The integration of artificial intelligence (AI) in education has emerged as a transformative force, reshaping the learning landscape for students across the globe. A recent study conducted by researchers Mistry, Jhala, and Maheta delves into the adoption and utilization of AI tools among school and university students in Surat city, highlighting the significance of understanding new technologies through the lens of established frameworks. Their investigation employs the UTAUT2 model, an influential theoretical framework that explains the technology acceptance process, to unveil critical insights about students’ perceptions and usage patterns of AI educational tools.
The rapid acceleration of digital technology has heralded an era where artificial intelligence becomes integral to educational environments. AI tools are not merely enhancements; they reconfigure learning paradigms. From personalized learning experiences that adapt to individual student needs to AI-driven analytics that inform teaching methods, the implications are profound. The study’s authors aim to decode these phenomena by examining various dimensions of AI tool adoption, addressing both the enthusiasm and skepticism surrounding these innovations.
Within the framework of UTAUT2, the researchers explore multiple factors influencing AI adoption. Performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and price value all play pivotal roles in determining how students engage with AI technologies. The authors meticulously detail each construct, illuminating how they converge and diverge in relation to the educational context. This nuanced understanding informs educators, policymakers, and technology developers about the driving forces behind AI tool utilization.
Interestingly, the study reveals a disparity in AI adoption trends between different educational levels. University students exhibit a higher propensity for AI tool adoption compared to their school counterparts. This variance may stem from differences in technological fluency, access to resources, and the nature of educational demands at varying academic stages. Insight into these distinctions allows stakeholders to tailor AI solutions that cater specifically to the needs of different learning groups.
Moreover, the authors illuminate the critical importance of facilitating conditions, which include access to technology, training, and support systems. In an educational setting, these conditions can significantly mediate the user experience. Notably, schools and universities must invest in robust infrastructure and provide comprehensive training for both students and educators to maximize the potential benefits of AI tools. Without such support, even the most sophisticated technology may fail to gain traction.
Social influence also emerges as a key driver in the study, emphasizing the role peer behaviors and societal norms play in shaping individual attitudes toward AI adoption. As students witness their peers effectively harnessing AI for academic success, they are more inclined to engage with these technologies themselves. This insight can lead to initiatives that foster positive peer influence and promote collaborative learning environments where AI tools can be effectively integrated.
Another fascinating aspect of this research pertains to hedonic motivation, reflecting the enjoyment derived from using AI educational tools. Students who find learning engaging and enjoyable are inherently more likely to adopt these technologies. This finding serves as a powerful testament to the importance of creating interactive, gamified learning experiences that not only educate but also entertain. Educational institutions can thus innovate by designing AI tools that captivate students’ imaginations and stimulate their intrinsic motivation to learn.
The issue of price value also resurfaces as a critical consideration in AI adoption. For many educational institutions, budget constraints are an ever-present challenge. The research suggests that perceived value relative to costs heavily influences students’ inclination to adopt AI tools. Thus, stakeholders must emphasize demonstrating the tangible benefits of these technologies to foster a willingness to invest in AI-enhanced educational resources. Clear evidence of improved learning outcomes will be central to convincing policymakers and institutions to allocate funding for such initiatives.
Delving deeper into the implications of the research, it becomes evident that understanding the nuances of AI tool adoption is crucial for the development of educational policy. Policymakers must consider how various factors interact in the unique context of education, ensuring that access to AI tools is equitable and that training programs are adequately funded. As AI continues to permeate educational systems, an informed policy approach will account for the diverse needs of students, educators, and educational institutions alike.
Ultimately, Mistry and colleagues’ research underscores the dynamic interplay between technology and education. The findings hold promise not just for enhancing individual learning experiences but also for redefining educational pedagogies in the digital age. As AI becomes more embedded in education, understanding these adoption dynamics may lead to improved student outcomes and a more effective educational landscape.
In conclusion, this comprehensive study provides invaluable insights into the adoption and usage of AI tools in education, specifically within the context of Surat city’s students. The UTAUT2 framework serves as a robust lens through which to examine this complex phenomenon, shedding light on the multifaceted factors that drive technology acceptance. As educators, researchers, and policymakers strive to harness the power of artificial intelligence in education, studies like this one are pivotal in guiding future initiatives and ensuring that AI tools serve to benefit all learners in their pursuit of knowledge.
As we continue to witness the evolution of education in a technology-driven world, it is paramount that we remain vigilant in understanding the forces at play in the adoption of AI tools. The future of education may very well hinge on how effectively we embrace and integrate these innovative technologies, shaping not only the landscape of learning but also the future of society at large.
Subject of Research: Adoption and use of artificial intelligence tools in education among school and university students.
Article Title: Adoption and use of artificial intelligence tools in education: a UTAUT2-based study of school and university students in Surat city.
Article References:
Mistry, A., Jhala, P., Maheta, D. et al. Adoption and use of artificial intelligence tools in education: a UTAUT2-based study of school and university students in Surat city. Discov Educ 4, 551 (2025). https://doi.org/10.1007/s44217-025-00979-5
Image Credits: AI Generated
DOI: https://doi.org/10.1007/s44217-025-00979-5
Keywords: Artificial intelligence, education, UTAUT2, technology adoption, learning outcomes, student engagement.
