Artificial intelligence in curriculum evaluation through a narrative systematic review of opportunities and challenges in higher education
Abstract
The integration of artificial intelligence (AI) into higher education curriculum evaluation has become increasingly relevant in response to institutions’ growing demand for adaptive, accurate, and data-driven quality assurance processes. However, the use of AI in curriculum evaluation remains fragmented and is often positioned merely as a technical tool for learning or analytics, resulting in an underarticulated role in supporting systematic and decision oriented curriculum evaluation. Therefore, this study aims to systematically examine how AI is utilised in higher education curriculum evaluation by synthesising the associated opportunities, challenges, and theoretical and practical implications, with particular emphasis on programme and institutional level evaluation. This study adopts a narrative systematic review approach to international publications published between 2018 and 2025, applying inclusion criteria focused on the use of AI in curriculum evaluation and learning within higher education contexts. Literature searches were conducted through Scopus, Web of Science, and Google Scholar, yielding 28 articles that were analysed thematically. The findings identify four major opportunities, namely learning personalisation, predictive analytics, automation of evaluative processes, and enhancement of administrative efficiency. At the same time, the literature highlights significant challenges, particularly tensions between automation and human oversight, risks of algorithmic bias, ethical and data protection concerns, and issues related to institutional readiness. To bridge these opportunities and challenges, this study proposes a conceptual framework AI for Curriculum Evaluation aligned to CIPP–O which maps the role of AI across each stage of curriculum evaluation without replacing human professional judgement. Overall, while AI demonstrates strong potential to enhance the quality of curriculum evaluation, its effective implementation requires clear governance structures, adequate human resource capacity, and robust oversight mechanisms.