Rethinking Effective Learning in Higher Education: From Teacher Centered Instruction to Human- Centered AI-Augmented Learning

The rapid growth of artificial intelligence (AI), particularly generative AI, is challenging conventional approaches to teaching and learning in higher education. While teacher-centered instruction provides expert guidance and structured knowledge, its dominant use may limit learner autonomy, personalization, active engagement, and individualized feedback. At the same time, AI integration offers opportunities for adaptive support and self-directed learning while raising concerns about academic integrity, learner dependence, misinformation, privacy, equity, and the changing role of teachers. This conceptual paper rethinks effective learning by examining the transition from predominantly teacher-centered instruction toward human-centered AI-augmented learning. An integrative literature review of scholarly research and major policy documents published between ۲۰۲۲ and ۲۰۲۶ was conducted. The synthesis indicates that AI’s educational value depends less on technological sophistication than on pedagogical integration. AI can enhance learning through personalization, feedback, scaffolding, and self-directed learning when supported by human agency, critical engagement, teacher oversight, and ethical governance. Accordingly, the paper proposes a human-centered model in which AI functions as a pedagogical scaffold rather than a substitute for teachers. Effective higher education should therefore integrate teachers, learners, and AI within a balanced ecosystem that promotes personalized, active, critical, and ethically responsible learning.

کلیدواژه ها:

Human-Centered AI ، AI Augmented-Learning ، Higher Education ، Generative AI ، Learner Autonomy.