AI in Academia: An In-Depth Analysis of the Impact of AI on Undergraduate Studies

Autor/inn/en	Mohammad Alawamleh; Rabab Alatout; Worud Awamleh
Titel	AI in Academia: An In-Depth Analysis of the Impact of AI on Undergraduate Studies
Quelle	In: Journal of Academic Ethics, 24 (2026) 1, Artikel 5Infoseite zur Zeitschrift PDF als Volltext Link als defekt meldenVerfügbarkeit
Zusatzinformation	ORCID (Mohammad Alawamleh)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1570-1727
DOI	10.1007/s10805-025-09685-1
Schlagwörter	Forschungsbericht; Undergraduate Students; Undergraduate Study; Artificial Intelligence; Technology Uses in Education; Morale; Research Skills; Ethics; Student Motivation; Learner Engagement; Influence of Technology; Student Attitudes; Computer Attitudes + Suchen Sie Ihr Suchwort? Grundstudium; Künstliche Intelligenz; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Moral; Forschungsleistung; Ethik; Schulische Motivation; Schülerverhalten
Abstract	This study aims to provide a comprehensive understanding of how AI is influencing and shaping various aspects within the academic context by using a mixed-methods approach, combining quantitative investigation and qualitative analysis to explore AI impacts on undergraduate education. The findings indicate a significant positive correlation between AI usage and academic morale in the quantitative investigation, while results for research skills and ethical issues are not conclusive. Qualitative insights reveal positive factors affecting academic motivation and learning opportunities (e.g., increasing engagement with course content, tailored content, and saving time), but they can present ethical considerations. Given that this is a relatively new field of exploration, and taking into account the rapidly evolving nature of AI itself, there is a relatively insufficient amount of secondary data covering the relationships being studied in this paper. However, this study offers original contributions as variables derived from reviewed literature may have been inadequately explored in previous studies, lacking precision and depth. This study offers insights into the changing nature of AI in academia and identifies areas for further investigation. (As Provided).
Anmerkungen	BioMed Central, Ltd. Available from: Springer Nature. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: customerservice@springernature.com; Web site: https://www.springer.com/gp/biomedical-sciences
Begutachtung	Peer reviewed
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2026/1/01