Title: Enhancing Student Engagement through AI-Enabled Simulated Case Activity: An Empirical Study

Description

This study utilises interactive, decision-based learning experiences in tertiary education to investigate the role of generative AI in enhancing student engagement. OpenAI was employed to simulate a business case that was embedded within an H5P branching scenario. Students (N = 164) were tasked with making iterative decisions about market entry strategies and were provided with immediate feedback at each decision point to guide them toward the optimal outcome. To address learners’ limited avidity for long-form cases, the design is grounded in experiential theory.

A conceptual model was designed to test the influence of AI-enabled activity design on affective, cognitive, and behavioural engagement, as well as its collective outcome on student satisfaction. The model was tested through a structural equation model. Results highlighted a full mediation effect through engagement. This advances the use of AI technology in digital pedagogy, sparking engagement as a driver of satisfaction.

The study reframes AI as a co-creator of pedagogical resources, thus theoretically contributing to current literature. Practically, it also proposes AI as a facilitating tool for developing immersive, feedback-driven learning activities. The study further necessitates professional development and targeted training for educators to garner skills in applying AI programs for content creation.

Period	10 Oct 2025
Held at	School of Business