Evolution of Learning: Assessing the Transformative Impact of Generative AI on Higher Education

Abstract

Generative artificial intelligence (GenAI) models, such as ChatGPT, have rapidly gained popularity. Despite this widespread usage, there is still a limited understanding of how this emerging technology impacts different stakeholders in higher education. While extensive research exists on the general opportunities and risks in education, there is often a lack of specificity regarding the target audience—namely, students, educators, and institutions—and concrete solution strategies and recommendations are typically absent. Our goal is to address the perspectives of students and educators separately and offer tailored solutions for each of these two stakeholder groups. This study employs a mixed-method approach that integrates a detailed online questionnaire of 188 students with a scenario analysis to examine potential benefits and drawbacks introduced by GenAI. The findings indicate that students utilize the technology for tasks such as assignment writing and exam preparation, seeing it as an effective tool for achieving academic goals. Subsequent the scenario analysis provided insights into possible future scenarios, highlighting both opportunities and challenges of integrating GenAI within higher education for students as well as educators. The primary aim is to offer a clear and precise understanding of the potential implications for students and educators separately while providing recommendations and solution strategies. The results suggest that irresponsible and excessive use of the technology could pose significant challenges. Therefore, educators need to establish clear policies, reevaluate learning objectives, enhance AI skills, update curricula, and reconsider examination methods.

Graphical abstract

Keywords

generative AI / ChatGPT / higher education / scenario analysis

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Acknowledgments

The research was supported by the German Federal Ministry of Education and Research (BMBF) in the Programme Künstliche Intelligenz in der Hochschulbildung (Grant No. 16DHBKI010) as well as the Programme Sachsen-Anhalt WISSENSCHAFT Gleichstellung, Qualifikation, Nachwuchs aus dem Europäischen Sozialfonds Plus (Grant No. ZS/2023/11/181808). We thank all students who voluntarily participated in the survey and the participants in our feedback sessions. We thank Ashish Dalvi and Syed Khubaib Zaidi for conducting the literature review on lecture strategies. Furthermore, we would like to acknowledge the insightful comments and constructive suggestions from Frieder Stolzenburg. Open Access funding enabled and organized by Projekt DEAL.

Conflict of Interest

The authors declare that they have no conflict of interest related to the content of this paper.

Ethics Statement

The authors declare that their Institutional Ethics Committee confirmed that no ethical review was required for this study. Written informed consent for participation was not required because all participants‘ data was anonymized before the statistical analyses were done.

Data Availability Statements

The authors confirm that all data generated or analysed during this study are included in this published article.

Authors Contributions

Main author Stefanie Krause developed the study conception and design, finalized the manuscript with the reviewer feedback. Survey preparation and data collection were performed by Bhumi Hitesh Panchal and Nikhil Ubhe. The data analysis was performed by all authors. The first draft of the manuscript was written by all authors. All authors whose names appear on the submission made substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data; or the creation of new software used in the work; drafted the work or revised it critically for important intellectual content; approved the version to be published; and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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