Beyond the hype: Decoding how generative AI shapes academic achievement in higher education

Authors

DOI:

https://doi.org/10.14742/ajet.10395

Keywords:

academic achievement, self-efficacy, higher education, generative AI, ChatGPT, AI literacy, cross-sectional survey

Abstract

The study investigated how university students’ adoption and usage of ChatGPT influences their academic achievement. The study further explored how these relationships differ by gender and field of study. Using an online cross-sectional survey, data were collected from 461 students at a Ghanaian public university. Measures consisted of ChatGPT literacy, self-efficacy, behavioural intention to use ChatGPT and academic achievement. Structural equation modelling and multi-group analysis were employed to test hypothesised relationships and examine potential gender and discipline differences. Findings show that higher ChatGPT literacy and self-efficacy significantly boost students’ behavioural intention to use ChatGPT, which positively impacts academic achievement. Notably, the effect of behavioural intention on achievement was stronger among science, technology, engineering and mathematics (STEM) students, highlighting the role of field of study in shaping ChatGPT’s educational benefits. The study presents a predictive model linking ChatGPT adoption factors to academic success and emphasises the need for targeted support, especially for non-STEM students, to foster equitable artificial intelligence (AI) integration. It offers practical guidance for educators and policymakers to develop discipline-sensitive strategies that enhance ChatGPT literacy and self-efficacy, ensuring more inclusive and effective use of generative artificial intelligence (GenAI) tools in higher education.

 

Implications for practice or policy:

  • University administrators should mandate AI literacy training during orientation to ensure equitable student engagement.
  • Non-STEM programme leaders can improve outcomes by embedding discipline-specific AI tasks into core curricula.
  • Equity and inclusion officers must monitor demographic disparities in adoption to provide targeted support.
  • Institutional policymakers should establish integrity frameworks that balance AI-assisted learning with rigorous assessment.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Author Biography

Aras Bozkurt, Anadolu University

Aras Bozkurt is a researcher and faculty member at Anadolu University, Türkiye. With MA and PhD degrees in distance education, Dr. Bozkurt's work focuses on empirical studies in areas such as distance education, online learning, networked learning, and educational technology. He applies critical theories like connectivism, rhizomatic learning, and heutagogy to his research. Dr. Bozkurt is also interested in emerging research paradigms, including social network analysis, sentiment analysis, and data mining. Dr. Bozkurt's studies also cover the integration of artificial intelligence technologies into educational processes in the axis of human-machine interaction.

His dedication to advancing the field is reflected in his editorial roles as the Editor-in-Chief of Open Praxis and Asian Journal of Distance Education, as well as his roles as an associate editor for prestigious journals like Higher Education Research and Development, Online Learning, eLearn Magazine, and Computer Applications in Engineering Education.

Downloads

Published

2026-07-05

How to Cite

Essel, H. B., Johnson, E. E., Nunoo, F. K. N., Sarpong-Danquah, B., & Bozkurt, A. (2026). Beyond the hype: Decoding how generative AI shapes academic achievement in higher education. Australasian Journal of Educational Technology. https://doi.org/10.14742/ajet.10395

Issue

Early Release Articles

Section

Articles

License

Copyright (c) 2026 Harry Barton Essel, Esi Eduafua Johnson, Francis Kofi Nimo Nunoo, Beatrice Sarpong-Danquah, Aras Bozkurt

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Articles published in the Australasian Journal of Educational Technology (AJET) are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant AJET right of first publication under CC BY-NC-ND 4.0.

This copyright notice applies to articles published in AJET volumes 36 onwards. Please read about the copyright notices for previous volumes under Journal History.