Artificial Intelligence in Higher Education: Benefits, Challenges and Future Directions
Keywords:
— Artificial Intelligence, Higher Education, Generative AI, Intelligent Tutoring Systems, Retrieval-Augmented Generation, Academic Integrity, Learning Analytics, Responsible AI, Pedagogical Governance.Abstract
Artificial Intelligence (AI) and Generative AI (GenAI) technologies are fundamentally reshaping tertiary education ecosystems by transforming pedagogical delivery, programming assistance, assignment scaffolding, and institutional administration. While conventional agents and foundation models provide rapid 24/7 academic support, commercial off-the-shelf systems often deliver uncited, generalized responses lacking syllabus alignment, academic contextualization, and transparent pedagogical safeguards. This research paper presents an analytical examination of AI in higher education, assessing its historical evolution, key pedagogical applications, institutional benefits, operational bottlenecks, and ethical challenges. Combining an exhaustive systematic literature review across foundational educational computing studies with a mixed-method empirical methodology, this paper investigates how intelligent tutoring systems, large language models (LLMs), automated formative assessment, and predictive learning analytics can be systematically embedded within university curricula. Crucially, the paper explores dedicated support systems for computer applications curricula, including programming debugging, assignment scaffolding, and placement training. The paper addresses critical risks surrounding academic integrity, cognitive bypass, knowledge hallucinations, data privacy compliance, and algorithmic bias, proposing a multi-tiered Responsible AI Governance Framework for higher education institutions.
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