Impacts of Generative Artificial Intelligence in Higher Education: Research Trends and Students’ Perceptions

Sandra Saúde (), João Paulo Barros and Inês Almeida
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Sandra Saúde: Polytechnic Institute of Beja, School of Education, LabAT, Campus do IPBeja, Rua Pedro Soares, Apartado 6155, 7800-295 Beja, Portugal
João Paulo Barros: Polytechnic Institute of Beja, School of Technology and Management, LabSI2, Campus do IPBeja, Rua Pedro Soares, Apartado 6155, 7800-295 Beja, Portugal
Inês Almeida: Autónoma Techlab, Universidade Autónoma de Lisboa, Palácio dos Condes do Redondo, Rua de Santa Marta 56, 1169-023 Lisboa, Portugal

Social Sciences, 2024, vol. 13, issue 8, 1-19

Abstract: In this paper, the effects of the rapid advancement of generative artificial intelligence (Gen AI) in higher education (HE) are discussed. A mixed exploratory research approach was employed to understand these impacts, combining analysis of current research trends and students’ perceptions of the effects of Gen AI tools in academia. Through bibliometric analysis and systematic literature review, 64 publications (indexed in the SCOPUS and Web of Science databases) were examined, highlighting Gen AI’s disruptive effect on the pedagogical aspects of HE. The impacts identified by the literature were compared with the perceptions held by computer science students of two different HE institutions (HEIs) on the topic. An exploratory study was developed based on the application of a questionnaire to a group of 112 students. The results suggest that while Gen AI can enhance academic work and learning feedback, it requires appropriate pedagogical support to foster critical, ethical, and digital literacy competencies. Students demonstrate awareness of both the risks and benefits associated with Gen AI in academic settings. The research concludes that failing to recognize and effectively use Gen AI in HE impedes educational progress and the adequate preparation of citizens and workers to think and act in an AI-mediated world.

Keywords: bibliometric analysis; systematic literature review; generative artificial intelligence; higher education; impacts; students’ perceptions (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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