AI-PACT: A structured framework for integrating Artificial Intelligence into active and contextual learning in higher education

Abstract

Higher education increasingly requires teaching approaches that move beyond content transmission towards active interpretation, contextual application and the development of higher-order thinking. Yet, lecture-centred teaching can leave students with limited opportunities to connect theoretical concepts to real-world situations, while the use of artificial intelligence (AI) in education may remain fragmented and tool-driven. This article presents AI-PACT (AI-Powered Active and Contextual Teaching), a structured and reusable teaching method that integrates AI within an Input–Process–Output (IPO) architecture and an eight-stage learning journey: Engage, Explore, Experience, Challenge, Diagnose, Solve, Reflect and Assess. The method positions AI as a pedagogical enabler rather than a substitute for teaching or student reasoning. Its design is illustrated through two undergraduate learning prototypes, Scale of Poverty and Unemployment & Inflation, which retain the same learning architecture while addressing different content domains. In addition to describing the framework, the article incorporates exploratory feedback from interviews with 15 students who reported that the newer learning method helped them understand the subject matter better than conventional techniques. For analytical clarity, these accounts are presented as early perceptions of learning before and after exposure to AI-PACT. The findings are organised around perceived conceptual understanding, contextualisation, active participation, analytical engagement and the perceived usefulness of structured AI support. The evidence suggests that AI-PACT offers a promising pedagogical structure for connecting content, experience, inquiry, diagnosis, solution development and reflection. The article concludes with implications for implementation and a rigorous evaluation agenda using baseline and post-intervention measures, student artefacts, reflective evidence and comparison with conventional instruction.