Author: Dr. Bimal Mandal
DOI Link: https://doi.org/10.70798/Bijmrd/03100029
Abstract: The integration of Artificial Intelligence (AI) in education has revolutionized adaptive learning systems by enabling real-time personalization and dynamic curriculum adjustments. These systems analyze learners’ behaviors, preferences, and performance patterns to optimize content delivery and enhance learning efficiency. However, concerns have emerged regarding cognitive manipulation, where algorithms may inadvertently—or intentionally—steer learners’ attention, decision-making, and thought processes based on data-driven predictions (Zuboff, 2019).Adaptive platforms, powered by machine learning, can promote beneficial cognitive engagement; yet, they also raise ethical questions about autonomy, transparency, and data privacy (Luckin et al., 2016). The potential for manipulating learner cognition— through reinforcement strategies, gamification, or behavioral nudges—demands a framework that balances innovation with ethical responsibility. As Selwyn (2020) argues, unchecked AI in education could compromise critical thinking by over-structuring learning paths.This study explores the dual nature of AI in adaptive learning: its capacity to support personalized education and its risk of influencing learner cognition beyond pedagogical intent. It highlights the need for human oversight, transparent algorithmic design, and inclusive policy regulation. Through critical review and analysis, the paper offers recommendations for designing AI-driven educational technologies that align with learner agency, ethical standards, and democratic values.
Keywords: Artificial Intelligence, Adaptive Learning Systems, Cognitive Manipulation, Educational Ethics.
Page No: 233-240