article · Journal for STEM Education Research
A survey of 176 undergraduate students at a public university in southwestern Nigeria reveals how technological readiness, self-efficacy, and attitudes influence the adoption of artificial intelligence tools. Using structural equation modelling based on the technology acceptance model, the investigation established that a student's attitude serves as the primary driver for using artificial intelligence tools. While technological self-efficacy directly shapes usage and influences perceived ease of use, it does not determine perceived usefulness or general attitude. Conversely, technological readiness influences self-efficacy, perceived ease of use, and perceived usefulness, yet it does not directly drive actual usage or attitudes. Because these behavioural factors are interconnected, educational institutions are encouraged to foster artificial intelligence literacy and guide adoption rather than impose outright bans. Supporting student confidence and competence allows for more seamless integration of these technologies into academic activities.
Understanding what drives student adoption of artificial intelligence tools helps universities design effective educational policies. Rather than attempting to ban these technologies, higher education institutions can focus on building digital literacy and positive attitudes. Recognising that readiness and confidence shape perceptions of utility allows educators to create structured guidance that prepares learners to use artificial intelligence responsibly and productively in their academic work.
This early-stage behavioural study provides empirical insights into how university students adopt emerging technologies. The findings could inform developers of educational software, EdTech platforms, and training providers aiming to introduce artificial intelligence tools to tertiary learners. To drive uptake, product designers and institutional programmes must target student attitudes and self-efficacy rather than relying solely on access or baseline technological readiness. The work itself remains academic research rather than a deployable commercial product.
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Abstract This study investigates the relationship between undergraduates’ technological readiness, self-efficacy, attitude, and usage of artificial intelligence (AI) tools. The study leverages the technology acceptance model (TAM) to explore the relationships among the study’s variables. The study’s participants are 176 undergraduate students from a public university in southwestern Nigeria. The Partial Least Square Structural Equation Modeling (PLS-SEM) was used to analyze the responses from the participants. The questionnaire has six constructs measured on a 5-point Likert scale. The results show that undergraduates’ technological self-efficacy determines their usage of AI tools and perception of AI tools’ ease of use, but this does not determine their perception of the AI tools’ usefulness and attitude towards AI tools usage. Also, technological readiness was found to determine the perception of the AI tools’ usefulness, perception of AI tools’ ease of use, and technological self-efficacy among undergraduates but does not determine their usage of AI tools and attitude towards AI tools usage. In addition, undergraduates’ attitude towards AI tools was considered the primary determinant of the usage of AI tools. It was concluded that some factors determine the adoption of AI tools, which are interrelated. Educators can play a pivotal role in empowering students to harness the power of AI tools by encouraging their usage under well-coordinated guidance rather than imposing outright restrictions. By fostering AI literacy and equipping students with the knowledge and skills to navigate these innovative technologies, educators can instil the confidence and competency needed to integrate AI tools into various academic activities seamlessly.
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DOI: 10.1007/s41979-024-00132-1
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