Systematic Review: AI's Impact on Higher Education - Learning, Teaching, and Career Opportunities

Abstract

AI is transforming many fields, including higher education. The pandemic has shown how AI can improve learning and teaching in higher education. This review examines how AI affects education quality, learning assessment, and higher education jobs (HE). The study employs a systematic qualitative method to review the academic literature on AI and higher education between 1900 and 2021. The data was gathered from various sources, including ERIC, Scopus, and the Web of Science, using specific exclusion and inclusion criteria centred on publication date, language, reported outcomes, setting, and publication type. From there on, the articles were analysed by Rayyan Software and categorised in Excel according to a scale that included aspects such as the quality of learning and teaching, assessment, and potential ethical future careers. The research also produced two bibliometric figures using VOSviewer to investigate co-authorship and the frequency of keyword occurrences in academic journals published in AI and HE. The analysis was done to ensure the study's validity in the scientific community. The study found that AI can improve education quality, provide practical learning and teaching methods, and improve assessments to better prepare students for careers. The study also emphasises the potential of AI to shape future employment opportunities and the need for higher education institutions to adopt AI to meet market demands. The study calls for more research on AI's effects on assessment, integrity, and higher education careers.

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