Abstract

Experiential learning is widely recognized as an effective pedagogical approach for bridging theory and practice in Information Systems (IS) education. However, providing meaningful experiential opportunities at scale particularly in online and hybrid programs, and measuring their effectiveness remain persistent challenges due to limited industry access, coordination overhead, delivery constraints, and student-related factors. In this work, we discuss our experience using a cloud-hosted and AI-augmented employer-matching platform to deliver scalable and digitally accessible experiential learning across eight IS and technology-oriented courses in undergraduate and graduate programs at a business school in a large university in the southeastern United States. Drawing on Connectivism, Kolb’s Experiential Learning Theory, and Situated Learning Theory, we propose a research model and develop hypotheses to guide empirical investigation. This paper presents the experiential design, research model, hypotheses, data collection strategy, and descriptive statistics from the collected data.

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