TY - JOUR
T1 - Perceived influence of GenAI on student engagement in online higher education
AU - Ala, Mamun
AU - Shahid, Sehrish
AU - Mahmud, Saadia
AU - Mohyuddin, Syed
AU - Kaur, Kuldeep
PY - 2025/9/16
Y1 - 2025/9/16
N2 - This paper analyses the perceived influence of Generative Artificial Intelligence (GenAI) on student engagement in online higher education using the Self-Determination Theory (SDT) framework. Drawing on qualitative data from 27 experienced academics across the Australian tertiary sector, the study investigates the perspectives of online educators on how GenAI may influence three core psychological needs that are considered central to student engagement: autonomy, competence, and relatedness. The findings reveal that GenAI can enhance student autonomy through personalised learning opportunities, improve competence through real-time feedback and writing support, and support relatedness by enabling inclusive participation for linguistically diverse learners. Nevertheless, the study also identifies key risks, including over-reliance on GenAI, diminished critical thinking, reduced interaction with peers and instructors, reduced collaboration, and concerns around academic integrity. The paper argues that to harness GenAI’s pedagogical potential, higher education institutions must integrate GenAI literacy, student-centred instructional design, and actionable ethical frameworks. With such measures in place, GenAI can evolve from an emerging tool into a major driver of engagement, inclusion, and transformational learning in higher education.
AB - This paper analyses the perceived influence of Generative Artificial Intelligence (GenAI) on student engagement in online higher education using the Self-Determination Theory (SDT) framework. Drawing on qualitative data from 27 experienced academics across the Australian tertiary sector, the study investigates the perspectives of online educators on how GenAI may influence three core psychological needs that are considered central to student engagement: autonomy, competence, and relatedness. The findings reveal that GenAI can enhance student autonomy through personalised learning opportunities, improve competence through real-time feedback and writing support, and support relatedness by enabling inclusive participation for linguistically diverse learners. Nevertheless, the study also identifies key risks, including over-reliance on GenAI, diminished critical thinking, reduced interaction with peers and instructors, reduced collaboration, and concerns around academic integrity. The paper argues that to harness GenAI’s pedagogical potential, higher education institutions must integrate GenAI literacy, student-centred instructional design, and actionable ethical frameworks. With such measures in place, GenAI can evolve from an emerging tool into a major driver of engagement, inclusion, and transformational learning in higher education.
U2 - 10.37074/jalt.2025.8.2.16
DO - 10.37074/jalt.2025.8.2.16
M3 - Article
SN - 2591-801X
VL - 8
JO - Journal of Applied Learning and Teaching
JF - Journal of Applied Learning and Teaching
IS - 2
ER -