Designing Inclusive Learning Experiences to Reduce Dropout Rates in Emirati Foundation Programs



Author Information

Maha Alameri, Higher Colleges of Technology, United Arab Emirates

Abstract

Foundation programs in the United Arab Emirates (UAE) represent a critical transition stage between secondary and higher education, yet early academic disengagement and withdrawal remain persistent concerns. This study examines how intentionally designed inclusive learning experiences can enhance student engagement, academic performance, and retention among first-year Emirati students in foundation-level English courses. Grounded in principles of Universal Design for Learning (Meyer et al., 2014), constructivist learning theory (Vygotsky, 1978), and research on student retention and engagement (Tinto, 2012), the study investigates the impact of early diagnostic assessment, differentiated instruction, structured collaborative learning, and scaffolded formative feedback implemented over one academic semester. A mixed-method classroom-based inquiry was conducted using attendance patterns, assessment performance data, withdrawal trends, and student perception surveys. Findings indicate improved attendance consistency, narrowed performance gaps across proficiency levels, increased learner confidence and a measurable decline in withdrawal rates compared to previous cohorts. Students reported greater clarity of expectations, stronger academic belonging, and reduced assessment anxiety when provided with structured support and iterative feedback opportunities. The study argues that dropout prevention is closely linked to classroom-level instructional design rather than student deficit. By embedding inclusive pedagogical practices that anticipate learner diversity, educators can transform transitional learning environments into supportive academic spaces that promote persistence, engagement and resilience within foundation programs across the UAE.


Paper Information

Conference: PCE2026
Stream: Teaching Experiences

This paper is part of the PCE2026 Conference Proceedings (View)
Full Paper
View / Download the full paper in a new tab/window


Comments & Feedback

Place a comment using your LinkedIn profile

Comments

Share on activity feed

Powered by WP LinkPress

Share this Research

Posted by James Alexander Gordon