditional male student) means that “If a supervisee is unable to be open and honest (despite previous experiences), then no progress is made towards professional growth.” Additionally, managing personal and interpersonal issues was deemed important for supervisee roles (Item 22, +4). As one supervisee noted, “Although it can be difficult to manage various life roles, it is important not to let those life roles interfere.” The Expressive Learner is further conceived as valuing the demonstration of verbal communication skills (Item 28, +3) and having the ability to take multiple perspectives (Item 21, +3), both of which were deemed essential for “welcoming and responding to supervisors’ critical feedback,” especially with challenging cases. The underlying sentiment of feeling empowered by supervisors (Item 45, +2) was deemed important because “feeling empowered will drive you to continue growing your skills.” Overall, the personal and interpersonal nature of supervision and supervisees’ roles was distinguishing for this factor.

Supervisees ascribing to the Expressive Learner factor expected that the ability to speak freely in supervision (Item 2, -3) is an assumed role of supervisees. As one participant explained, “It is important for me to say exactly what I’m feeling so my supervisor can give me their perspective and help me work through any issues.” Similarly, identifying supervisee developmental needs (Item 9, -4) is viewed as part of all supervision that should be initiated by the instructor at the beginning stage of supervision. For example, as one supervisee noted, “Because I am a student, I want my supervisor to initiate discussions” related to developmental needs “and then guide me with questions.” Finally, active participation in supervision (Item 42, -2) was viewed as less important because it is “expected,” and although supervisees should work collaboratively, “establishing tasks and goals should first be initiated by the supervisor,” a point echoed by all supervisees associated with Factor 3. It seems then that Expressive Learners are interpersonally attuned and focused and most responsive when supervisee roles are activated through initial supervisor prompts.


The purpose of the current study was to examine the roles of supervisees as perceived from the multiple viewpoints of counseling practicum supervisees, a doctoral co-instructor, and a faculty instructor. Collectively, our findings reveal three different viewpoints (i.e., factors) of supervisees’ roles and responsibilities. Interestingly, only one of the seven supervisees’ views of these roles aligned with the views of the doctoral co-instructor and practicum course instructor. Even though the instructors acculturated the supervisees to their responsibilities in relatively the same way (e.g., university supervision contract, course syllabus) and used methods that aligned with accreditation guidelines, professional standards, and best practices in supervision, the majority of students still made meaning of these roles as supervisees in ways that differed from the instructors’ viewpoint. At the same time, supervisees deemed it important to convey their own professional competencies to their evaluative supervisors (Cook et al., 2019). As we will discuss below, course instructors who hope to better attend to the learning needs of all students and understand how their students perceive their own roles in clinical supervision can integrate details from the three factors (the Dutiful Learner, the Discerning Learner, and the Expressive Learner) into their instruction practices.

Participants whose views most strongly aligned to the Dutiful Learner factor perceive the most important aspect of supervisee roles as adhering to ethical codes and course requirements. For Dutiful Learners, supervisee roles parallel the concrete expectations often outlined in a supervision contract (Ellis, 2017) or course syllabus. That is, having clear expectations of clinical supervision and an operational understanding of the structural aspects of clinical supervision were endorsed as the strongest expectations of Dutiful Learners. Additionally, participants who conceptualized supervisee roles in terms of Factor 1 believe supervisees will gain insight into their own skills and competencies over time as they develop in their roles (Loganbill et al., 1982). However, having a foundational understanding of how to utilize clinical supervision as well as their rights as supervisees in clinical supervision (Munson, 2002) may be most critical for Dutiful Learners (Stoltenberg & McNeill, 2010). Accordingly, Dutiful Learners may find the explicit instructions for supervision helpful for managing the anxieties and uncertainties that are often experienced by new supervisees (Loganbill et al., 1982). Specific aspects to focus on for Dutiful Learners’ roles would be to review ethical guidelines, course requirements, and strategies for coming prepared to supervision.

Discerning Learners (Factor 2) favor their roles as active participants in the supervision process, which they perceive as a relational process between supervisee and supervisor, and student and instructor. That is, Discerning Learners perceive a collaborative relationship between supervisee and supervisor as being central to their professional development and their counseling work with clients. This factor best reflects the supervisee working alliance (Bordin, 1983), in which creating a strong emotional bond between supervisors and supervisees and mutual agreement on goals and tasks is most important to positive outcomes in supervision (e.g., intentional nondisclosure, role ambiguity; Cook & Welfare, 2018; Ladany & Friedlander, 1995). Discerning Learners also acknowledge that anxiety is a common characteristic of being a supervisee, which is somewhat expected given the participants’ developmental level (i.e., novice supervisees; Rønnestad & Skovholt, 2003; Stoltenberg & McNeill, 2010). However, they view acknowledging this anxiety to their supervisors as helpful. Finally, Discerning Learners perceive discussing cultural identities as being relevant to their role as supervisees, although one supervisee stated culture should only be discussed with a client “when relevant to their counseling work.”

Expressive Learners (Factor 3) perceive the role of a supervisee as being vulnerable with and openly disclosing information to their supervisor, demonstrating the ability to take multiple perspectives with their clients, and feeling empowered by their supervisors. These findings align with Cook et al. (2018), who investigated supervisees’ perceptions of power dynamics in clinical supervision. Further, the Expressive Learner factor represents views most aligned with tenets of feminist supervision (e.g., Porter, 1995; Porter & Vasquez, 1997). Porter (1995) noted that supervisors empower their supervisees by creating a safe environment and valuing their supervisees’ perspectives with the goal of facilitating their supervisees’ autonomy, although there is substantial evidence that counseling students, such as practicum supervisees, withhold information from their supervisors (e.g., Cook & Welfare, 2018; Cook et al., 2019). Expressive Learners view learning as a self-directed process within supervision, which also suggests they perceive themselves as active contributors to clinical supervision (Stark, 2017). At the same time, Expressive Learners also look to their supervisors to initiate discussion about their developmental needs and to provide insights into their opportunities for professional growth. This viewpoint aligns with that of Stoltenberg and McNeill (2010), who contend that supervisors can help novice supervisees to gain awareness into their own developmental needs through questioning and supportive feedback.

Implications for Practicum Instructors
Practicum course instructors often have the responsibility to teach supervisees about their roles and responsibilities as they align with accreditation standards (i.e., CACREP, 2015), professional standards (i.e., ACES Best Practices in Clinical Supervision; Borders et al., 2014), and ethical guidelines (i.e., ACA, 2014). To that end, practicum instructors must convey their expectations for students in their classroom and attend to the diverse learning needs of all their students. Our findings suggest supervisees understand their roles and responsibilities in three different ways, which at times differ from those of the course instructors. Instructors must be able to provide sufficient, appropriate, and meaningful feedback to all supervisees in their class (Borders, 2019) to ensure they are adequately able to successfully navigate supervision in the classroom and in future supervision experiences. Thus, we offer practicum instruction strategies based on the three supervisees’ viewpoints of their roles (i.e., factors). For example, instructors can assess supervisees’ understanding of their prior experiences with evaluative relationships (i.e., educational, personal, professional; Borders, 2019) and how those experiences might be similar or different to their current experience in the counseling practicum course.

Our findings also connect with evidence-based processes for how students learn. As you may recall from the literature review, Borders (2019) delineated seven principles rooted in learning theories, with a particular focus on understanding how to help supervisees based on the process of how students learn. These seven principles are connected to our findings and noted in parentheses (e.g., Principle 1) within the text that follows. Specifically, instructors can use characteristics of the three factors, along with the seven learning principles, to inform counseling practicum instruction and doctoral supervision strategies. For example, instructors can help Dutiful Learners identify ethical dilemmas (e.g., risk assessment, mandated reporting, healthy boundaries between client and counselor) and ways to discuss solutions with their supervisors by watching segments of counseling sessions (Principle 1). Instructors can then ask supervisees to use ethical decision-making models to connect practice to theory (Principle 2), and they can help supervisees to identify needed skills, including situations in which these skills are most needed (Principle 4 and 7). Instructors can observe supervisees’ skills practice and direct doctoral co-teachers to identify ways for the supervisees to improve practice and convey ethical dilemmas to supervisors (e.g., site supervisor, course instructor). As supervisees understand their roles, they can pursue role-playing ethical dilemmas and learn how to receive and respond to feedback after each role-play within a low-risk classroom setting (Principle 3). Overall, supervisees and doctoral co-teachers should receive scaffolded instructor feedback to help them better correct any errors (Principle 5).

Discerning Learners prefer presenting counseling work to their supervisors and discussing related feedback about their counseling skills, which can be done based on a mutual understanding and appreciation of supervisees’ roles. Thus, instructors should consider reviewing with supervisees the counseling skills learned in previous classes (Principle 1; Borders, 2019), including assessing supervisees’ comfort level with using specific counseling skills. To that end, instructors can ask supervisees to identify and name specific skills in their counseling work as well as their peers’ counseling work during role-plays or actual counseling sessions (Principle 5). Additionally, because Discerning Learners value discussing their anxiety and issues of culture with their supervisors, instructors can include a question about supervisees’ anxiety in case presentation forms, which could then be used as a starting point to facilitate any individual or group discussions. Identifying and addressing anxiety (Bernard & Goodyear, 2019) is important because supervisees need to know how to broach difficult topics with clients (Day-Vines et al., 2020), and instructors need to model that broaching for doctoral co-teachers and supervisees (Principle 6).

Of the factors identified in the current study, the Expressive Learners prefer a self-directed role when engaging in their supervision experience. Expressive Learners prefer a learning environment in which disclosure is encouraged, vulnerability is validated, and empowerment is facilitated. Accordingly, instructors need to assess Expressive Learners’ motivation level, which is a critical driver for learning new content (Principle 3; Borders, 2019) and for understanding supervisees’ capacities to self-direct their learning experiences (Principle 7). Instructors can assist Expressive Learners with developing learning goals that can include strategies for both collaboration and self-direction (Principle 7). Additionally, instructors may use specific supervision techniques, such as interpersonal process recall (Kagan, 1980), to gain insight into supervisees’ perceptions of their skills and to encourage their disclosure-related skill acquisition (Principle 4). This is important because Expressive Learners are willing to discuss their concerns when prompted by supervisors. Finally, instructors may also consider using the Power Dynamics in Supervision Scale (Cook et al., 2018) to assess supervisees’ perspectives of being vulnerable or empowered.

Limitations and Future Research
Researchers who use Q methodology gather and analyze data to reveal common viewpoints among participants, and in this case within a single counseling practicum course. As such, the Q factors in this study do not generalize (Brown, 1980) similarly to the findings in widescale quantitative studies. We caution readers against interpreting factors as being “better or worse” or “right or wrong” for other practicum courses. However, similar factors may plausibly exist among supervisees’ views in other counselor education practicum courses. In this way, any similarities from our findings to other sites is seen more as a matter of shared experiences rather than generalized findings (Stephenson, 1978). The low number of participants in the current study may be viewed as a limitation. However, similar to Baltrinic and Suddeath (2020), the instructors and student participants in the current study represented a purposeful sample of sole interest (Brown, 1980), revealing robust factors within a counselor education classroom (i.e., the unit of analysis). Nevertheless, future research could include larger numbers of participants across multiple practicum courses, which may increase the potential for revealing the existence of additional factors. Researchers are encouraged to test propositions by having supervisees complete Q-sorts with the current Q sample within and across other counseling subspeciality areas as well. Researchers can also use qualitative or case study methods to investigate supervisees’ views from practicum through the completion of internship.

In conclusion, practicum course instructors can incorporate the current findings into their supervision pedagogy. Using student-generated factors can help practicum course instructors guide supervisees to (a) develop skills grounded in a clear understanding of their roles and related approaches to learning, (b) select and incorporate supervisor feedback about the goals and tasks of supervision, and (c) identify areas of growth based on the alignment of supervisees’ and instructors’ role perspectives.


Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.



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Q Sample Statements and Factor Array

Eric R. Baltrinic, PhD, LPCC-S (OH), is an assistant professor at the University of Alabama. Ryan M. Cook, PhD, ACS, LPC, is an assistant professor at the University of Alabama. Heather J. Fye, PhD, NCC, LPC, is an assistant professor at the University of Alabama. Correspondence may be addressed to Eric Baltrinic, The University of Alabama, Box 870231, Tuscaloosa, AL 35487, erbaltrinic@ua.edu.

A Q Methodology Study of a Doctoral Counselor Education Teaching Instruction Course

Eric R. Baltrinic, Eric G. Suddeath

Many counselor education and supervision (CES) doctoral programs offer doctoral-level teaching instruction courses as part of their curriculum to help prepare students for future teaching roles, yet little is known about the essential design, delivery, and evaluation components of these courses. Accordingly, the authors investigated instructor and student views on the essential design, delivery, and evaluation components of a doctoral counselor education teaching instruction (CETI) course using Q methodology. Eight first-year CES doctoral students and the course instructor from a large Midwestern university completed Q-sorts, which were factor analyzed. Three factors were revealed, which were named The Course Designer, The Future Educator, and The Empathic Instructor. The authors gathered post–Q-sort qualitative data from participants using a semi-structured questionnaire, and the results from the questionnaires were incorporated into the factor interpretations. Implications for incorporating the findings into CES pedagogy and for designing, delivering, and evaluating CETI courses are presented. Limitations and future research suggestions for CETI course design and delivery are discussed.

Keywords: teaching instruction course, Q methodology, pedagogy, counselor education, doctoral students


Counselor education doctoral students (CEDS) need teaching preparation as part of their doctoral training (Hall & Hulse, 2010; Orr et al., 2008), including the completion of formal courses in pedagogy, adult learning, or teaching (Barrio Minton & Price, 2015; Hunt & Weber Gilmore, 2011; Suddeath et al., 2020). Teaching instruction courses may occur within or outside of the counselor education curriculum. Within counselor education, counselor education teaching instruction (CETI) courses are those doctoral-level seminar or semester-long curricular experiences designed to provide CEDS with the basic foundational knowledge for effective teaching (Association for Counselor Education and Supervision [ACES], 2016). CETI courses are cited as an important foundational training component for preparing CEDS for success in fulfilling future teaching roles (ACES, 2016). Additionally, simply possessing expert knowledge in one’s field (e.g., counseling) is not sufficient to support student learning in the classroom (ACES, 2016; Waalkes et al., 2018), a reality recognized in counselor education some time ago by Lanning (1990).

To increase the attention to and strengthen the rigor of teaching preparation, the Council for Accreditation of Counseling and Related Educational Programs (CACREP) developed standards for fostering students’ knowledge and skills in teaching through curricular and/or experiential training (CACREP, 2015). Specifically, within the CACREP (2015) teaching standards, CEDS need to learn “instructional and curriculum design, delivery, and evaluation methods relevant to counselor education” (Section 6, Standard B.3.d.). Although programs may use teaching internships (Hunt & Weber Gilmore, 2011), structured teaching teams (Orr et al., 2008), coteaching (Baltrinic et al., 2016), and teaching mentorships (Baltrinic et al., 2018) to address standards and train CEDS for their future roles as educators, teaching coursework is cited as the most common preparation practice (Barrio Minton & Price, 2015; Suddeath et al., 2020; Waalkes et al., 2018). Despite our knowledge that teaching coursework is commonly used for teaching preparation (Barrio Minton & Price, 2015; Suddeath et al., 2020), little is known about how counselor educators design and deliver these courses within counselor education. Although a few studies in counselor education and supervision address teaching coursework (e.g., Suddeath et al., 2020; Waalkes et al., 2018), it is in a cursory way or as one part of a broader inquiry into teacher preparation processes.

Perceived Effectiveness of CETI Courses
     Ideally, teaching coursework, whether offered within counselor education specifically or not, should provide doctoral students with a basic framework for effective teaching. Unfortunately, as previously mentioned, little is known about what constitutes a CETI course. Moreover, the few studies that address this training component suggest inconsistency in its perceived value and effectiveness. For example, early research by Tollerud (1990) and Olguin (2004) found no difference in terms of teaching self-efficacy between those with and without coursework, regardless of the number of courses taken. Similarly, in Hall and Hulse’s (2010) study examining counselor educators’ doctoral teaching preparation and perceived preparedness to teach, participants found their teaching coursework least helpful for preparing them to teach. To improve the effectiveness of their coursework, participants in Hall and Hulse’s study indicated a desire for multiple courses with a greater focus on the practical aspects of teaching, approaches for teaching adult learners, and more opportunities to engage in actual teaching during the course.

In a recent study by Waalkes et al. (2018), participants expressed similar sentiments reporting a general lack of emphasis and rigor in teacher preparation as compared to other core areas of development and especially for teaching coursework. Specific deficiencies included a lack of emphasis on pedagogy and teaching strategies and a discrepancy between their teaching coursework and their actual teaching responsibilities as current counselor educators (Waalkes et al., 2018). Given their experience, participants indicated a desire for greater integration of doctoral-level teaching coursework throughout their programs as well as “philosophy and theory, pedagogy/teaching strategies, understanding developmental levels of students, course design, assessment, and setting classroom expectations” (Waalkes et al., 2018, p. 73).

Unlike Tollerud (1990) and Olguin (2004), Suddeath et al. (2020) found that formal teaching coursework significantly predicted increased self-efficacy toward teaching. Furthermore, participants indicated that formal coursework strengthened their self-efficacy toward teaching slightly more than their fieldwork in teaching experiences. However, it is unclear from this study what aspects of the CEDS’ coursework contributed to increased self-efficacy. In a study by Hunt and Weber Gilmore (2011), CEDS identified elements such as the creation of syllabi, exams, rubrics, and a philosophy of teaching and receiving support and feedback from instructors and peers as most helpful in their coursework experiences. Those who did not find the course helpful expressed a desire for more opportunities to engage in actual teaching. Overall, the literature addressing the relative effectiveness of teaching coursework suggests the need to (a) improve teaching courses, (b) connect teaching courses to additional teaching experiences, and (c) make it a meaningful and impactful experience for CEDS.

Instructor Qualities and Course Delivery
     Counselor education research also suggests that instructor qualities and course delivery influence the learning experiences of counseling students (Malott et al., 2014; Moate, Cox, et al., 2017; Moate, Holm, & West, 2017). Regarding instructor qualities, two recent studies examining novice counselors’ instructor preferences within their didactic (Moate, Cox, et al., 2017) and clinical courses (Moate, Holm, & West, 2017) found that, overall, participants preferred instructors who were kind, supportive, empathic, genuine, and passionate about the course. Likewise, Malott et al. (2014) reported that instructors who were caring, which included characteristics such as respect, interest, warmth, and availability, were “essential in motivating learning” (p. 295). Moate and Cox (2015) also emphasized the importance of cultivating a supportive and safe learning environment for increasing students’ active participation and engagement in their learning.

Regarding course delivery, overall participants in didactic and clinical courses preferred instructors who were pragmatic and connected course material to their actual work as counselors (Moate, Cox, et al., 2017; Moate, Holm, & West, 2017). Within didactic courses specifically—which included career counseling, theories, ethics, and diagnosis—Moate, Cox, et al. (2017) emphasized students’ lack of preference for instructors who primarily utilized lecture or PowerPoint for instruction. This relates to the topic of teacher-centered versus learner-centered approaches. Those who use teacher-centered approaches utilize lecture as the primary mode of delivery and focus on the transmission of content through lecture from the experienced expert to the inexperienced novice, which may foster passive learning (Moate & Cox, 2015). In contrast, those who use learner-centered approaches emphasize shared responsibility for learning, which encourages active learning and application of course content through collaborative learning activities to tap into the collective knowledge of the group as well as supporting students’ active engagement and application of course content (Malott et al., 2014; Moate & Cox, 2015).

Although Moate, Cox, et al. (2017) and Moate, Holm, and West (2017) focused on master’s-level versus doctoral-level students, their findings suggested the importance of instructor qualities and approaches as well as student perspectives within course design and delivery. Moate, Cox, et al. (2017) and Moate, Holm, and West (2017) did not link instructor qualities to the training they received within doctoral CETI coursework, but having an understanding of these connections may aid doctoral instructors’ design and delivery of CETI courses to better meet student needs.

Regarding instructor qualities and approaches to course delivery within doctoral CETI courses specifically, our literature search identified two studies that minimally addressed these components. Participants in the studies of both Waalkes et al. (2018) and Hunt and Weber Gilmore (2011) emphasized the importance of feedback from professors and classmates within CETI courses for strengthening their preparedness to teach. Neither study described exactly how this feedback supported their preparedness to teach, the type of feedback received, or the instructor’s approach to delivering feedback.

The Current Study
     Teaching preparation is an essential component of CEDS’ training (ACES, 2016), as teaching and related responsibilities (a) consume a greater proportion of time than any other responsibility of a counselor educator (Davis et al., 2006) and (b) impact CEDS’ confidence and feelings of preparedness to teach (Hall & Hulse, 2010; Suddeath et al., 2020). Still, some findings suggest a lack of rigor concerning teaching preparation compared to other core doctoral training areas (e.g., research and supervision; Waalkes et al., 2018). Although teaching preparation research in general is gaining momentum, there are no findings clarifying what components of formal coursework most support students’ development as teachers. In fact, findings are mixed regarding its effectiveness (e.g., Suddeath et al., 2020; Waalkes et al., 2018). Furthermore, no in-depth research exists on how counselor educators implement formal teaching courses within counselor education or how those teaching courses are designed and delivered by counselor educators and experienced by CEDS. Yet, our experience tells us and research confirms (e.g., Waalkes et al., 2018) that counselor education programs increasingly require CEDS to engage in CETI courses as one way to develop teaching competencies, with some citing it as the most widely utilized way in which programs train CEDS to teach (ACES, 2016; Barrio Minton & Price, 2015; Suddeath et al., 2020).

As variability exists in how respective programs deliver CETI courses (Hunt & Weber Gilmore, 2011), we studied a single CETI course as a way to illustrate an example of common issues and potential discrepancies faced by students and instructors engaged in a doctoral CETI course. We examined this course, taking into account both experienced instructor and novice student views, to (a) reveal common views on ideal course design, delivery, and evaluation components among participants navigating a common curriculum; (b) identify any similar or divergent views between the instructor and students; and (c) determine how to design course content and instruction to meet the future needs of students. The study was guided by the research question: What are instructor and student views on the essential design, delivery, and evaluation elements needed for a CETI course?


     Q methodology is a unique research method containing the depth of qualitative data reduction and the objective rigor of by-person factor analysis (Brown, 1993). Researchers have effectively utilized this method in the classroom setting to facilitate personal discovery and to increase subject matter understanding (Watts & Stenner, 2012). Specifically, students’ self-perspectives are investigated and then related to other students’ views, which are then related to nuances within their own views (Good, 2003). Q methodology has also been effectively used as a pedagogical exercise to examine subjectivity in intensive samples of participants (McKeown & Thomas, 2013). Focusing on intensive samples, and even single cases, allows researchers to retain participants’ frames of reference while concurrently revealing nuances within their views, which may be lost within larger samples (Brown, 2019). Yet, the rigor of findings from intensive samples derived from Q factor analysis remains.

We selected Q methodology for the current study versus a qualitative or case study approach (Stake, 1995) to reveal common and divergent viewpoints in relation to common stimulus items (i.e., a Q sample composed of ideal design, delivery, and evaluation of CETI course components from the literature). We also wanted both the instructor and students participating in the sampled doctoral CETI course to provide their subjective views on the optimal design, delivery, and evaluation components of a doctoral CETI course, while incorporating the rigorous features of quantitative analysis (Brown, 1980).

Concourse and Q Sample
     Specific steps were taken to develop the Q sample, which is the set of statements used to assist participants with expressing their views during the Q-sorting process. The first step is selecting a concourse, which is a collection of opinion statements about any topic (Stephenson, 2014). Many routes of communication contribute to the form and content of a concourse (Brown, 1980). The concourse for this study was composed of statements taken by the authors from select teaching literature and documents (e.g., ACES, 2016; McAuliffe & Erickson, 2011; West et al., 2013).  After carefully searching within these sources, researchers selected statements specifically containing teaching experts’ views on essential components for teaching preparation, in general, and CETI courses in particular. The concourse selection process resulted in over 240 concourse statements, which was too many for the final Q sample (Brown, 1970, 1980).

Second, the concourse of statements was reduced by the first author using a structured deductive Q sample design shown in Table 1 (Brown, 1970). Data reduction using a structured design results in a reduction of concourse statements into a manageable Q sample (McKeown & Thomas, 2013). Accordingly, data reduction proceeded with the removal of unclear, fragmented, duplicate, or unrelated statements until there were eight items for each of the types, resulting in the structured 48-item sample shown in the Appendix.


Table 1

Structured Q Sample

Dimensions Types N
1. Design a. Materials
(Items 4, 5, 10, 13, 14, 23, 28, 39)
b. Experiences

(Items 3, 22, 24, 25, 36, 37, 43, 45)

2. Delivery


c. Content
(Items 2, 15, 17, 18, 26, 27, 35, 38)
d. Process

(Items 6, 8, 12, 30, 32, 41, 44, 46)



3. Evaluation e. Formative
(Items 7, 20, 21, 29, 33, 40, 42, 47)
f. Summative

(Items 1, 9, 11, 16, 19, 31, 34, 48)



*Q-set = D (Criteria) (Replications); D ([1₂] [2₂] [3₂]) (n); D (2) (2) (2); D = 8 combinations;
D (2) (2) (2) (6 replications); D = 48 statements for the Q sample.


Third, the 48-item Q sample was then evaluated by three expert reviewers using a content validity index (Paige & Morin, 2016). Expert reviewers who had a minimum of 10 years of experience as counselor educators, had designed and delivered doctoral CETI courses, had published frequently on teaching and learning, and were familiar with Q methodology were solicited by the first author. Accordingly, expert reviewers rated each of the 48 items on a 4-point scale using three criterion questions: 1) Is the statement clear and unambiguous as read by a counselor educator? 2) Is the statement clear and unambiguous as read by CEDS? and 3) Is the statement distinct from the other statements listed here? Items receiving a score of 3 (“Mostly”) or 4 (“Completely”) were included; items receiving a score of 2 (“Somewhat”) were reviewed and modified by the authors for appropriateness; items receiving a score of 1 (“Not at all”) were discarded from the sample. After the three expert evaluators completed the content validity index, the authors refined the Q sample by rewriting two items to improve clarity, eliminating one duplicate item, and adding an item the reviewers thought important. For the final step, two of the experts completed Q-sorts to assure the final Q sample facilitated the expression of views on supervisee roles. The results of these two pilot Q-sorts were not included in the data analysis.

Participant Sample
     Researchers followed McKeown and Thomas’ (2013) recommendations for selecting an intensive participant sample (i.e., fewer than 20 participants), which included a combination of purposeful and convenience sampling strategies (Patton, 2015) to obtain participants for the study. We purposefully selected the doctoral CETI course and the instructor because it was offered within a reputable, CACREP-accredited doctoral program; developed by a counselor educator known for teaching excellence and professional contributions; and taught and refined in an on-campus, in-person program by that same instructor for over 16 years. Additionally, the participants engaged in the course at the time of investigation constituted a convenience sample of eight first-year CEDS. Participants collectively represented a group of individuals holding similar theoretical interests and the ability to provide insight into the topic of investigation (Brown, 1993).

All nine participants were from a large, top-ranked counselor education program located in the Midwest. Seven of the students identified as White cisgender females, and one as a cisgender Asian male. Four student participants were in the 25 to 30-year-old range, and four were in the 31 to 35-year-old range. The instructor was in the 50 to 55-year-old range, who identified as a White cisgender male. None of the student participants reported having previous teaching experience.

Data Collection
     After obtaining IRB permission, the first author collected the initial consent, demographic, Q-sort, and post–Q-sort written data from the students and instructor using a semi-structured questionnaire. The nine participants (n = 8 students; n = 1 instructor) were each asked to rank-order the 48 items in the Q sample along a forced choice grid from most agree (+4) to most disagree (-4). The conditions of instruction used for the students’ and instructor’s Q-sorts stemmed directly from the research question. After completing this Q-sort, participants were asked by the first author to provide written responses, using a semi-structured questionnaire, for the top three items with which they most (+4) and least (-4) agreed and were asked to comment on any other items of significance.

The first author asked the course instructor to respond in writing to three questions, in addition to those prompts contained in the semi-structured questionnaire. This was done to add nuance and context to the results. The additional questions and highlights from the instructor’s responses are shown in Table 2.

Data Analysis

Nine Q-sorts completed by participants were each entered into the PQMethod software program V. 2.35 (Schmolck, 2014). A correlation matrix was then generated reflecting the “nature and extent of relationships” among all the participants’ Q-sorts in the data set (Watts & Stenner, 2012, p. 111). The correlation matrix served as the basis for factor analysis, which was completed using the centroid method (Brown, 1980). Essentially, factor analysis allows researchers to examine the correlation matrix for patterns of similarity among the participants’ Q-sorts. In the current study, we were interested in similar and divergent patterns among the instructor’s and students’ Q-sorts on essential doctoral CETI course components. In other words, data analysis in Q studies is possible because all participants rank-order a Q sample of similar items, which allows researchers to inter-correlate those Q-sorts for subsequent factor analysis.

Given the low number of participants, we initially extracted five factors from the correlation matrix,  which yielded fewer significant factor loadings (i.e., a correlation coefficient reflecting the degree to which a participant’s Q-sort correlates with the factor). Therefore, we extracted three factors, which yielded a higher number of factor loadings. The three factors were rotated using the varimax method, which we selected because (a) we had no preconceived theoretical notions regarding the findings, (b) we were blind to participant identifying information in the data, and (c) we intended to obtain dominant views among participants within the same course (Watts & Stenner, 2012). The varimax factor rotation method helps researchers to identify individual factor loadings “whose positions closely approximate those of the factor” (Watts & Stenner, 2012, p. 142). In Q methodology, a factor is a composite or ideal Q-sort to which individual participants correlate (Watts & Stenner, 2012). Overall, data analysis steps yielded a 3-factor solution containing at least two significant factor loadings on each factor, which is the minimum suggested number of factor loadings for a factor to hold significance (Brown, 1980). Notably, the final 3-factor solution contained significant factor loadings for all nine of the study participants, which suggests the rigor of the collective viewpoints (i.e., factors) discussed in the results.


Table 2

Summary of Instructor Responses

Interview Question Interview Responses (Factor A Exemplar)
1. What is important for planning, delivering, and evaluating doctoral-level counselor education teaching instruction courses? I think of the different elements that go into teaching and I think these are the things that students need to be exposed to, such as: developing a teaching philosophy, creating a syllabus, evaluating other instructors’ syllabi, making selections on textbooks, looking at equity in the classroom, backwards design of curriculum, having a small group teaching experience, having a large group teaching experience, using experiences in the classroom for developing reflective practice, and reviewing essential readings in the teaching field. I also think it is essential that we teach students how to use online platforms, so they have exposure and, to what degree we can, competency, to online platforms.
2. What are some significant lessons learned over the past 16 years as an instructor of a counselor education teaching instruction course? This course is a change in pace for most students in my program. For that reason, students generally seem excited about this course. Having them excited about taking the course makes teaching the course a pure joy. Along with the excitement, students bring a level of naïveté to the topic. They have been students, but they do not have a lot of exposure to being a teacher. In my field of counseling, students at the doctoral level have exposure to counseling, so they come in with a level of exposure and expertise in that area, but in teaching it seems all new to them. And that makes a course fun for me.


I believe the hardest thing for students to learn is to set aside their own passions and misconceptions about what their students need to know in service of what they must know to be an effective counselor. What their passions are and what students need to know are not always the same thing. I notice students are generally apprehensive about their performance when it comes to teaching. I have to constantly remind myself that it doesn’t come automatically to them as it does to me, having taught many years. So I have to reintroduce myself to the idea of performance anxiety in the classroom. That’s where I think the in-class reflective practice piece fits in nicely for them. They get a chance to think and talk through their anxiety about teaching.

3. What role does a counselor education teaching instruction course serve for preparing doctoral students to teach? I can’t imagine a program that does not have a teaching instruction course, preferably taught within the program, that would be able to adequately prepare students for future faculty roles. Most of my career has been to emphasize the need for good faculty instruction on teaching in the counseling field.



The data analysis revealed three significantly different viewpoints (i.e., Factors A, B, and C) on the essential design, delivery, and evaluation elements needed for a doctoral CETI course. All participants in the study were significantly associated with one of the three factors. Specifically, one student participant and the course instructor were significantly associated with Factor A (i.e., had factor loadings of .37 or higher; .50 and .84, respectively). Five of the eight student participants were significantly associated with Factor B (.72, .70, .66, .78, and .60, respectively). Two of the eight student participants were significantly associated with Factor C (.75 and .87, respectively). Select participant quotes from participants’ post-sort questionnaires were incorporated into the factor interpretations below to provide contextual details for each factor.

Factor A: The Course Designer
     Factor A is most distinguished by the view that CETI courses should result in students having the ability to design their own counseling courses, which differs from Factors B and C (Item 37; +4, 0, 0, respectively). This pervasive opinion is contained in the instructor’s semi-structured questionnaire response to Item 37:

I cannot imagine the purpose of having a course for teaching in counselor education without the purposeful outcome being to create a course. The ability to do course development, to me, is the skillset that doctoral graduates should have from a teaching course.

The student associated with this factor added, “I want this course to help me be successful, which means I have to practice . . . making a syllabus, working with students . . . the basis of the entire course is to learn to teach!” Learning how to design evaluations of the teaching and learning process (Item 48, +2) is also considered an essential CETI course component for Factor A. For Factor A, CETI courses need to include discussions about selecting textbooks (Item 14, +2) and opportunities to learn about classroom management (Item 18, +2). There was even stronger agreement that CETI courses need to include information about designing a syllabus (Item 39, +3) and constructing related course objectives (Item 33, +3), which would culminate in a plan for actual teaching experiences (Item 35, +3). Given the preference for technical and design elements in CETI courses, the authors have named Factor A The Course Designer.

Factor A placed less emphasis on the developmental level (Item 25, -3) and cultural differences (Item 38, -1) of students as essential components of a CETI course. But that does not suggest these elements are unimportant, as one participant illustrated: “All instructors need to be mindful of students’ cultural differences. Learning can only be effective in an environment conducive of understanding students’ differences.” Importantly, the Factor A view was not limited to just design and technical components. In fact, Factor A, like B and C, viewed having some type of teaching experience as an essential element of a CETI course (Item 46; +4, +4, +1, respectively).

Factor B: The Future Educator
     The Factor B viewpoint, which the authors named The Future Educator, placed importance on the use of interactive (Item 6, +4) and experiential (Item 45, +3) activities, more so than course design, as essential elements of a CETI course. In contrast to Factors A (-4) and C (-4), Factor B participants believed in the helpfulness of teaching to their peers (Item 44, +2). However, Factor B was most distinguished from Factors A (+1) and C (-1) in its belief that CETI courses should prepare students for future faculty roles (Item 43, +4). Collectively, individuals on this factor all agreed that the role of a CETI course was to help them be successful as future faculty members, and as one student stated, “Students need to be prepared for future faculty roles including teaching, so students need to be prepared to teach.”

     Factor B differed from Factors A and C on the importance of evaluation of students’ learning (Item 20, -1) and textbook selection (Item 14, -2), but agreed that videotaping students’ experiences is not an essential component of CETI courses (Item 11, -4). Regarding Item 11, participants noted, “Video recordings may not demonstrate the entire experience, including feelings and opinions of students and teachers.” Additionally, CEDS noted that being video-recorded could potentially “make students in the class act differently,” and, “if there is live evaluation” contained in a CETI course, “including guided reflection and time to process feedback, then video isn’t necessary.” This is an interesting finding given that many of the participants were trained in counseling programs that used video work samples as the basis for supervision feedback related to counseling skills development.

Factor C: The Empathic Instructor
     Factor C represented a preference for instructor qualities and intentional communication (i.e., delivery) more so than design issues (Factor A) or future faculty preparation (Factor B). For instance, Factor C participants believed that instructors of CETI courses should be passionate about teaching (Item 30, +4), compared to -1 and 2 for Factors A and B, respectively. As one student put it, “I feel as though passion fuels everything else in the course: effort, preparation, and availability of the instructor. Passion is everything.” According to Factor C, CETI instructors should be approachable (Item 32, +4), model and demonstrate how to provide feedback for future student encounters (Item 26, +3), and check in often with students to determine their level of understanding (Item 21, +3). However, when designing, delivering, and evaluating CETI courses, Factor C participants highlighted the developmental level (Item 25, +2) and cultural differences (Item 38, +4) of students, which contrasts with Factors A and B. Factor C simply placed higher importance on these items compared to the other factors.

Factor C was also distinguished by what is not essential for a CETI course, such as planning for a teaching experience (Item 35, -1), processing fellow classmates’ teaching experiences (Item 29, -3), and being able to design evaluations of teaching and learning (Item 48, -4), which, as one participant stated, are “usually dictated by the institution where you are employed.” Factor C placed less emphasis on specific feedback (i.e., content-oriented) instructors provide to students on their teaching (Item 42, -1) in favor of the instructor’s approachability. As one participant described, “There is not growth without feedback . . . if the instructor is approachable then the student will feel as if they can approach the instructor with any concerns, including any items on this Q sample.” Given the preference for instructor qualities and communication, the authors have named Factor C The Empathic Instructor.

     Despite the distinguishing perspectives contained in each individual factor, significant areas of consensus existed among factors with respect to particular Q sample items. For example, Factors A, B, and C believed that designing a syllabus is an important aspect of a CETI course (Item 39; +3, +3, and +2, respectively). All three factors commonly acknowledged that CETI course instructors ought to consider the pedagogy used for course delivery (Item 10; 0, +1, and +1, respectively), and that CETI courses should prepare doctoral students for teaching internships (Item 22; 0, +1, 0). CETI courses should address classroom management issues as well (Item 18; +2, +1, and 0, respectively). Finally, CETI courses should contain intentional student engagement efforts (Item 3; +2, +1, and +2) with regular and relevant discussions (Item 8; +1, +3, and +2, respectively).

Consensus among factors also existed around the non-essential elements of a CETI course. Specifically, all three factors expressed that midterm (Item 16; -3, -3, and -2, respectively) and final course exams (Item 19; -3, -4, and -3, respectively) were not essential components of a CETI course. One male participant summarized this point: “I think students’ progress can be evaluated by exploring what students think they learn, how much insight they gain, and how they plan to apply what they learn in the class, rather than using exams or pre/post-tests.” Similarly, another female participant cited, “Exams will not show progress in teaching skills. You need real life experiences and discussion.” Overall, participants across factors believed that exams promote memorization of content more so than the fair and commensurate evaluation of teaching knowledge and skills. In other words, they believed that CETI courses should be more experiential in nature.


The purpose of this study was to gain insight into the essential design, delivery, and evaluation elements needed for a CETI course. The results produced three unique views on this topic. In addition, although participants’ views varied, with Factor A emphasizing the technical components of creating a course, Factor B emphasizing experiential components and future faculty roles, and Factor C emphasizing the character and qualities of the instructor, there were several areas of consensus. Specifically, participants across all three factors agreed on the importance of CETI courses for (a) preparing CEDS for teaching internships (Hunt & Weber Gilmore, 2011; Orr et al., 2008; Waalkes et al., 2018); (b) using pedagogy to guide CETI course delivery (ACES, 2016; Waalkes et al., 2018); (c) designing syllabi (Hall & Hulse, 2010; Hunt & Weber Gilmore, 2011); and (d) developing teaching skills such as classroom management, engaging students, and facilitating class discussions (Hall & Hulse, 2010; Hunt & Weber Gilmore, 2011; Waalkes et al., 2018). As indicated above, these points of consensus align with previous counselor education literature, including participants’ desire for CETI courses to prepare them for teaching as counselor educators (Baltrinic et al., 2016).

An expected finding within Factor C is the influence of the instructor’s qualities (e.g., approachability and passion) and delivery (e.g., seminar format) on participants’ views of the CETI course (Moate, Cox, et al., 2017). The instructor delivered the course in a seminar format emphasizing student leadership for content sharing and de-emphasizing the use of lecture, which relates to consensus factor scores on Item 40, “In a teaching course, I should be evaluated on my ability to do a lecture.” However, it is unclear from the data how participants understood the purpose or role of lectures for engaging students in the classroom. It is notable to mention, however, that participants delivered counseling content to master’s-level students as part of their teaching experiences for the course and would thus benefit from feedback on their performance.

Many have suggested that utilizing lecture as the principal mode of delivery fosters passive learning and does not necessarily support students’ engagement in course content or development of decision-making, problem-solving, or critical-thinking skills (e.g., Malott et al., 2014; Moate & Cox, 2015). Participants in Waalkes et al.’s (2018) study indicated that their training primarily equipped them to lecture, which they reported did not fully prepare them for their roles as educators. Although Moate and Cox (2015) do not recommend utilizing lecture as the only method for helping students engage with course content, both they and Brookfield (2015) emphasized the false dichotomy that exists between teacher-centered approaches, which are typically characterized by lecturing, and learner-centered approaches, which often rely on using discussions as a primary mode of teaching.

Rather than dismissing lectures entirely, instructors can utilize lectures to provide a broad overview of the course content, to explain difficult or complex concepts with frequent examples, to generate students’ engagement and interest in a topic, and/or to model the types of skills and dispositions instructors would like to foster in students (Brookfield, 2015; Malott et al., 2014; Moate & Cox, 2015). Thus, lectures can serve as a starting point to model and frame course content for further discussion and application using other teaching methods (Moate & Cox, 2015). Overall, we believe that it is important for students to possess a variety of teaching methods for engaging students with course content and understand when and how to apply various methods effectively, which requires CETI instructor feedback and support.

Surprising results included participants’ low rankings of Item 12 regarding the importance of role-playing, of Item 7 regarding the importance of peer feedback, and of Item 11 regarding the use of video recordings of teaching—this latter finding contrasts with participant responses in Hunt and Weber Gilmore’s (2011) study, who found “sharing and critiquing a video of us teaching” an especially valuable component of their coursework (p. 147). Current counselor education research consistently affirms the importance and reported desire for formal coursework to incorporate practical teaching components related to the actual work of a counselor educator (Hall & Hulse, 2010; Hunt & Weber Gilmore, 2011). Instructors who employ learner-centered approaches often emphasize the role of peers and the use of peer feedback to enhance student learning (Moate & Cox, 2015). It could be that participants assumed that role-plays pertain to practicing counseling-related interventions. As such, it may prove helpful if counselor educators consider situational uses for role-plays, such as a way of managing difficult situations in the classroom (e.g., classroom management), or for addressing sensitive topics related to multicultural concerns, among others (Hunt & Weber Gilmore, 2011). Instructors can model how to facilitate these skills, which can be followed up with dyadic or triadic student role-plays.

Additionally, participants did not place importance on peer feedback over the instructor’s feedback or learning how to provide feedback to their future students in the instructor role. Instead, participants favored feedback from the instructor on their own teaching skills, the proposition here being that instructors can provide feedback from a position of experience, more so than peers who do not have teaching experience. It is plausible that CEDS attending CETI courses need feedback about how to provide feedback and perceive this as an important teaching skill (Hunt & Weber Gilmore, 2011). This is important because students in CETI courses are likely (a) learning the course-related content and (b) learning the pedagogy for delivering counseling-related content in their future classrooms (ACES, 2016).

     Findings support two important implications for counselor educators, the first of which is illustrated by the instructor from this study: “What students’ passions are and what students need to know are not always the same thing.” One can reasonably expect discrepancies between the perceptions of the instructor and those of students as evidenced by some participants’ dissatisfaction with the content and delivery of their CETI courses (e.g., Hall & Hulse, 2010; Waalkes et al., 2018). However, we encourage counselor educators as they teach to consider students’ views (i.e., factors) even if they feel their own views and curriculum support best practice. We also acknowledge that some instructors may have limited autonomy in the construction of CETI course syllabi and assignments because of accreditation requirements.

In thinking about the implications for counselor educators, to the extent possible, tailoring a CETI course to the reported preferences/needs of the students seems essential for preparing them for future teaching (Waalkes et al., 2018) as well as for increasing student engagement (e.g., Moate & Cox, 2015). For example, counselor educators can incorporate technology, curricular, and course design elements into CETI courses (Factor A). Counselor educators can link teaching experiences to future faculty roles by exploring them in the context of accreditation requirements, their impact on tenure and promotion practices (Davis et al., 2006), and managing teaching loads in the context of other duties and institutional demands (Silverman, 2003; Factor B). Finally, counselor educators can incorporate Factor C views into their CETI courses by attending to the instructor qualities, modeling passion, demonstrating approachability, and frequently checking in on students’ progress (Malott et al., 2014). Additionally, the authors suggest that counselor educators incorporate aspects of all three factors into their own teaching practice and link the CETI course to future supervised teaching experiences such as teaching practicum or internships as suggested by Waalkes et al. (2018).

Second, counselor educators should obtain and incorporate CEDS’ perspectives early when designing, delivering, and evaluating CETI courses, which can be helpful for investigating (formally or informally) the impact of those instructional strategies and curriculum on CEDS’ teaching skill development and is recommended as a best practice by Malott et al. (2014). It is common practice to collect student opinions of instruction at the end of the semester, and many instructors collect ongoing data on how students are progressing in the semester. Q methodology could be used in ways similar to this study to help instructors positively influence CEDS’ learning. Additionally, counselor educators could utilize Q methodology to identify factors and use those factors to improve their own performance, to design other teaching-related courses, and to affect CEDS’ classroom experiences and learning outcomes. Counselor educators could also compare their CETI courses with other instructors’ courses to see trends or use Q methodology to identify factors within or between CETI courses over time.

Limitations and Future Research
     Q methodology studies gather and rigorously analyze data to reveal common viewpoints among participants. Factors do not generalize in Q studies the same way as findings from traditional factor analysis (i.e., R methodology; Brown, 1980). Rather, factors are simply collections of opinion, the structure of which may or may not exist in other counselor education settings. However, CETI instructors can test this proposition by having students in other CETI courses complete Q-sorts with the current Q sample or by developing and testing relevant Q samples of their own design. In fact, because the Q sample was used in one class, researchers are encouraged to test propositions with larger samples across programs to see if the factors exist in multiple settings. Finally, because the participants in the current study were a convenience sample from a brick-and-mortar program composed mostly of White females within a single course, participant diversity was lacking. Future studies could examine the views of students of color and international students in larger samples across multiple courses and multiple formats (e.g., online and hybrid programs).

Additional conditions of instruction could be added to expand teaching instruction viewpoints using a single-case design approach (Baltrinic et al., 2018). Supporting Q findings with qualitative information from in-depth interviews from student and instructor factor exemplars would add more nuance to the existing factors as well. Finally, following in our footsteps, researchers could develop and administer their own teaching instruction Q-sorts before beginning a CETI course to tailor the development and delivery of the course to the needs of their students. This would allow CETI instructors to develop studies, which may reveal idiosyncratic and shared experiences (Stephenson, 2014) related to programs’ CETI course design, delivery, and evaluation.

     We proposed in this article that doctoral CETI courses offer a starting point for CEDS’ teaching preparation. We elaborated further that despite accreditation guidelines and the anecdotal experiences of counselor educators in various programs, little is known about what specifically to include in a CETI doctoral course. Counselor educators and CEDS alike can honor course variability, anecdotal experiences, and academic freedoms, while providing some structure to their CETI courses. This goal can be achieved by acknowledging that CETI course design, delivery, and evaluation include professional-level, student, and instructor perspectives. The Q factors in the current study revealed one way to include multiple perspectives and to identify preferred and recognizable CETI course components.


Conflict of Interest and Funding Disclosure
The authors reported no conflict of interest
or funding contributions for the development
of this manuscript.



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College Teaching Q Sample Statements and Factor Array

# Q Sample Statement A B C
1 Peers should be able to review the courses I develop as part of a teacher training course. -1 -2 -2
2 Teacher training courses should have case examples. -2  0  1
3 Designing student engagement is important for a course on teaching.  2  1  2
4 Courses in teacher training should have relevant technology resources.  1 -2 -2
5 Learning how to assess students’ learning is important in a teaching course.  3  0  2
6 Courses in teacher training should have interactive activities.  0  4  1
7 I should have student feedback for the classes I teach while a student in a teacher
training course.
-2  0  2
8 Teacher training courses should have relevant discussion.  1  3  2
9 Teacher training courses should have student feedback mechanisms for the instructor.  0  0  0
10 A teaching course should consider the pedagogy used for course delivery.  0  1  1
11 I believe that my teaching should be videoed in my teacher training course. -1 -4 -1
12 Having role-plays on teaching is important for a teaching course. -4 -3  0
13 Teaching instruction courses should incorporate adult learning theories.  0 -1  0
14 Selecting a textbook is an important part of learning in a teaching course.  2 -2  1
15 Content in teacher training courses should be up to date. -1  1 -1
16 Teacher training courses should have midterm evaluations of my work in the course. -3 -3 -2
17 Teacher training courses should have breakout groups. -3 -3 -3
18 Teacher training courses should address classroom management.  2  1  0
19 Teacher training courses should have course exams. -3 -4 -3
20 A method to evaluate students’ learning is important to course design.  2 -1  1
21 Instructors of teacher training courses should check in often with students to determine their level of understanding. -1  0  3
22 Teaching instruction courses should prepare students for teaching internships.  0  1  0
23 Teacher training courses should have assigned readings on varied aspects of teaching
and learning.
 1 -2 -1
24 Considering students’ personal and cultural characteristics is important in designing a teaching course.  0  2  1
25 Considering students’ developmental level is important in designing a teaching course. -3 -1  2
26 Learning how to provide feedback to future students is important for a teaching course.  1  0  3
27 In a teacher training course, I should be expected to create a teaching philosophy.  4  1  3
28 Teacher training classes should have supplemental learning materials. -1 -2 -2
29 I should process fellow classmates’ teaching experiences as a part of a teacher
training course.
 1 -1 -3
30 The instructor in a teacher training course should be passionate about teaching. -1  2  4
31 In a teacher training course, I should be able to design a teaching instruction course. -4 -1 -4
32 Instructors of teacher training courses should be approachable.  0  2  4
33 Creating course objectives are important to a teaching course.  3  0  3
34 Teacher training courses should have pre/posttest of students’ learning. -2 -4 -3
35 Planning for a teaching experience is an important part of the course.  3  2 -1
36 Portions of teacher training courses should include lectures. -2 -1 -2
37 In a teacher training course, I should be able to design a counseling course.  4  0  0
38 Instructors of teacher training courses should anticipate students’ cultural differences. -1  2  4
39 Designing a syllabus is an important aspect of a teaching course.  3  3  2
40 In a teaching course I should be evaluated on my ability to do a lecture. -2  1 0
41 Decisions on how you will use media are important in designing a teacher training course.  0 -2 -2
42 Instructors of teacher training courses should provide appropriate feedback to students
on teaching.
 2  3 -1
43 Teaching instruction courses should prepare students for future faculty roles.  1  4 -1
44 In a teaching training course, I should have the opportunity to teach to my peers. -4  2 -4
45 Experiential activities are important in a teaching instruction course.  1  3  0
46 Having a teaching experience is important for a course on teaching.  4  4  1
47 In a teacher training course, I should be able to use technology to collect evaluation data. -2 -3 -2
48 In a teacher training course, I should be able to design evaluations of teaching and learning.  2 -1 -4


Eric R. Baltrinic, PhD, LPCC-S, is an assistant professor at the University of Alabama. Eric G. Suddeath, PhD, LPC, is an assistant professor at Mississippi State University – Meridian. Correspondence can be addressed to Eric Baltrinic, Graves Hall, Box 870231, Tuscaloosa, AL 35487, erbaltrinic@ua.edu.

Counselor Educators’ Teaching Mentorship Styles: A Q Methodology Study

Eric R. Baltrinic, Randall M. Moate, Michelle Gimenez Hinkle, Marty Jencius, Jessica Z. Taylor

Mentoring is an important practice to prepare doctoral students for future graduate teaching, yet little is known about the teaching mentorship styles used by counselor educators. This study identifies the teaching mentorship styles of counselor educators with at least one year of experience as teaching mentors (N = 25). Q methodology was used to obtain subjective understandings of how counselor educators mentor. Our results suggest three styles labeled as Supervisor, Facilitator, and Evaluator. Specifically, these styles reflect counselor educators’ distinct viewpoints on how to mentor doctoral students in teaching within counselor education doctoral programs. Implications and limitations for counselor educators seeking to transfer aspects of the identified mentorship styles to their own practice are presented, and suggestions for future research are discussed.

Keywords: teaching mentorship, counselor education, Q methodology, doctoral students, graduate teaching

Counselor educators mentor doctoral students in many aspects of the counseling profession, including preparation for future faculty roles (Borders et al., 2011; Briggs & Pehrsson, 2008; S.F. Hall & Hulse, 2010; Lazovsky & Shimoni, 2007; Protivnak & Foss, 2009). Counselor education doctoral students (CEDS) credit faculty mentor relationships in general, and teaching mentorships in particular, as strengthening their professional identities (Limberg et al., 2013). For example, co-teaching, a common form of teaching mentorship, includes relationships that allow CEDS to have instructive pedagogical conversations (Casto, Caldwell, & Salazar, 2005) and learn teaching skills (Baltrinic, Jencius, & McGlothlin, 2016).

Support for teaching mentorships is present in the higher education literature. Doctoral students across disciplines reported the helpfulness of regular mentoring (Austin, 2002) and careful guidance in teaching from faculty members (Jepsen, Varhegyi, & Edwards, 2012). Doctoral students attributed mentoring in teaching as important for increasing self-confidence and comfort with teaching as future faculty members (Utecht & Tullous, 2009). In counselor education, the specific benefits attributed to teaching mentorships included greater confidence in CEDS’ ability to find employment as faculty members (Warnke, Bethany, & Hedstrom, 1999) and greater confidence in CEDS’ teaching ability (S. F. Hall & Hulse, 2010). Doctoral students given teaching opportunities without mentoring risk developing poor attitudes and skill sets, instead of having critical experiences to help them become successful university teachers (Silverman, 2003). Overall, the benefits of teaching mentorships are important given that (a) teaching is a primary component of the faculty job (Davis, Levitt, McGlothlin, & Hill, 2006) and (b) new counselor educators need to sufficiently plan and implement quality teaching (Magnuson, Norem, & Lonneman-Doroff, 2009). Counselor education scholars agree on the importance of mentorship for socializing doctoral students for teaching roles (Baltrinic et al., 2016; Orr, Hall, & Hulse-Killacky, 2008), yet little research is available describing specific styles and approaches to teaching mentorship (S. F. Hall & Hulse, 2010). This gap in the literature is concerning given that new counselor educators reported mentoring and feedback on their teaching by senior faculty members was helpful in enhancing their pedagogical skills (Magnuson, Shaw, Tubin, & Norem, 2004).

Type and Style of Teaching Mentorship

In contrast to discrete faculty–student interactions or training episodes (Black, Suarez, & Medina, 2004), mentor relationships may occur over months and years. Kram (1985) has characterized these relationships as career (teaching skills) and psychosocial (mentor–mentee relationship) types. Career mentoring refers to the act of fostering skills development and sharing field-related content to mentees, and psychosocial mentoring pertains more to the interpersonal and relational aspects of entering a field (e.g., emotional support and working through self-doubt; Curtin, Malley, & Stewart, 2016). Both career and psychosocial mentoring types, or some combination, are used by academic faculty mentors (Curtin et al., 2016). But it is uncertain if these, or any other specific mentoring types, are used for teaching mentorships in counselor education. Teaching mentorships of all types allow faculty members to be flexible, emphasize multiple aspects of being a teacher, and allow for the inclusion of multiple mentors (Borders et al., 2011).

Teaching mentorships transpire through a variety of formal (more structured and planned) and informal (less structured and spontaneous) mentorship styles (Borders et al., 2012). For example, a CEDS may experience teaching mentorship as part of a structured pedagogy course (formal), or have an informal conversation with their faculty advisor about teaching experiences spontaneously during an advising session. Given the complexities and importance of mentor relationships in counselor training, little is known about either formal or informal styles. Thus, it is hardly surprising uncertainty exists regarding counselor educators’ preferred ways of mentoring in general (Borders et al., 2012) and mentoring in teaching in particular (S. F. Hall & Hulse, 2010).

We found no evidence in the counselor education literature describing common styles of teaching mentorship used by counselor educators. This is concerning given that faculty members tend to mentor in the manner that they were mentored (L. A. Hall & Burns, 2009), and that CEDS’ mentorship experiences are influential in shaping their careers as future counselor educators (Borders et al., 2011). Our purpose was to learn more about how counselor educators understand and use their own teaching mentorship styles, thus requiring that we measure aspects of sample members’ subjective understanding of this phenomenon. Therefore, we set out to answer the following research question: What are counselor educators’ preferred styles of engaging in teaching mentorships with CEDS?


Because Q methodology objectively analyzes subjective phenomena, such as people’s preferences and opinions on a topic (Stephenson, 1935), it was selected for this study to reveal the structure of counselor educators’ perspectives (i.e., factors) on the teaching mentorship styles used for preparing CEDS to teach. Q methodology embodies the relative strengths of quantitative and qualitative methodologies by drawing on the depth and richness of qualitative data and the objective rigor of factor analysis to analyze data (Shemmings, 2006).


The participants (N = 25) eligible for this study: (a) were currently employed as a full-time faculty member in a counselor education doctoral program and (b) had accrued at least one year of experience mentoring CEDS in graduate teaching as a counselor educator. Twenty-five is a sufficient number given that Q methodology simply seeks to establish, understand, and compare individuals’ self-referent views expressed through the Q sort process (Brown, 1980). Participants were both conveniently sampled (n = 10) from counselor educators attending a workshop on Q methodology and purposefully sampled (n = 15) through recruitment emails sent to faculty members at several prominent counselor education doctoral programs in the Eastern (n = 7), Midwestern (n = 10), and Southern (n = 8) regions of the United States. Data were collected from participants by mailing packets that contained an informed consent, basic demographic questionnaire, Q sort, post–Q sort questionnaire, and a postage-prepaid return envelope. (Additional participant demographics are shown in Table 1). Note, we abstained from collecting certain demographic data (e.g., race, ethnicity, university type) from participants in response to their stated concerns about anonymity during data collection. Also, participants in this study were those that completed Q sorts (N = 25) versus those (N = 54) counselor educators used to generate the concourse described below.

Table 1

Demographics of Participants (N = 25)

Age                                                   n (%)                        Rank                                                        n (%)

25–30                                            1 (4%)                    Full Professor                                       5 (20%)

31–40                                            7 (28%)                  Associate Professor                              8 (32%)

41–50                                            5 (20%)                  Assistant Professor                              12 (48%)

51–60                                            9 (36%)

61–65+                                          3 (12%)
Gender                                              n (%)                        Tenure Status                                           n (%)

Female                                           13 (52%)                Tenured                                               13 (52%)

Male                                              12 (48%)                Untenured                                            12 (48%)


Years of Teaching

Mentorship Experience                  n (%)                                                                                                         

1–5                                                 9 (36%)

6–10                                               3 (12%)

11–15                                             6 (24%)

16–20                                             4 (16%)


Concourse Generation and Selecting Items for the Q Sample

Q methodology studies begin with creating a concourse, or a collection of thoughts or sentiments about a topic (Stephenson, 1978), which serves as the source material for selecting items for the Q sample. To generate the concourse for this study, 54 counselor educators, each with a minimum of one year of experience mentoring doctoral students in graduate teaching, were solicited on a counseling listserv (see Table 2). Counselor educators each provided 5–10 opinion statements on teacher mentorship approaches for working with CEDS in response to one open-ended question: What are your preferred approaches to mentoring CEDS in teaching? This process resulted in 432 opinion statements. However, this was too many statements for participants to rank order during the Q sort process. Accordingly, a 2 x 2 factorial design based on Kram’s (1985) career and psychosocial mentorship types and Borders et al.’s (2012) formal and informal mentoring styles was used as a theoretical guide to obtain a reduced yet representative subset (sample) of statements from the concourse (for additional information on Q sample construction, see Paige & Morin, 2016).

Table 2

Demographics of Counselor Educators Providing Opinion Statements for Concourse (N = 54)

Age                                                n (%)                         Racial Identity                                 n (%)

25–30                                           0 (0%)                      African American                            4 (7%)

31–35                                         8 (15%)                     Native American/Indigenous        1 (2%)

36–40                                        13 (24%)                     Caucasian                                       38 (70%)

41–45                                          7 (13%)                    Hispanic/Latino(a)/Chicano(a)       5 (9%)

46–50                                         4 (7%)                      Multiracial                                         3 (6%)

51–55                                          7 (13%)                   Biracial                                  3 (6%)

56–60                                          7 (13%)

61–65                                          4 (7%)

66–70                                          3 (6%)

71–75+                                         1 (2%)


Gender                                          n   (%)                       Primary Professional Identity          n  (%)

Female                                         33 (61%)                  Counselor Educator                            51 (94%)

Male                                            19 (35%)                  School Counselor Educator                  3 (6%)

Transgender                                  1 (2%)

Gender Fluid                                  1 (2%)


Sexual Identity                             n   (%)                       Academic Rank                                  n  (%)

Lesbian                              3 (6%)                    Professor                                             9 (17%)

Gay                                                4 (7%)                    Associate Professor                             18 (33%)

Bisexual                                         4 (7%)                    Assistant Professor                              27 (50%)

Heterosexual                                43 (80%)


First, the lead author organized the 432 statements into two broad categories: informal and formal mentoring styles (Borders et al., 2012). Duplicate, fragmented, and unclear statements were identified and eliminated in this step. Then, the remaining 96 statements (i.e., 48 statements in the informal and formal categories, respectively) were each cross-referenced with two mentoring types (i.e., psychosocial and career; Kram, 1985). Similar to the first step, the lead author reviewed the content of each statement and eliminated any statements containing duplicate, fragmented, or unclear language, resulting in 52 statements across four domains: 13 statements representing informal and career, 13 statements representing informal and psychosocial, 13 statements representing formal and career, and 13 statements representing formal and psychosocial. Finally, the first author eliminated four and reworded two of the 52 statements after they were reviewed by the second, third, and fourth authors, resulting in a final sample of 48 statements (12 statements per domain). This final group of statements is called the Q sample, which in this case is a collection of statements that represent counselor educators’ perspectives on how to mentor CEDS in teaching. The 48-item Q sample constructed by the first author was reviewed by the second, third, and fourth authors to ensure that each item was unique and did not overlap with other statements, and was applicable to the study. The final Q sample was given to participants for rank ordering during the Q sort process.

Q Sort Process

After Institutional Review Board approval was obtained, 25 participants completed the Q sort process. During the Q sort process, participants were prompted to reflect on their personal experiences of mentoring teaching to CEDS and then asked to rank order the 48 items in the Q sample on a forced-choice frequency distribution, shown in Table 3. Participants indicated a conscribed number of items with which they most agreed (+4) to items with which they least agreed (-4) along the distribution. Items placed in the middle of the rank order indicated statements about which participants were neutral or ambivalent. After finishing the rank ordering of items, participants were asked to provide brief post–Q sort written responses for the top two or three statements with which they most and least agreed, which were incorporated into the factor interpretations found in the results section below.


Table 3

Q Sort Forced-Choice Frequency Distribution

Ranking Value          – 4         -3         -2            -1            0              +1           +2           +3           +4

Number of Items      3             4         6             7             8                7             6             4             3


Data Analysis

Twenty-five completed Q sorts were entered into the PQMethod software program V. 2.35 (Schmolck & Atkinson, 2012). The PQMethod software creates a by-person correlation matrix (i.e., the “intercorrelation of each Q sort with every other Q sort”) used to facilitate factor analysis and subsequent factor rotation (Watts & Stenner, 2012, p. 97). The purpose of factor analysis in Q methodology is to group small numbers of participants with similar views into factors in the form of Q sorts (Brown, 1980). Factor analysis helps researchers rigorously reveal subjective patterns that could be overlooked via qualitative analysis. A 3-factor solution was selected to provide the highest number of significant factor loadings associated with each factor (Watts & Stenner, 2012). Factors were then rotated using varimax criteria with hand rotation adjustments in order to best reveal groupings of individuals with similar Q sorts. The factor rotations increased the total number of significant factor loadings from 17 to 20 of 25 participants, shown in Table 4.

We approached analyzing and interpreting each factor in the context of all other factors to provide a holistic factor interpretation, versus favoring specific items (i.e., factor scores, +4 or -4) over others within a particular factor (Watts & Stenner, 2012). To do so, a worksheet was created from the factor array (see Table 5) for each individual factor containing the highest and lowest ranked items within the factor and those items ranked lower within the factor compared to other factors. Second, items in the worksheets were compared to participants’ demographic and qualitative responses associated with that factor in order to add depth and detail before the final step. Finally, the finished worksheets were used for constructing the factor interpretation narratives, which are written as a story containing the viewpoint of the factor as a whole.


Table 4

Rotated Factor Loadings for Supervisor (1), Facilitator (2), and Evaluator (3)

Q Sort      Factor 1          Factor 2          Factor 3

Supervisor      Facilitator      Evaluator

1             .05                 .74                 .07

2             .47                 .46                 .30

3             .13                 .60                 .24

4             .02                 -.13                .76

5             .51                 .26                 -.23

6             .60                 .25                 -.16

7             .18                 .48                 .03

8             .55                 .37                 .24

9             .54                 .17                 .13

10           .70                 .16                 .14

11           .53                 .17                 .34

12           .54               -.11                  .25

13           .22                 .48                 .16

14           .52                 .40                 -.04

15           .34                 .15                 .53

16           .41                 .13                 .19

17           .10                 .39                 .33

18           .19                 .32                 .47

19           .26                 .73                 .05

20           .27                 .04                 .12

21           .36                 .26                 .11

22           .13                 .40                 .54

23           .10                 .55                 .03

24           .20                 .39                 .50

25           .32                 .46                 .08

Note. Significant loading > .43 are in boldface



The data analysis revealed the existence of three different viewpoints (i.e., factors 1, 2, 3) on mentoring CEDS in graduate teaching. We named the factors Supervisor (F1), Facilitator (F2), and Evaluator (F3), respectively, and included those names in the factor interpretations below to best represent the distinguishing teaching mentorship characteristics of the groups of individuals associated with each factor. The resulting three factors accounted for 37% of the total variance in the correlation matrix. Note that sole reliance on statistical criteria, such as the proportion of variance, is discouraged in Q methodology. This is because a factor may hold theoretical interest and have contextual relevance that may be overlooked if only a statistical basis for interpreting subjective factors is used (Brown, 1980). Twenty of the 25 participants loaded significantly on one of the three factors. Factor loadings of > .43 were significant at the p < 0.01 level. Factor 1 had eight participants with significant loadings, accounting for 14% of the variance. Factor 2 had seven participants with significant loadings, accounting for 15% of the variance, whereas Factor 3 had five participants with significant loadings, accounting for 9% of the variance. Five of the 25 Q sorts were non-significant; four participants’ Q sorts were non-significant (X < .43) and one was confounded, meaning the factor scores for that participant were associated with more than one factor.

Table 5

48-Item Q Sample Factor Array With Factor Scores


  1            2            3

1 Viewing doctoral students’ life experiences as complementary to those of the faculty teaching mentor. -3 0 -1
2 Exposing doctoral students to progressively more challenging teaching roles with faculty  supervision. 0 0 3
3 Guiding doctoral students to complete a teaching practicum and/or internship as part of their doctoral training. 2 1 1
4 Sharing teaching resources with doctoral students (e.g., group activities, discussion prompts, assignments, etc.). -1 1 0
5 Maintaining a reputation among doctoral students as a quality teacher by modeling and  demonstrating quality teaching. 0 2 -1
6 Giving doctoral students examples from your own teaching on how to overcome teaching     challenges. 4 -3 -2
7 Having doctoral students rehearse teaching strategies (e.g., lectures, activities) prior to      implementing them in the classroom. -2 -3 -3
8 Defining for doctoral students their teaching roles in and out of the classroom. -1 -2 0
9 Modeling best practices in teaching to facilitate the development of doctoral students’ teaching styles. -1 1 -2
10 Having doctoral students facilitate portions of a course under supervision as part of co-teaching, a course assignment, and so forth. 3 3 1
11 Having doctoral students develop and discuss a teaching philosophy. 0 -2 2
12 Teaching doctoral students to develop rubrics and grade student assignments. -2 -1 0
13 Providing doctoral students with a safe space to acknowledge their teaching mistakes. 4 4 1
14 Assisting doctoral students with incorporating technology and course management systems (e.g., Blackboard) into the teaching process. -2 -2 -4
15 Holding doctoral students to high level of accountability regarding their teaching and learning practices. 0 0 4
16 Having doctoral students teach a portion of a class under faculty supervision. 2 3 1
17 Immersing doctoral students in teaching environments in a sink-or-swim manner with no advice, preparation, or supervision. -4 -4 -1
18 Having doctoral students co-teach an entire course with faculty members and/or experienced peers. 4 0 2
19 Providing strengths-based feedback and support regarding teaching. 0 4 0
20 Interacting with doctoral students as colleagues or equals. -3 3 -4
21 Teaching doctoral students to evaluate their teaching effectiveness and student learning. 1 1 4
22 Providing doctoral students with specific examples of how to address student issues. 3 -1 0
23 Acting as a “sounding board” when doctoral students need to discuss their feelings about   teaching. 0 3 -3
24 Promoting the creation of critical learning environments where doctoral students are asked to apply higher order cognitive skills (e.g., Bloom’s Taxonomy). -3 -2 4
25 Assisting doctoral students with identifying challenging student behaviors. 1 1 2
26 Encouraging doctoral students with teaching experience to engage in mentoring of their peers’ teaching. -4 -1 -3
27 Assisting doctoral students with preparing lectures, activities, and discussion topics. -2 -1 -2
28 Focusing on a broad range of learning and instructional theories when grounding one’s     teaching approach. -2 -3 2
29 Having doctoral students participate in a formal course on pedagogy. -1 -4 2
30 Encouraging doctoral students to implement refined teaching approaches after receiving      feedback from teaching mentors. 3 -1 1
31 Disclosing to doctoral students the ways that faculty members developed their teaching practice, including successes and mistakes. 2 1 -2
32 Supporting doctoral students’ solo teaching opportunities (e.g., to lead a class). 1 2 0
33 Providing both candid and immediate feedback to doctoral students about their teaching
2 0 0
34 Having doctoral students identify the verbal and nonverbal behaviors that contribute to
building teacher–student rapport.
-1 -1 -1
35 Nurturing professionalism in teaching during faculty–doctoral student interactions. -3 4 3
36 Talking to doctoral students about how their life experiences influence their approach to
-4 0 -1
37 Providing doctoral students with readings on pedagogy. 1 -4 2
38 Having doctoral students participate in designing a course. 2 0 -2
39 Having doctoral students observe faculty and experienced peers’ teaching. -1 -2 -1
40 Inviting doctoral students to discuss their clinical/school counseling experiences while in a teaching role in the classroom. 1 2 -3
41 Assisting doctoral students with developing a syllabus. 2 -1 -4
42 Planning before class with doctoral students before they engage in teaching activities. 1 -3 -2
43 Discussing boundaries and other ethical concerns regarding teaching. 0 0 3
44 Facilitating opportunities to improve doctoral students’ confidence and comfort about teaching. -1 2 -1
45 Helping doctoral students with understanding the variables and actions linked to an improved learning environment. -2 0 1
46 Assisting doctoral students with linking specific learning theories to course content/topic areas. 0 -3 1
47 Teaching doctoral students to remain empathic to students’ worldviews by using worldview-affirming language. 3 2 3
48 Discussing with doctoral students why instructional decisions were made in the classroom. 1 2 0

The three factors contain factor exemplars merged to form a single ideal Q sort for each factor, called a factor array (Watts & Stenner, 2012). The factor array, which contains the 48 Q sample items and the associated factor scores for Factors 1 through 3, is found in Table 5. The factor array contains factor scores calculated by weighted averages in which higher-loading Q sorts are given more weight in the averaging process because they better exemplify the factor. It is the factor scores contained in the factor array versus participants’ factor loadings that are used for factor interpretation. Note that parenthetical references to Q sample items and commensurate factor scores (e.g., item 24, +4) provide contextual reference for each of the factor interpretations below.

Factor 1: Supervisor

Eight (32%) of the 25 participants were associated with factor 1. Factor 1 mentors (i.e., Supervisors) view mentoring in teaching as a process that begins with CEDS co-teaching an entire course under the supervision of a faculty member or experienced peer (item 18, +4). Providing CEDS with real-world teaching examples from faculty members’ teaching experiences (item 6, +4) and a safe space to acknowledge teaching mistakes (item 13, +4) are defined as key mentoring processes for Factor 1. In so doing, Supervisors provide candid and immediate feedback about CEDS’ teaching performance (item 33, +2) and incorporate examples from their mentors’ own teaching successes and mistakes as part of the feedback (item 31, +2). These points are illustrated by one participant in her post–Q sort responses: “As a doctoral student, I appreciated receiving honest real-talk feedback (about teaching), which rarely happened. Now, when I mentor students, I tell folks what I really think in a kind but frank manner.” Supervisors encourage CEDS to implement refined teaching approaches after receiving candid feedback about their teaching. Additionally, Supervisors regularly plan before class with CEDS before they engage in teaching activities (item 42, +1). CEDS engage in syllabus development (item 41, +2) and course design (item 38, +2), versus sharing teaching resources (item 4, -1) and linking teaching variables to improved learning environments (item 45, -2), both of which are, as one participant remarked, “assumed to be part of the mentoring process.” Supervisors prefer that CEDS complete formal practica or internships as part of their doctoral training (item 3, +2).

Supervisors employ both formal (e.g., co-teaching, practica and internships, and regular pre-class planning) and informal (e.g., real-world examples, candid feedback, and appropriate professional disclosure about teaching) mentoring practices intended for students’ incremental professional development as teachers (Baltrinic et al., 2016). Supervisors’ teaching mentorship style is guided by the belief that experienced faculty members versus less-experienced peers are critical for influencing the development of doctoral students’ teaching skills (item 26, -4), more so than Factors 2 and 3. And, although Supervisors agree that no doctoral student should learn to teach in a sink-or-swim manner (item 17, -4), the Supervisor takes a less nurturing, or life experience–based approach to mentoring (items 1, -3; 35, -3; and 36, -4 respectively) than Factors 2 and 3. A less nurturing approach may be difficult to understand given the nature of mentoring itself. Keep in mind that what is central to Supervisors’ views on mentoring is the instructive and real-world supervision of students’ structured teaching activities over time, which does not preclude faculty members valuing students’ life experience or nurturing their development; rather, these are not central drivers for preferred mentoring interactions between faculty members and students.

Factor 2: Facilitator

Seven (28%) of the 25 participants agreed with Factor 2, which we have titled Facilitator. Facilitators are distinguished as mentors who nurture professionalism during faculty–student interactions (item 35, +4) and provide feedback and support using a strengths-based approach regarding CEDS’ teaching (item 19, +4). Similar to Supervisors (Factor 1), Facilitators provide CEDS with a safe space in the mentoring relationship to acknowledge teaching mistakes (item 13, +4). However, Facilitators favor providing supportive versus corrective or formal feedback (item 30, -1) as central to the mentoring relationship—described aptly by one participant as “I am not big on structured pedagogical teaching. In other words, modeling and supportive discussion can serve the mentor well.” It stands to reason that Facilitators prefer to maintain a reputation as a quality teacher by modeling and demonstrating best practices in teaching (item 5, +2), and thereby extend this practice to facilitate the development of CEDS’ teaching styles (item 9, +1). Accordingly, Facilitators do not approach mentoring in teaching by providing CEDS with formal readings on pedagogy, or have them participate in a formal course on pedagogy (items 29, -4 and 37, -4 respectively). Instead, Facilitators prefer to discuss with CEDS why they made teaching decisions in the classroom without being prescriptive (item 48, +2).

Facilitators approach mentoring by treating CEDS as colleagues or equals during the teaching experience (item 20, +3) and by creating opportunities for them to improve their comfort and confidence when teaching (item 44, +2). When providing feedback, Facilitators act as sounding boards for CEDS to express their feelings about teaching (item 23, +3). For example, noted in one participant’s post–Q sort response, “We learn the most through our own discomfort, so a mentor serving as a sounding board is very important.” Facilitators are more interested than Supervisors or Evaluators (Factor 3) in how CEDS’ life experiences influence their approach to teaching (item 36, 0). In the classroom, Facilitators invite CEDS to discuss their clinical or school counseling experiences when teaching (item 40, +2). In contrast with the Supervisor and the Evaluator, the Facilitator will share examples of their own teaching resources with CEDS (item 4, +1). In general, Facilitators prefer to have CEDS formally teach a portion of a class under their supervision (item 16, +3), versus having them co-teach an entire class or be thrown into teaching in a sink-or-swim manner (item 17, -4).

Facilitators avoid helping CEDS overcome teaching challenges through examples from their own teaching (item 6, -3) or by providing specific examples to address issues. Overall, Facilitators prefer not to define teaching roles for CEDS (item 8, -2), pre-plan specific activities before class (item 42, -3), provide particular learning theories to address specific course content (item 46, -3), or impose on the learning environment (item 28, -3). Finally, Facilitators do not prefer to provide CEDS with feedback that they should use to refine and subsequently implement during future teaching endeavors (item 30, -1), which is not surprising given the relational and discovery-oriented focus of this factor’s approach to mentoring in teaching.

Factor 3: The Evaluator

Factor 3, the Evaluator, included five (20%) of the 25 participants. Evaluators create a critical learning environment for CEDS to use higher order cognitive skills (item 24, +4) while helping them to evaluate their teaching effectiveness and student learning (item 21, +4). Additionally, Evaluators create a safe space for CEDS to acknowledge their mistakes (item 13, +1) and offer corrective feedback as a way for them to refine their teaching (item 30, +1). Unlike Facilitators in Factor 2, Evaluators do not interact with CEDS as colleagues or equals (item 20, -4), initiate conversations about students’ feelings (item 23, -3), or promote students’ confidence and comfort (item 44, -1) about teaching as a central part of mentorship. Instead, Evaluators come from a directive teaching perspective and place an emphasis on content-driven mentorship. Fittingly, Evaluators have high expectations of CEDS to learn and study critical components of teaching and guide students accordingly. Evaluators provide CEDS with readings on pedagogy (item 37, +2) and expose students to a range of learning and instructional theories (item 28, +2). Evaluators also place high value on CEDS taking a formal class on pedagogy (item 29, +2), distinguishing themselves from Supervisors and Facilitators, who rated teaching-related course work as less important.

Although Evaluators make students aware of ethical concerns while teaching (item 42, -2) and identify specific techniques linked to improved learning (item 45, +1), other pragmatic aspects of teaching are given less attention. For example, Evaluators place minimal importance on rubric development and grading practices (item 12, 0) and course design (item 38, -2), and even less importance on developing a syllabus (item 41, -4) and incorporating technology or course management systems into the teaching process (item 14, -4). This is a stark difference from Supervisors in Factor 1, who placed higher value on some of these responsibilities. And Supervisors emphasize skill development, whereas Evaluators stress creating a strong theoretical foundation to guide CEDS’ teaching tasks.

Classroom experiences, though secondary to learning theory and techniques, also are important aspects to mentorship for participants grouped in Factor 3. Evaluators supervise CEDS as they teach portions of courses (item 10, +1) or take on solo teaching opportunities (item 32, 0). In these circumstances, Evaluators hold CEDS to high levels of accountability in terms of their teaching and learning practices (item 15, +4), as opposed to their counterparts in Factors 1 and 2, who rate the importance of accountability more neutrally. One participant illustrates the importance of accountability: “I want doctoral students to know the how, what, and why of where they are going in the classroom, otherwise their students may end up somewhere else. Educators need to be responsible for accounting for students’ outcomes.” Offering feedback to improve teaching is a key aspect of the mentoring process for Evaluators as mentors and students evaluate these hands-on teaching experiences (item 30, +1). These experiences may be critical for Evaluators to assess CEDS’ learning and abilities, gradually exposing them to more challenging teaching roles (item 2, +3).

Throughout the mentorship process, Evaluators place CEDS’ learning and teaching practice at the center of interactions. Whereas Supervisors and Facilitators share their teaching experiences with CEDS, Evaluators avoid conversation about successes or mistakes in their teacher development (item 21, +4). Furthermore, Evaluators do not believe their reputations as quality teachers (item 5, -1) nor their modeling of best practices in teaching is relevant to CEDS’ development of teaching styles (item 9, -2). Instead, Evaluators keep themselves in a distant position during the course of mentorship. Key teaching mentorship interactions are characterized as student-centered and include discussion of their unique teaching philosophies (item 11, +2), exploration of the intentionality behind the instructional decisions they make in classrooms (item 48, 0), and evaluation of their teaching effectiveness (item 21, +4). Consequently, the mentorship style of Evaluators is directive but student-focused, with emphasis on mentees learning and reflecting upon various pedagogical theories and practices as they develop into teachers.


Three different perspectives (i.e., Supervisor, Facilitator, and Evaluator) exist among counselor educators of preferred ways to mentor CEDS in teaching. The three perspectives could be conceptualized as different styles of mentorship that are used by counselor educators. Although each perspective is unique, we noticed areas of agreement among counselor educators on using certain formal (e.g., co-teaching), informal (e.g. affirming worldviews), and combinations of mentoring approaches (Borders et al., 2011). These areas of agreement are similar to mentorship experiences in research with CEDS (Borders et al., 2012). The findings of this study also reinforce that mentoring is a complex process in which mentors fill a variety of roles and initiate multiple activities (Casto et al., 2005). Overall, results lend support for teaching mentorship also supported by the literature. For example, Silverman’s (2003) suggestions that learning about pedagogy, having teaching experiences, and working closely with an experienced mentor who facilitates pedagogical conversations are helpful for preparing future faculty members. Though the pairing procedures between participants and students were unknown (e.g., intentionally paired, general guidance; Borders et al., 2011), each factor in this study contained some combination of formal (e.g., planned readings or activities) and informal (e.g., in-the-moment conversations, minimal planning) approaches to mentoring, which is consistent with other findings on preparing CEDS to teach (Baltrinic et al., 2016).

Both career and psychosocial mentoring types are embodied within the three factors reported in the current study, the findings of which support and extend the work of Kram (1985) by providing examples specific to teaching mentorship styles. The Evaluator and the Supervisor perspectives contain career components, as they are knowledge and skill driven, respectively. The Facilitator perspective is reflective of Kram’s psychosocial type, as it is the most relational, exploratory, and insight-oriented perspective of the three. Though career and psychosocial properties overlap between factors (e.g., skill building, feedback, support), each mentoring perspective has one that is a central characteristic.

The combination of career and psychosocial (Kram, 1985) mentoring types evident in the results also are highlighted in other counselor education mentorship guidelines. Similar to the Association for Counselor Education and Supervision research mentorship model (Borders et al., 2012), participants noted the importance of mentors demonstrating and transferring teaching-oriented knowledge and skills to mentees, as well as providing constructive feedback. Other mentor characteristics and tactics, such as facilitating student self-assessment and accountability, modeling, and creating a supportive and open relationship (Black et al., 2004; Briggs & Pehrsson, 2008), are reflected in the current findings on teacher mentoring approaches. For some participants, maintaining a nurturing and supportive environment was of utmost importance, which also has been noted as essential for mentoring CEDS (Casto et al., 2005).

Borders et al. (2011) specifically noted the importance of mentoring graduate students who aspire to be faculty and, though minimally, addressed pedagogy support by offering teaching opportunities to students and engaging them in conversation about their experiences. The current research findings expand on Borders and colleagues’ position by providing ideas on what these conversations might entail. All three factors identified teacher-related topics of conversation and relevant activities, including teaching philosophies, skills, and tasks; pedagogical and learning theories; monitoring student interactions; classroom ethics and boundaries; and self-efficacy associated with teacher development. This offers some unique ideas on topics of interest that may be incorporated into conversations when mentoring students in teaching.

A practical component to teaching mentorships is represented within the factors. Rather than culminating in a product, such as co-written publications developed in research mentoring (Briggs & Pehrsson, 2008), each of the three teaching mentorship factors guide CEDS through applied teaching experiences. These hands-on teaching opportunities provided experiences for CEDS to work through and reflect upon, and offered material for mentors to provide feedback. The extent of student involvement in teaching varied, as did the direction of conversations (e.g., corrective, exploratory); nevertheless, some mentoring tasks were built from observable and enacted teaching moments.

Implications for Counselor Education Programs and Counselor Educators

We believe that it may be helpful for faculty members in positions of leadership (i.e., department chairs, doctoral program coordinators) in counselor education doctoral programs to infuse awareness of teaching mentorship practices among other faculty members. Senior counselor education faculty members responsible for coordinating doctoral programs may be able to create more impactful mentorship experiences for CEDS by encouraging other faculty members to become more aware of their mentorship practices. Several researchers have suggested that quality mentorship is associated with counselor education faculty members who demonstrate intentionality in their mentorship practices (Black et al., 2004; Casto et al., 2005). Findings from this study can generate discussion and self-assessment among faculty members, leading to a clearer understanding of different mentoring styles that exist within a department or program. As different mentoring styles are identified among faculty members, it may help to consider ways to match CEDS with faculty members who will be a good fit for their preferred learning style.

Similarly, we also believe that counselor educators mentoring CEDS in teaching can benefit from being reflective about their own style of mentorship. It may be helpful to consider one’s personal style of mentorship in relation to the styles of teaching mentorship (i.e., Supervisor, Facilitator, and Evaluator) highlighted in this study. Counselor educators who identify with a particular teaching mentorship style may discuss this with CEDS early in the mentorship process to facilitate a goodness of fit. In situations in which CEDS do not have the opportunity to select a mentor of their choosing, it may be particularly important for counselor educators to consider how their style of mentorship will fit with their mentee. It may help counselor educators identifying with a singular style of mentorship to integrate strengths from other styles of mentorship into their practice. For example, a counselor educator who closely identifies with the Supervisor style may benefit from increasing the amount of strength-based feedback they provide mentees (i.e., associated with the Facilitator), or by being more methodical about gradually increasingly their mentees exposure to challenging teaching experiences (i.e., associated with the Evaluator).

Limitations and Recommendations for Future Research

Q studies are not generalizable in the same way as other quantitative studies. The data in this study represent subjective perspectives; thus, results are viewed similar to qualitative studies (Watts & Stenner, 2012). However, Q results offer an additional rigor derived from the factor analysis of the participants’ respective Q sorts. Results from this study pertain to mentoring CEDS in aspects of pedagogy and not clinical teaching or clinical experiences. Future Q methodology studies can use purposeful samples of diverse particpants with a range of pedagogy and clinical teaching experiences, and use participants from a wider range of regions within the United States. Examining students’ and faculty members’ critical incidents during teaching mentorships may increase understanding of respective mentor and mentee perspectives. Future studies distinguishing teacher mentorship from research mentorship would be useful. Finally, investigating the specific practices of the three factor types through single-case studies could provide in-depth perspectives on faculty members’ teaching mentorship styles.


Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest or funding contributions for the development of this manuscript.


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Eric R. Baltrinic is an assistant professor at Winona State University. Randall M. Moate is an assistant professor at the University of Texas at Tyler. Michelle Gimenez Hinkle is an assistant professor at William Paterson University. Marty Jencius is an associate professor at Kent State University. Jessica Z. Taylor is an assistant professor at Central Methodist University. Correspondence can be addressed to Eric Baltrinic, Gildemeister 116A, P.O. Box 5838, 175 West Mark Street, Winona, MN 55987-5838, ebaltrinic@gmail.com.

An Exploration of Career Counselors’ Perspectives on Advocacy

Melissa J. Fickling

Advocacy with and on behalf of clients is a major way in which counselors fulfill their core professional value of promoting social justice. Career counselors have a unique vantage point regarding social justice due to the economic and social nature of work and can offer useful insights. Q methodology is a mixed methodology that was used to capture the perspectives of 19 career counselors regarding the relative importance of advocacy interventions. A two-factor solution was reached that accounted for 60% of the variance in perspectives on advocacy behaviors. One factor, labeled focus on clients, emphasized the importance of empowering individual clients and teaching self-advocacy. Another factor, labeled focus on multiple roles, highlighted the variety of skills and interventions career counselors use in their work. Interview data revealed that participants desired additional conversations and counselor training concerning advocacy.

Keywords: social justice, advocacy, career counselors, Q methodology, counselor training


The terms advocacy and social justice often are used without clear distinction. Advocacy is the active component of a social justice paradigm. It is a direct intervention or action and is the primary expression of social justice work (Fickling & Gonzalez, 2016; Ratts, Lewis, & Toporek, 2010; Toporek, Lewis, & Crethar, 2009). Despite the fact that counselors have more tools than ever to help them develop advocacy and social justice competence, such as the ACA Advocacy Competencies (Lewis, Arnold, House, & Toporek, 2002) and the Multicultural and Social Justice Counseling Competencies (Ratts, Singh, Nassar-McMillan, Butler, & McCullough, 2015), little is known about practitioners’ perspectives on the use of advocacy interventions.

One life domain in which social inequity can be vividly observed is that of work. The economic recession that began in 2007 has had a lasting impact on the labor market in the United States. Long-term unemployment is still worse than before the recession (Bureau of Labor Statistics, U.S. Department of Labor, 2016a). Further, in the United States, racial bias appears to impact workers and job seekers, as evidenced in part by the fact that the unemployment rate for Black workers is consistently about double that of White workers (e.g., 4.1% White unemployment and 8.2% Black unemployment as of May 2016; Bureau of Labor Statistics, U.S. Department of Labor, 2016b). Recent meta-analyses indicate that unemployment has a direct and causal negative impact on mental health, leading to greater rates of depression and suicide (Milner, Page, & LaMontagne, 2013; Paul & Moser, 2009). Clearly, the worker role is one that carries significant meaning and consequences for people who work or want to work (Blustein, 2006).

The rate at which the work world continues to change has led some to argue that worker adaptability is a key 21st century skill (Niles, Amundson, & Neault, 2010; Savickas, 1997), but encouraging clients to adapt to unjust conditions without also acknowledging the role of unequal social structures is inconsistent with a social justice paradigm (Stead & Perry, 2012). Career counselors, particularly those who work with the long-term unemployed and underemployed, witness the economic and psychological impact of unfair social arrangements on individuals, families and communities. In turn, they have a unique vantage point when it comes to social justice and a significant platform from which to advocate (Chope, 2010; Herr & Niles, 1998; Pope, Briddick, & Wilson, 2013; Pope & Pangelinan, 2010; Prilleltensky & Stead, 2012).

It appears that although career counselors value social justice and are aware of the effects of injustice on clients’ lives, they are acting primarily at the individual rather than the systemic level (Cook, Heppner, & O’Brien, 2005; McMahon, Arthur, & Collins, 2008b; Prilleltensky & Stead, 2012; Sampson, Dozier, & Colvin, 2011). Some research has emerged that focuses on practitioners’ use of advocacy in counseling practice (Arthur, Collins, Marshall, & McMahon, 2013; Arthur, Collins, McMahon, & Marshall, 2009; McMahon et al., 2008b; Singh, Urbano, Haston, & McMahan, 2010). Overall, this research indicates that advocacy is challenging and multifaceted and is viewed as a central component of good counseling work; however, more research is needed if we are to fully understand how valuing social justice translates to use of advocacy interventions in career counseling practice. This study aims to fill this theory–practice gap by illuminating the perceptions of advocacy behaviors from career counselors as they reflect upon their own counseling work.



Through the use of Q methodology, insight into the decisions, motivations and thought processes of participants can be obtained by capturing their subjective points of view. When considering whether to undertake a Q study, Watts and Stenner (2012) encouraged researchers to consider whether revealing what a population thinks about an issue really matters and can make a real difference. Given the ongoing inequality in the labor market, increased attention and energy around matters of social justice in the counseling profession, the lack of knowledge regarding practitioners’ points of view on advocacy, and career counselors’ proximity to social and economic concerns of clients, the answer for the present study is most certainly yes.

Q methodology is fundamentally different from other quantitative research methodologies in the social sciences. It uses both quantitative and qualitative data to construct narratives of distinct perspectives. The term Q was coined to distinguish this methodology from R; Q measures correlations between persons, whereas R measures trait correlations (Brown, 1980). Rather than subjecting a sample of research participants to a collection of measures as in R methodology, Q methodology subjects a sample of items (i.e., the Q sample) to measurement by a collection of individuals through a ranking procedure known as the Q sort (see Figure 1; Watts & Stenner, 2012). Individuals are the variables in Q methodology, and factor analysis is used to reduce the number of points of view into a smaller number of shared perspectives. Then interviews are conducted to allow participants to provide additional data regarding their rankings of the Q sample items. In this study, career counselors were asked to sort a set of advocacy behaviors according to how important they were to their everyday practice of career counseling. Importance to practice was used as the measure of psychological significance since career counselors’ perspectives on advocacy interventions were of interest, rather than self-reported frequency or competence, for example.


Q Sample

The Q sample can be considered the instrumentation in Q methodology. The Q sample is a subset of statements drawn from the concourse of communication, which is defined as the entire population of statements about any given topic (McKeown & Thomas, 2013). The goal when creating the Q sample is to provide a comprehensive but manageable representation of the concourse from which it is taken. For this study, the concourse was that of counselor advocacy behaviors.

The Q sampling approach used for this study was indirect, naturalistic and structured-inductive. Researchers should draw their Q sample from a population of 100 to 300 statements (Webler, Danielson, & Tuler, 2009). For this study, I compiled a list of 180 counselor social justice and advocacy behaviors from a variety of sources including the ACA Advocacy Competencies (Lewis et al., 2002), the Social Justice Advocacy Scale (SJAS; Dean, 2009), the National Career Development Association (NCDA) Minimum Competencies (2009), the Council for Accreditation of Counseling and Related Educational Programs (CACREP) Standards (2009), and key articles in counseling scholarly and trade publications.

Consistent with a structured-inductive sampling strategy, these 180 statements were analyzed to identify categories representing different kinds of advocacy behaviors. By removing duplicates and those items that were more aligned with awareness, knowledge or skill rather than behavior, I was able to narrow the list from 180 to 43 statements. These statements were sorted into five domains that were aligned with the four scales of the SJAS (Dean, 2009) and a fifth added domain. The final domains were: Client Empowerment, Collaborative Action, Community Advocacy, Social/Political Advocacy, and Advocacy with Other Professionals. Aligning the Q sample with existing domains was appropriate since advocacy had been previously operationalized in the counseling literature.

Expert reviewers were used to check for researcher bias in the construction of the Q sample, including the addition of the fifth advocacy domain. Three expert reviewers who were faculty members and published on the topic of social justice in career counseling were asked to review the potential Q sample for breadth, coverage, omissions, clarity of phrasing and the appropriateness of the five domains of advocacy. Two agreed to participate and offered their feedback via a Qualtrics survey, leading to a refined Q sample of 25 counselor advocacy behaviors (see Table 1). Five statements were retained in each of the five domains. Finally, the Q sample and Q sorting procedure were piloted with two career counselors, leading to changes in instructions but not in the Q sample itself. Pilot data were not used in the final analysis.



In Q methodology, participant sampling should be theoretical and include the intentional selection of participants who are likely to have an opinion about the topic of interest (McKeown & Thomas, 2013; Watts & Stenner, 2012). It also is important to invite participants who represent a range of viewpoints and who are demographically diverse. For the current study, the following criteria were required for participant inclusion: (a) holds a master’s degree or higher in counseling and (b) has worked as a career counselor for at least one year full-time in the past two years. For this study, career counselor was defined as having career- or work-related issues as the primary focus of counseling in at least half of the counselor’s case load. Regarding the number of participants in a Q study, emphasis is placed on having enough participants to establish the existence of particular viewpoints, not simply having a large sample since generalizability is not a goal of Q methodology (Brown, 1980). In Q methodology, it also is important to have fewer participants than Q sample items (Watts & Stenner, 2012; Webler et al., 2009).

Participants were recruited by theoretical sampling of my professional network of practitioners, and one participant was recruited through snowball sampling. Nineteen career counselors participated in the present study from six states in the Southeast, West and Midwest regions of the United States. The participant sample was 68% female (n = 13) and 32% male (n = 6); the sample was 84% White and included two Black participants and one multi-racial participant. One participant was an immigrant to the United States and was a non-native English speaker. The participant sample was 95% heterosexual with one participant identifying as gay. Sixty-three percent of participants worked in four-year institutions of higher education and one worked in a community college. Thirty-two percent (n = 6) provided career counseling in non-profit agencies. The average age was 43 (SD = 12) and the average number of years of post-master’s counseling experience was eight (SD = 7); ages ranged from 28 to 66, and years of post-master’s experience ranged from one and a half to 31 years.


Q Sorting Procedure

The Q sort is a method of data collection in which participants rank the Q sample statements according to a condition of instruction along a forced quasi-normal distribution (see Figure 1). There is no time limit to the sorting task and participants are able to move the statements around the distribution until they are satisfied with their final configuration. The function of the forced distribution is to encourage active decision making and comparison of the Q sample items to one another (Brown, 1980).


Figure 1

Sample Q Sort Distribution

The condition of instruction for this study was, “Sort the following counselor advocacy behaviors according to how important or unimportant they are to your career counseling work.” The two poles of the distribution were most important and most unimportant. Poles range from most to most so that the ends of the distribution represent the areas that hold the greatest degree of psychological significance to the participant, and the middle of the distribution represents items that hold relatively little meaning or are more neutral in importance (Watts & Stenner, 2012).

The Q sorts for this study were conducted both in person and via phone or video chat (i.e., Google Hangouts, Skype). Once informed consent was obtained, I facilitated the Q sorting procedure by reading the condition of instruction, observing the sorting process, and conducting the post-sort interview. Once each participant felt satisfied with his or her sort, the distribution of statements was recorded onto a response sheet for later data entry.


Post-Sort Interview

Immediately following the Q sort, I conducted a semistructured interview with each participant in order to gain a greater understanding of the meaning of the items and their placement, as well as his or her broader understanding of the topic at hand (Watts & Stenner, 2012). The information gathered during the interview is used when interpreting the final emergent factors. Items in the middle of the distribution are not neglected and are specifically asked about during the post-sort interview so that the researcher can gain an understanding of the entire Q sort for each participant. Although the interview data are crucial to a complete and rigorous factor interpretation and should be conducted with every participant in every Q study, the data analysis process is guided by the quantitative criteria for factor analysis and factor extraction. The qualitative interview data, as well as the demographic data, are meant to help the researcher better understand the results of the quantitative analysis.


Data Analysis

Data were entered into the PQMethod program (Schmolck, 2014) and Pearson product moment correlations were calculated for each set of Q sorts. Inspection of the correlation matrix revealed that all sorts (i.e., all participants) were positively correlated with one another, some of them significantly so. This indicated a high degree of consensus among the participants regarding the role of advocacy in career counseling, which was further explored through factor analysis.

I used centroid factor analysis and Watts and Stenner’s (2012) recommendation of beginning by extracting one factor for every six Q sorts. Centroid factor analysis is the method of choice among Q methodologists because it allows for a fuller exploration of the data than a principal components analysis (McKeown & Thomas, 2013; Watts & Stenner, 2012). Next, I calculated the significance level at p < .01, which was .516 for this 25-item Q sample.

The unrotated factor matrix revealed two factors with Eigenvalues near or above the commonly accepted cutoff of 1 according to the Kaiser-Guttman rule (Kaiser, 1970). Brown (1978) argued that although Eigenvalues often indicate factor strength or importance, they should not solely guide factor extraction in Q methodology since “the significance of Q factors is not defined objectively (i.e., statistically), but theoretically in terms of the social-psychological situation to which the emergent factors are functionally related” (p. 118). Since there currently is little empirical evidence of differing perspectives on advocacy among career counselors, two factors were retained for rotation.

In order to gain another perspective on the data, I used the Varimax procedure. I flagged those sorts that loaded significantly (i.e., at or above 0.516) onto only one factor after rotation. Four participants (2, 8, 9 and 17) loaded significantly onto both rotated factors and were therefore dropped from the study and excluded from further analysis (Brown, 1980; Watts & Stenner, 2012). Two rotated factors were retained, which accounted for 60% of the variance in perspectives on advocacy behaviors. Fifteen of the original 19 participants were retained in this factor solution.

Q methodology uses only orthogonal rotation techniques, meaning that all factors are zero-correlated. Even so, it is possible for factors to be significantly correlated but still justify retaining separate factors (Watts & Stenner, 2012). The two factors in this study are correlated at 0.71. This correlation indicates that the perspectives expressed by the two factor arrays share a point of view but are still distinguishable and worthy of exploration as long as the general degree of consensus is kept in mind (Watts & Stenner, 2012).


Constructing Factor Arrays

After the two rotated factors were identified, factor arrays were constructed in PQMethod. A factor array is a composite Q sort and the best possible estimate of the factor’s viewpoint using the 25 Q sample items. First, a factor weight was calculated for each of the 15 Q sorts that loaded onto a factor. Next, normalized factor scores (z scores) were calculated for each statement on each factor, which were finally converted into factor arrays (see Table 1). In Q methodology, unlike traditional factor analysis, attention is focused more on factor scores than factor loadings. Since factor scores are based on weighted averages, Q sorts with higher factor loadings contribute proportionally more to the final factor score for each item in a factor than those with relatively low factor loadings. Finally, factors were named by examining the distinguishing statements and interview data of participants that loaded onto the respective factors. Factor one was labeled focus on clients and factor two was labeled focus on multiple roles.


Factor Characteristics

Factor one was labeled focus on clients and accounted for 32% of the variance in perspectives on advocacy behaviors. It included nine participants. The demographic breakdown on this factor was: six females, three males; eight White individuals and one person who identified as multi-racial. The average age on this factor was about 51 (SD = 10.33), ranging from 37 to 66. Persons on this factor had on average 11 years of post-master’s counseling experience (SD = 8.6), ranging from one and a half to 31 years. Fifty-six percent of participants on this factor worked in 4-year colleges or universities, 33% in non-profit agencies, and one person worked at a community college.

Factor two was labeled focus on multiple roles and accounted for 28% of the variance in career counselors’ perspectives on advocacy behaviors. It included six participants. Five participants on this factor identified as female and one identified as male. Five persons were White; one was Black. The average age of participants on this factor was almost 35 (SD = 6.79), ranging from 29 to 48, and they had an average of just over seven years of post-master’s experience (SD = 3.76), ranging from three and a half to 14 years. Four worked in higher education, and two worked in non-profit settings.


Factor Interpretation

In the factor interpretation phase of data analysis, the researcher constructs a narrative for each factor by incorporating post-sort interview data with the factor arrays to communicate the rich point of view of each factor (Watts & Stenner, 2012). Each participant’s interview was considered only in conjunction with the other participants on the factor on which they loaded. I read post-sort interview transcripts, looking for shared perspectives and meaning, in order to understand each factor array and enrich each factor beyond the statements of the Q sample. Thus, the results are reported below in narrative form, incorporating direct quotes and paraphrased summaries from interview data, but structured around the corresponding factor arrays.

Table 1

Q Sample Statements, Factor Scores and Q Sort Values



Factor 1

Factor 2

Factor Score


Factor Score


1 Question intervention practices that appear inappropriate.





2 Seek feedback regarding others’ perceptions of my advocacy efforts.





3 Serve as a mediator between clients and institutions.





4 Express views on proposed bills that will impact clients.





5 Maintain open dialogue to ensure that advocacy efforts are consistent with group goals.





6 Encourage clients to research the laws and policies that apply to them.





7 Collect data to show the need for change in institutions.





8 Educate other professionals about the unique needs of my clients.





9 Help clients develop needed skills.





10 Assist clients in carrying out action plans.





11 Help clients overcome internalized negative stereotypes.





12 Conduct assessments that are inclusive of community members’ perspectives.





13 With allies, prepare convincing rationales for social change.





14 Identify strengths and resources of clients.





15 Get out of the office to educate people about how and where to get help.





16 Teach colleagues to recognize sources of bias within institutions and agencies.





17 Deal with resistance to change at the community/system level.





18 Collaborate with other professionals who are involved in disseminating public information.





19 Help clients identify the external barriers that affect their development.





20 Use multiple sources of intervention, such as individual counseling, social advocacy and case management.





21 Train other counselors to develop multicultural knowledge and skills.





22 Work to ensure that clients have access to the resources necessary to meet their needs.





23 Work to change legislation and policy that negatively affects clients.





24 Ask other counselors to think about what social change is.





25 Communicate with my legislators regarding social issues that impact my clients.





Note. Q sort values are -4 to 4 to correspond with the Q distribution (Figure 1) where 4 is most important
and -4 is most unimportant; QSV = Q Sort Value.




Factor 1: Focus on Clients

For participants on the focus on clients factor, the most important advocacy behavior was to “identify client strengths and resources” (see Table 1). When speaking about this item, participants often discussed teaching clients self-advocacy skills, stating that this is a key way in which career counselors promote social justice. Identifying client strengths and resources was referred to as “the starting point,” “the bottom line” and even the very “definition of career counseling.” One participant said that counseling is about “empowering our clients or jobseekers, whatever we call them, to do advocacy on their own behalf and to tell their story.” In general, persons on this factor were most concerned with empowering individual clients; for example, “I would say, even when we’re doing group counseling and family counseling, ultimately it’s about helping the person in the one-to-one.” Similarly, one participant said, “Instead of fighting for the group in legislation or out in the community, I’m working with each individual to help them better advocate for themselves.” Interview data indicated that social justice was a strongly held value for persons on this factor, but they typically emphasized the need for balancing their views on social injustice with their clients’ objectives; they wanted to take care not to prioritize their own agendas over those of their clients.

Several participants on this factor perceived items related to legislation or policy change as among the least client-centered behaviors and therefore as the more unimportant advocacy behaviors in their career counseling work. Persons on this factor stated that advocacy at the systems level was neither a strength of theirs nor a preference. A few reported that there are other people in their offices or campuses whose job is to focus on policy or legislative change. There also was a level of skepticism about counselors’ power to influence social change. In regard to influencing legislative change in support of clients, one participant said, “I don’t think in my lifetime that is going to happen. Maybe someday it will. I’m just thinking about market change right now instead of legislative change.”

Interview data revealed that career counselors on this factor thought about advocacy in terms of leadership, both positively and negatively. One person felt that a lack of leadership was a barrier to career counselors doing more advocacy work. Another person indicated that leaders were the ones who publicly called for social change and that this was neither his personality nor approach to making change, preferring instead to act at the micro level. Finally, persons on this factor expressed that conversations about social change or social justice were seen as potentially divisive in their work settings. One White participant said the following:

There is a reluctance to do social justice work because—and it’s mostly White people—people really don’t understand what it means, or feel like they don’t have a right to do that, or feel like they might be overstepping. Talking about race or anything else, people are really nervous and they don’t want to offend or say something that might be wrong, so as a result they just don’t engage on that level or on that topic.


Factor 2: Focus on Multiple Roles

One distinguishing feature of the focus on multiple roles factor was the relatively high importance placed on using multiple sources of intervention (see Table 1). Participants described this as being all-encompassing of what a career counselor does and reflective of the multiple roles a career counselor may hold. One participant said, “You never know what the client is going to come in with,” arguing that career counselors have to be open to multiple sources of intervention by necessity. Another participant indicated that she wished she could rely more on multiple sources of intervention but that the specialized nature of her office constricted her ability to do so.

Participants on this factor cited a lack of awareness or skills as a barrier to their implementing more advocacy behaviors. They were quick to identify social justice as a natural concern of career counselors and one that career counselors are well qualified to address due to their ability to remain aware of personal, mental health and career-related concerns simultaneously. One participant said:

I don’t know if the profession of career counseling is really seen as being as great as it is in that most of us have counseling backgrounds and can really tackle the issues of career on a number of different levels.

In talking about the nature of career counseling, another participant said, “Social justice impacts work in so many ways. It would make sense for those external barriers to come into our conversations.”

Regarding collaborating with other professionals to prepare convincing rationales for social change, one participant stated that there are already enough rationales for social change; therefore, this advocacy behavior was seen as less important to her. Persons on this factor placed relatively higher importance on valuing feedback on advocacy efforts than did participants on factor one. One participant said she would like to seek feedback more often but had not thought of doing so in a while: “I did this more when I was in graduate school because you are thinking about your thinking all the time. As a practitioner, as long as social justice and advocacy are on my radar, that’s good.”



Neither setting nor gender appeared to differentiate the factors, but age and years of post-master’s experience may have been distinguishing variables. Younger individuals and those with fewer years of post-master’s experience tended to load onto factor two. Factor one had an average age of 51 compared to 35 for factor two, and the average age for all study participants was 43. It is interesting to note that the four participants who loaded onto both factors and were therefore dropped from analysis had an average of just over two years of post-master’s counseling experience versus 11 for factor one and seven for factor two. It is possible that their more recent training regarding advocacy may account for some differences in perspective from those of more experienced counselors.

Participants on factor one (focus on clients) who emphasized the importance of individual clients tended to perceive it as more difficult to have conversations about social justice with their peers or supervisors. In contrast, participants on factor two (focus on multiple roles) were more likely to cite a lack of knowledge or skills regarding their reasons for not engaging in more advocacy behaviors beyond the client level. Factor arrays indicated that factor one participants viewed engaging at the community level as more important, whereas participants on factor two viewed conversations with colleagues and clients about social justice as more important to their work.

The broader view of persons on factor two regarding the career counselor’s role and their openness to acknowledging their own lack of awareness or skills may reflect a different kind of socialization around advocacy compared to persons on factor one. Career counselors who graduated from counseling programs prior to the emphasis on multicultural competence in the early 1990s or before the inclusion of social justice in the literature and CACREP standards in the first decade of the 21st century may have had limited exposure to thinking about contextual or social factors that impact client wellness. Persons on both factors, however, expressed interest in social justice and felt that the vast majority of advocacy behaviors were important.

In post-sort interviews, participants from both factors described a gradual shift in emphasis from a focus on the individual on the right hand (most important) side of the Q sort distribution to an emphasis on legislation on the left hand (most unimportant) side. For example, the statement identify strengths and resources of clients was one of the most important behaviors for nearly every participant. Likewise, the statement work to change legislation and policy that negatively affects clients was ranked among the most unimportant advocacy behaviors for both factors. Interestingly, the statement encourage clients to research the laws and policies that apply to them was a consensus statement with a Q sort value of 0, or the very middle of the distribution. Since this advocacy behavior is both client focused and presumably would provide clients with important self-advocacy skills, it is interesting that it was ranked lower than other items related to client self-advocacy. Some participants indicated that they considered this item a “passive” counselor behavior in that they might encourage clients to research laws but could not or would not follow up with clients on this task. One participant said she would like to encourage clients to research laws that apply to them but shared that she would first need to learn more about the laws that impact her clients in order to feel effective in using this intervention.

Participants were asked directly about potential barriers to advocacy and potential strengths of career counselors in promoting social justice. Responses are discussed below. The questions about strengths and barriers in the post-sort interview did not reference Q sample items, so participant responses are reported together below.


Barriers to Promoting Social Justice

In the post-sort interviews, lack of time was mentioned by nearly every participant as a barrier to implementing more advocacy in career counseling, and it often came in the form of little institutional support for engaging in advocacy. For example, participants indicated that while their supervisors would not stop them from doing advocacy work, they would not provide material support (e.g., time off, reduced case load) to do so. This finding is consistent with other literature that suggests that career counselors report a lack of institutional support for engaging in advocacy (Arthur et al., 2009).

Another major barrier to advocacy was a lack of skill or confidence in one’s ability as an advocate. Advocacy at the social/political level requires a unique set of skills (M. A. Lee, Smith, & Henry, 2013), which practitioners in the present study may or may not have learned during their counseling training. Pieterse, Evans, Risner-Butner, Collins, and Mason (2009) reviewed 54 syllabi from required multicultural courses in American Psychological Association (APA)- and CACREP-accredited programs and found that awareness and knowledge tended to be emphasized more than skill building or application of social justice advocacy. This seems to have been reflected in the responses from many participants in the present study.

Participants on both factors indicated that they held some negative associations to advocacy work, calling it “flag waving” or “yelling and screaming” about inequality or social issues. They expressed some concern about how they might be perceived by their peers if they were to engage in advocacy; however, involvement in this study seemed to provide participants with a new understanding of advocacy as something that happens at the individual as well as at the social level. Participants appeared to finish the data collection sessions with a more positive understanding of what advocacy is and could be.


Strengths of Career Counselors in Promoting Social Justice

In addition to discussing barriers to advocacy, participants were asked directly about strengths of career counselors in promoting social justice and were able to identify many. First and foremost, participants saw the ability to develop one-on-one relationships with clients as a strength. One participant nicely captured the essence of all responses in this area by stating, “The key thing is our work one-on-one with an individual to say that even though you’re in a bad place, you have strengths, you have resources, and you have value.” Participants indicated that social change happens through a process of empowering clients, instilling hope and seeing diversity as a strength of a client’s career identity. The ability to develop strong counseling relationships was attributed partially to participants’ counseling training and identity, as well as to their exposure to a broad range of client concerns due to the inseparable nature of work from all other aspects of clients’ lives (Herr & Niles, 1998; Tang, 2003).

Career counselors in this study served diverse populations and highly valued doing so. These participants described multicultural counseling skills and experience as central to competent career counseling and to advocacy. They felt that they possessed and valued multicultural competence, which bodes well for their potential to engage in competent and ethical advocacy work with additional training, experience and supervision (Crook, Stenger, & Gesselman, 2015; Vespia, Fitzpatrick, Fouad, Kantamneni, & Chen, 2010).

Finally, participants felt that career counseling is seen as more accessible than mental health counseling to some clients, giving career counselors unique insight into clients’ social and personal worlds. Participants reported having a broad perspective on their clients’ lives and therefore unique opportunities to advocate for social justice. Relatedly, participants noted that the more concrete and tangible nature of career counseling and its outcomes (e.g., employment) may lead policymakers to be interested in hearing career counselors’ perspectives on social issues related to work. One participant noted that “there’s a huge conversation to be had around work and social justice” and that career counselors’ key strength “is empowering clients and the broader community to understand the role of work.”


Implications for Career Counselors, Counselor Educators, and Supervisors

Nearly all participants described the sorting process as thought provoking and indicated that social justice and advocacy were topics they appreciated the opportunity to think more about. There was a strong desire among some practitioners in this study to talk more openly with colleagues about social justice and its connection to career counseling, but a lingering hesitation as well. Therefore, one implication of the present study is that practitioners should begin to engage in discussions about this topic with colleagues and leaders in the profession. If there is a shared value for advocacy beyond the individual level, but time and skills are perceived as barriers, perhaps a larger conversation about the role of career counselors is timely. Career counselors may benefit from finding like-minded colleagues with whom to talk about social justice and advocacy. Support from peers may help practitioners strategize ways to question or challenge coworkers who may be practicing career counseling in ways that hinder social justice.

To move toward greater self-awareness and ethical advocacy, practitioners and career counseling leaders must ask themselves critical and self-reflexive questions about their roles and contributions in promoting social justice (McIlveen & Patton, 2006; Prilleltensky & Stead, 2012). Some authors have indicated there is an inherent tension in considering a social justice perspective and that starting such conversations can even lead to more questions than answers (Prilleltensky & Stead, 2012; Stead & Perry, 2012). Counselors should turn their communication skills and tolerance for ambiguity inward and toward one another in order to invite open and honest conversations about their role in promoting social justice for clients and communities. The participants in this study seem eager to do so, though leadership may be required to get the process started in a constructive and meaningful way.

Counselor educators and supervisors can provide counselors-in-training increased experience with systemic-level advocacy by integrating the ACA Advocacy Competencies and the Multicultural and Social Justice Counseling Competencies into all core coursework. Even though broaching issues of social justice has been reported as challenging and potentially risky, counselor educators should integrate such frameworks and competencies in active and experiential ways (Kiselica & Robinson, 2001; M. A. Lee et al., 2013; Lopez-Baez & Paylo, 2009; Manis, 2012). Singh and colleagues (2010) found that even self-identified social justice advocates struggled at times with initiating difficult conversations with colleagues; they argued that programs should do more to help counselors-in-training develop skills “to anticipate and address the inevitable interpersonal challenges inherent in advocacy work” (p. 141). Skills in leadership, teamwork and providing constructive feedback might be beneficial to prepare future counselors for addressing injustice. Furthermore, Crook and colleagues (2015) found that advocacy training via coursework or workshops is associated with higher levels of perceived advocacy competence among school counselors, lending more support in favor of multi-level training opportunities.



The current study is one initial step in a much-needed body of research regarding advocacy practice in career counseling. It did not measure actual counselor engagement in advocacy, which is important to fully understand the current state of advocacy practice; rather, it measured perceived relative importance of advocacy behaviors. Researcher subjectivity may be considered a limitation of this study, as researcher decisions influenced the construction of the Q sample, the factor analysis and the interpretation of the emergent factors. By integrating feedback from two expert reviewers during construction of the Q sample, I minimized the potential for bias at the design stage. Factor interpretation is open to the researcher’s unique lens and also may be considered a limitation, but if it is done well, interpretation in Q methodology should be constrained by the factor array and interview data. Although generalizability is not a goal of Q methodology, the sample size in this study is small and therefore limits the scope of the findings.


Suggestions for Future Research and Conclusion

Advocacy is central to career counseling’s relevance in the 21st century (Arthur et al., 2009; Blustein, McWhirter, & Perry, 2005; McMahon, Arthur, & Collins, 2008a), yet due to the complexity and personal nature of this work, more research is required if we are to engage in advocacy competently, ethically and effectively. There appears to be interest among career counselors in gaining additional skills and knowledge regarding advocacy, so future research could include analyzing the effects of a training curriculum on perceptions of and engagement with advocacy. Outcome research could also be beneficial to understand whether career counselors who engage in high levels of advocacy report different client outcomes than those who do not. Finally, research with directors of career counseling departments could be helpful to understand what, if any, changes to career counselors’ roles are possible if career counselors are interested in doing more advocacy work. Understanding the perspectives of these leaders could help further the conversation regarding the ideals of social justice and the reality of expectations and demands faced by career counseling offices and agencies.

This research study is among the first to capture U.S. career counselors’ perspectives on a range of advocacy behaviors rather than attitudes about social justice in general. It adds empirical support to the notion that additional conversations and training around advocacy are wanted and needed among practicing career counselors. Stead (2013) wrote that knowledge becomes accepted through discourse; it is hoped that the knowledge this study produces will add to the social justice discourse in career counseling and move the profession toward a more integrated understanding of how career counselors view the advocate role and how they can work toward making social justice a reality.



Conflict of Interest and Funding Disclosure

The author conducted this research with the assistance of grants awarded by the National Career Development Association, the North Carolina Career Development Association, and the Southern Association for Counselor Education and Supervision.



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Melissa J. Fickling, NCC, is an Assistant Professor at the University of Memphis. Correspondence can be addressed to Melissa J. Fickling, University of Memphis, Ball Hall 100, Memphis, TN 38152, mfckling@memphis.edu.