A. Muzawwirah Patawari
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Artificial Intelligence in Higher Education: A Systematic Review of Its Impact on Student Learning Nurfauziah; Dian Atmasani; A. Muzawwirah Patawari; Nur Athiyyah Fadhilah; Husna Saleh
Information Technology Education Journal Vol. 4, No. 2, May (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v4i2.8311

Abstract

The development of digital technology has made artificial intelligence an integral part of higher education. While its use by university students provides many benefits in supporting academic activities, there are also concerns about its negative impact, especially in relation to academic integrity, dependability, and critical thinking skills. This research aims to identify the positive and negative impacts of the use of artificial intelligence by university students as well as the challenges faced in the context of higher education. The method used was Systematic Literature Review with the PRISMA approach. The total population of articles obtained was 200 articles. Scientific articles were sourced from the Scopus database published between 2022 and 2025. Articles were screened based on inclusion and exclusion criteria and assessed using the CASP (Critical Appraisal Skills Programme) approach, resulting in 19 articles that could be analysed. The results showed that artificial intelligence can improve learning efficiency, strengthen concept understanding, and support student creativity and problem solving. However, there are serious risks such as plagiarism, dissemination of inaccurate information, and decreased motivation to learn independently. Lack of regulation and digital literacy are factors that exacerbate these negative impacts. Therefore, it is important for higher education institutions to urgently create policies for the ethical use of artificial intelligence and provide comprehensive digital literacy training to students. This research provides a scientific basis for policy makers to optimise the benefits of artificial intelligence while mitigating the risks of its use in academia.