TPC _Journal-Vol6_Issue_3-MTSS-Full_Issue

The Professional Counselor /Volume 6, Issue 3 280 accountable for showing gains in these areas in addition to academic areas. A construct-based approach to school counseling. Squier, Nailor, and Carey (2014) extensively reviewed the educational and developmental psychology literature to determine what capabilities are strongly related to students’ academic achievement and later success in life. The authors intentionally chose lines of research connected to student competencies in the academic, personal/social and career domains that comprise the school counseling ASCA (2012) National Model. Squier and colleagues (2014) established four overarching constructs that explicitly link to student success: (a) motivation, the forces that compel action and direct the behavior of individuals; (b) self-knowledge, the understanding that people have about their own abilities, values, preferences and skills and a necessary precondition for effective self-regulation; (c) self-direction, being able to identify one’s own life directions, to make academic choices consistent with these directions and to connect classroom learning to life goals; and (d) relationships, the ability to establish and maintain productive, collaborative, social relationships with teachers and peers. These four constructs have been shown to be strongly associated with students’ academic achievement and well-being; they also are considered to be malleable, receptive to intervention and within the range of expertise of school counselors (Bass, Lee, Wells, Carey, & Lee, 2015). Multi-Tiered System of Supports Use of MTSS is the recommended process for assessing and potentially intervening with an array of academic, behavioral and social-emotional issues while promoting schoolwide systems change (Lane, Menzies, Ennis, & Bezdek, 2013). An MTSS approach aligns closely with the ASCA (2012) National Standards and the work of school counselors in implementing prevention-based initiatives at a schoolwide level while providing more targeted intervention-based supports for students in need. It should be noted that MTSS is neither overly prescriptive nor rigid and has varying implementations and utility based on school districts’ needs. Schools use MTSS to approach issues within the student population in tiers and place students in such tiers in order to appropriately address their needs. For example, the primary tier refers to a universal intervention geared toward the general student body, whose members may not be faced with distinct difficulty, thereby focusing on prevention to reduce potential problems (Horner, Sugai, & Anderson, 2010). The secondary tier refers to interventions for at-risk students, which typically involve more small group-based and individual interventions for those students still demonstrating difficulty after receiving primary intervention and support (Horner et al., 2010). The tertiary tier refers to working with students who are faced with identified difficulties and have not responded efficiently to primary or secondary levels and are subsequently in need of significant school- and community-based supports (Horner et al., 2010). An MTSS approach can be conceptualized as incorporating elements of Response to Intervention (RTI) and Positive Behavioral Interventions and Supports (PBIS; Sugai & Horner, 2009). While RTI brings forth opportunities for preventative approaches and early intervention for students struggling with academic skills (Sandomierski, Kincaid, & Algozzine, 2007), MTSS incorporates a broader focus on both academic and social-emotional matters. Within the PBIS framework, the primary focus is on promoting consistent behavior expectations and systems of support to incentivize behaviors of all students within a school (Bohanon, Fenning, Eber, & Flannery, 2007). Both RTI and PBIS utilize MTSS, and specifically tiered intervention delivery, to accommodate the range of student needs. These frameworks are closely aligned in regards to their prevention foci, problem solving, implementation fidelity and data-based decision making (Sugai & Horner, 2009).