Agentic AI and Pedagogical Best Practice: The Tension Between Automation and Learning
2026-06-03 • Computers and Society
Computers and Society
AI summaryⓘ
The authors explain how AI in education is changing from simple chatbots to smart helpers that can start conversations and guide learning. They look at six teaching ideas like using what students already know and learning with others, and think about how AI affects these methods. They warn that AI might make learning too easy and less active if not designed carefully. They suggest ways to use AI that keep students involved and help teachers keep control.
Artificial IntelligenceAgentic AILearner AgencyPedagogical PrinciplesPrior Knowledge ActivationCollaborative LearningFormative AssessmentScaffoldingMetacognitionHuman-in-the-Loop
Authors
Steve Woollaston, Brendan Flanagan, Isanka Wijerathne, Hiroaki Ogata
Abstract
Artificial intelligence in education is evolving from passive chatbots to proactive AI agents capable of initiation and goal-directed interactions. While offering opportunities for personalised learning, this shift risks undermining learner agency and cognitive effort. This paper reviews six pedagogical principles-prior knowledge activation, collaborative learning, problem-based learning, formative assessment, scaffolding, and metacognition-through the lens of agentic AI. We discuss the tension between automation and learning, proposing design recommendations that prioritise intentional friction, dynamic scaffolding, human-in-the-loop oversight, and considered AI utilisation to ensure AI supports rather than supplants human learning.