EVALUATING THE EFFECTIVENESS OF AI-GENERATED, CONTEXT-SPECIFIC CASE STUDIES IN IMPROVING CRITICAL THINKING SKILLS IN ODL

Abstract

The advancement of artificial intelligence (AI) in education has created new opportunities to enhance learner-centered pedagogies, particularly in open and distance learning (ODL) systems where geographic, cultural, and infrastructural challenges often limit instructional effectiveness. Critical thinking, defined as the ability to analyze, evaluate, and synthesize information for evidence-based judgment and problem-solving, remains a central educational outcome and a global competency emphasized by higher education frameworks. Case-based learning has long been recognized as an effective approach for fostering critical thinking; however, static case materials often lack contextual relevance and adaptability for diverse learner populations in ODL contexts. This study investigated the effectiveness of AI-generated, context-specific case studies in improving critical thinking skills among Bangladeshi ODL learners. A quasi-experimental design was employed with pre-test and post-test measures administered to an experimental group (n = 100) and a control group (n = 100). The experimental group interacted with AI-generated cases designed to provide personalization, authenticity, adaptive feedback, and active engagement, while the control group studied traditional instructor-developed case materials. Findings revealed significant improvements in the experimental group’s critical thinking performance, with large effect sizes on post-test scores compared to the control group. Regression analysis confirmed that personalization, engagement, authenticity, and adaptive feedback each had a strong positive effect on critical thinking outcomes, with path coefficients ranging between β = .27 and β = .46. Structural equation modeling further demonstrated that these four variables collectively explained 68% of the variance in critical thinking development, confirming the overall model hypothesis.  The results underscore the effectiveness of AI-generated case studies in addressing key limitations of ODL, including isolation, lack of contextualization, and delayed feedback. By integrating AI-driven instructional design into learning management systems, institutions in Bangladesh can support critical thinking development at scale while ensuring inclusivity across diverse learner groups. This study contributes to the global literature on AI-enhanced pedagogy by demonstrating its applicability and impact within a South Asian ODL context, where access and equity are central educational challenges.