Exploring the landscape of GenAI and education literature: A taxonomy of themes and sub-themes

Abstract

The research landscape surrounding Generative Artificial Intelligence (GenAI) and education is rapidly expanding, characterised by a dynamic array of themes and sub-themes. This paper aims to construct a comprehensive taxonomy that categorises the current literature on the integration of GenAI in educational settings. To do so, a systematic analysis was conducted first, which filtered and selected 30 pieces of literature. Within this literature, 369 phrases were identified, which culminated in the development of 5 overarching themes and 38 sub-themes. These themes within the systematic review ran parallel to a taxonomy that was developed from them, which subsequently revealed a tension between them. Emphasising an interpretivist approach, this research acknowledges the subjective nature of knowledge formation and interpretation, enhancing understanding of the complex interplay between GenAI and educational practices, with a predominant focus on GenAI in higher education. Unlike previous literature reviews, this paper presents a subsequent taxonomy derived from the systematic review, which holds an original narrative: that a critical tension exists between technical discussions of GenAI and the pedagogical realities faced by educators. This taxonomy presents evidence that supports a notion that the fledging field of ‘GenAI and education’ research has two developing strands: the technical and the pedagogical. Not only are these two strands of foci emerging within the literature, but there is also a growing disconnect or void between the two. Without addressing this almost ‘siloed’ growth, conversations about GenAI's role in education risk becoming overly abstract, lacking practical relevance for educators. By illuminating this tension, this research invites further exploration into how educators can navigate the evolving landscape of GenAI in their classrooms.