From AI Tools to Learner-Centered Human–AI Collaboration: Developing and Evaluating the Learner-Centered Human–AI Pedagogical Framework (LCHAP)

Abstract

Generative artificial intelligence (AI) is reshaping higher education, yet practical guidance for integrating it into meaningful learning remains limited. This paper introduces the Learner-Centered Human–AI Pedagogical Framework (LCHAP), which positions AI as a collaborative cognitive partner while preserving learner agency and responsibility. LCHAP was implemented through the Human–AI Learning Cycle (HALC) in a 15-week quasi-experimental mixed-methods study involving 80 first-year undergraduates at the Mongolian National University of Education. At post-intervention, the experimental group showed higher mean scores than the control group in English writing, learner engagement, learner autonomy, AI literacy, reflective learning, and critical thinking. Qualitative evidence indicated a shift from answer generation toward idea exploration, comparison, revision, and reflection. Because the reported quantitative evidence is descriptive, the findings should be interpreted as preliminary rather than causal. LCHAP offers a practical design framework for responsible, learner-centered Human–AI collaboration in higher education.