article · Technology in Society
This study investigated the factors influencing the adoption of generative AI (GenAI) tools in higher education, using the Theory of Planned Behaviour (TPB). It examined how perceived benefits, strengths, weaknesses, and risks of GenAI relate to TPB factors such as attitude, subjective norms, and perceived behavioural control. The research also explored the link between TPB variables, intention to use GenAI, and actual usage. A quantitative approach was employed, collecting data from 130 lecturers and 168 students across various higher education institutions via an online questionnaire. The findings indicate that while lecturers' and students' perceptions of GenAI risks and weaknesses differ, the perceived strengths and advantages positively influence their attitudes, subjective norms, and perceived behavioural control. Crucially, the core TPB variables significantly impact the intention to use GenAI, which in turn positively affects its actual adoption.
This research helps understand why educators and students adopt generative AI. It provides insights for institutions to develop effective policies and guidelines, ensuring the responsible and beneficial integration of these tools into learning and teaching environments. Understanding these drivers is crucial for optimising educational technology strategies.
The findings offer managerial and policy implications for stakeholders in higher education, guiding the formulation of rules and regulations for GenAI use. This research could inform educational technology developers on features that enhance perceived strengths and address weaknesses, potentially leading to more widely adopted and ethically sound AI tools for learning and teaching. It is applied research, providing insights for strategic planning and product development in the educational technology sector.
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Drawing on the Theory of Planned Behaviour (TPB), this study investigates the relationship between the perceived benefits, strengths, weaknesses, and risks of generative AI (GenAI) tools and the fundamental factors of the TPB model (i.e., attitude, subjective norms, and perceived behavioural control). The study also investigates the structural association between the TPB variables and intention to use GenAI tools, and how the latter might affect the actual usage of GenAI tools in higher education. The paper adopts a quantitative approach, relying on an anonymous self-administered online questionnaire to gather primary data from 130 lecturers and 168 students in higher education institutions (HEIs) in several countries, and PLS-SEM for data analysis. The results indicate that although lecturers' and students' perceptions of the risks and weaknesses of GenAI tools differ, the perceived strengths and advantages of GenAI technologies have a significant and positive impact on their attitudes, subjective norms, and perceived behavioural control. The TPB core variables positively and significantly impact lecturers' and students’ intentions to use GenAI tools, which in turn significantly and positively impact their adoption of such tools. This paper advances theory by outlining the factors shaping the adoption of GenAI technologies in HEIs. It provides stakeholders with a variety of managerial and policy implications for how to formulate suitable rules and regulations to utilise the advantages of these tools while mitigating the impacts of their disadvantages. Limitations and future research opportunities are also outlined.
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DOI: 10.1016/j.techsoc.2024.102521
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