Publication Date

Spring 2026

Presentation Length

15 minutes

College

College of Education

Department

Education, Department of

Student Level

Graduate

Faculty Mentor

Ryan D. Fox

Metadata/Fulltext

Fulltext

Presentation Type

Talk/Oral

Summary

Abstract

This conceptual study introduces the Instructional Feedback for Inclusive Struggle (IFIS) framework, a model designed to address inequities experienced by learners with disabilities in compressed-pacing mathematics classes (CPMC). Although accelerated formats such as the 4x4 instructional block schedule are intended to deepen engagement, research shows that opportunities for sense-making, reflection, and productive struggle are often limited due to time constraints (Allen Queen et al., 1997; Cooke, 2023; Young et al., 2024). IFIS responds to these challenges by integrating three foundational theories: Vygotsky’s (1978) Zone of Proximal Development (ZPD), which emphasizes cognitive support; Universal Design for Learning (UDL), which foregrounds accessibility, representation, and flexibility (Boysen, 2024); and the Rights of the Learner (RoTL), which affirms students’ autonomy and identities (Kalinec-Craig, 2017). Through a conceptual synthesis of equity-driven mathematics research, inclusive feedback practices, and humanizing approaches for learners with disabilities, IFIS positions feedback as a multidimensional tool that sustains rigor while cultivating agency, authority, and belonging (Lambert et al., 2018; Murdoch et al., 2020). The framework highlights strategies such as cognitive scaffolding, problem-based learning, and visual supports as actionable methods for maintaining cognitive demand and promoting equitable participation in general education CPMC (Tarmizi & Bayat, 2012; Tharp & Gallimore, 1991; van Zee & Minstrell, 1997). This work offers leaders and educators an accessible model for embedding inclusive feedback practices in CPMC as an equity mechanism to transform productive struggle into an inclusive, identity-affirming experience for all learners (Lynch et al., 2018; NCTM, 2014).

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