Artificial Intelligence and Academic Achievement in Higher Education: A Conceptual Review
Year: 2026
Type: article
Abstract: Artificial Intelligence (AI) is transforming higher education by reshaping how students access information, engage with learning materials, undertake academic tasks, and achieve educational outcomes. This conceptual review examines the relationship between AI and academic achievement in higher education, with particular attention to the opportunities, challenges, and conditions that shape the educational value of AI technologies. The study adopts a secondary research method, based on existing scholarly literature and organising the reviewed studies thematically around the concepts, applications, educational benefits, academic achievement, human learning interaction, ethical concerns, and technology acceptance associated with AI. The paper argues that AI has considerable potential to enhance academic achievement by supporting personalised learning, providing immediate feedback, facilitating access to educational resources, assisting research and academic writing, and improving students’ engagement with complex learning tasks. However, the paper also identifies important challenges that may limit these benefits. Excessive dependence on AI may weaken students’ critical thinking, independent reasoning, creativity, and meaningful interaction with educators, while concerns relating to academic integrity, data privacy, fairness, transparency, and responsible use remain significant. The Technology Acceptance Model provides a useful conceptual lens for understanding the adoption of AI through perceived usefulness, perceived ease of use, behavioural intention, and actual technology use. The study concludes that AI can contribute meaningfully to academic achievement when deployed as a supportive educational resource rather than a substitute for human teaching, critical thinking, and student–educator interaction.
Source: Konfrontasi
Institutions: Caleb University, Federal Polytechnic Orogun
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W7214101057