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THE ROLE OF ARTIFICIAL INTELLIGENCE IN ENHANCING COMPUTER-BASED LEARNING
Abstract
Artificial Intelligence (AI) is playing an increasingly significant role in the transformation of computer-based learning (CBL), offering new opportunities to enhance personalization, engagement, and learning effectiveness. This paper explores the role of AI in strengthening CBL by examining its theoretical foundations, key methods and technologies, and implications for educational practice. Grounded in educational technology theory and cognitive learning frameworks, the study discusses how AI-driven systems support adaptive learning, automated feedback, and individualized learning pathways that respond to diverse learner needs. Technologies such as adaptive learning systems, intelligent tutoring systems, learning analytics, and natural language processing are analyzed for their contribution to improving learner engagement, self-regulation, and higher-order cognitive skills. The paper also traces the evolution of learning from traditional face-to-face instruction to intelligent digital learning environments, highlighting how AI-enabled systems facilitate active learning, reflection, and independent problem-solving through personalized pacing and feedback. Practical considerations for designing and implementing AI-based learning in educational institutions are examined, including the importance of digital infrastructure, pedagogical alignment, staff training, scalability, and equitable access to technology. Furthermore, the study addresses key challenges associated with AI integration, such as the risk of overreliance on automation, increased cognitive load, reduced learner autonomy, and the potential widening of the digital divide. The paper concludes that while AI has considerable potential to enhance computer-based and blended learning, its success depends on thoughtful, inclusive design and a balanced integration that ensures AI supports-rather than replaces-meaningful, human-centered learning experiences.
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