| by Walter Claassen (SARUA Associate) |
Right from the release of ChatGPT late in 2022, we have seen an uptake of GenAI in academic contexts. Some academics implemented the technology into existing pedagogical approaches to fulfil some functions; others reconsidered their pedagogical approaches within the scope of institutional policies to enable functionalities that were not feasible before the new and prominent presence of GenAI. In such cases, the existence of GenAI enabled new pedagogical approaches, or even transformed them to some extent.
Results of implementations of GenAI as a new pedagogical tool or as enabling new pedagogical approaches were reported in the scholarly and popular media, and we soon saw a massive increase in publications, both journal papers and other reports. Most of these reports during 2023 and 2024 were of a reporting or an anecdotal nature, informing on individual applications, experiments, strategies towards implementation, surveys of student and faculty acceptance of new approaches, etc. Many of these reports were indeed very useful for informing and encouraging other colleagues to implement such approaches or for stimulating them to re-imagine teaching and learning in different ways.
Many of these earlier reports were, however, not peer reviewed. Since late 2023, we have also seen a rapid increase in the number of peer-reviewed publications on the topic. In fact, the number of publications has become overwhelming, and many academics have difficulty finding their way across this corpus of material.
In June 2025, the first systematic review of peer-reviewed publications on pedagogical applications of GenAI appeared: Y. Qian, ‘Pedagogical Applications of Generative AI in Higher Education: A Systematic Review of the Field’, TechTrends, June 2025. Click to read.
This publication is very useful for academics and officials involved in teaching and learning activities. It provides a systematic analysis of peer-reviewed publications on the topic until November 2024. During the review process, the initially identified 262 publications were reduced to 37, by excluding articles based mainly on surveys and interviews and some other criteria. These articles were then analysed and coded in detail. Through this rigorous research method, the article then provides a clear picture of the pedagogical uses of GenAI that came to the fore since the release of ChatGPT.
Two figures (full pages) then provide an overview of ‘Pedagogical applications’ and ‘Challenges’, respectively. The reader can get a clear and systematic overview and can follow up by searching on the ‘code’ (terminology) to move to the relevant discussion and the publications that referred to that specific application or challenge.
The publication by Qian amounts to a systematic and functional reference work on applications and challenges during the period covered. It is highly recommended for academics and officials involved in shaping university policies and implementation on teaching and learning in the era of AI and GenAI.
