<p>The rapid advancement of Artificial Intelligence (AI) has catalysed significant digital transformation, presenting both opportunities and challenges within the educational landscape. While prior research has examined the integration of AI into academic curricula, limited studies have focused on AI adoption by students in contexts where its use is not mandated. This study primarily targets Generation Z (Gen-Z) students (aged 18–24) in urban India, while also incorporating millennials (aged 25–34) and AI domain experts, including faculty, industry practitioners, and professionals, to enrich the contextual understanding of AI adoption behaviours across diverse user groups. It extends the Unified Theory of Acceptance and Use of Technology (UTAUT) model by integrating composite moderators. Employing structural equation modelling (SEM) and a Multiple Indicators Multiple Causes (MIMIC) model, the research tests six hypotheses using data collected from 305 urban Indian respondents, analysing the moderating effects of gender, education level, and voluntary internet use. The findings indicate that behavioural intention, social influence, and digital engagement profiles have a positive effect on AI adoption. Students are primarily motivated by high expectations of AI’s performance, ease of use, and the surrounding social context. Additionally, self-empowerment emerges as a critical factor, with students actively seeking to enhance their skills and future career prospects through the utilisation of AI. While higher education levels and voluntary internet use have a positive moderating effect on AI adoption, gender demonstrates a negative moderating effect, underscoring the need to address gender disparities in AI access and usage. This study aims to offer insight into the dynamics of AI adoption among young Indian students. It highlights the necessity for targeted policies that foster inclusive and equitable access to AI technologies. Such initiatives are essential for mitigating gender-related barriers and further empowering students in their digital learning journeys.</p>

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AI adoption among young Indians: an analysis using a MIMIC model

  • Subhasis Bera,
  • Ishita Bera,
  • Dil Rahut

摘要

The rapid advancement of Artificial Intelligence (AI) has catalysed significant digital transformation, presenting both opportunities and challenges within the educational landscape. While prior research has examined the integration of AI into academic curricula, limited studies have focused on AI adoption by students in contexts where its use is not mandated. This study primarily targets Generation Z (Gen-Z) students (aged 18–24) in urban India, while also incorporating millennials (aged 25–34) and AI domain experts, including faculty, industry practitioners, and professionals, to enrich the contextual understanding of AI adoption behaviours across diverse user groups. It extends the Unified Theory of Acceptance and Use of Technology (UTAUT) model by integrating composite moderators. Employing structural equation modelling (SEM) and a Multiple Indicators Multiple Causes (MIMIC) model, the research tests six hypotheses using data collected from 305 urban Indian respondents, analysing the moderating effects of gender, education level, and voluntary internet use. The findings indicate that behavioural intention, social influence, and digital engagement profiles have a positive effect on AI adoption. Students are primarily motivated by high expectations of AI’s performance, ease of use, and the surrounding social context. Additionally, self-empowerment emerges as a critical factor, with students actively seeking to enhance their skills and future career prospects through the utilisation of AI. While higher education levels and voluntary internet use have a positive moderating effect on AI adoption, gender demonstrates a negative moderating effect, underscoring the need to address gender disparities in AI access and usage. This study aims to offer insight into the dynamics of AI adoption among young Indian students. It highlights the necessity for targeted policies that foster inclusive and equitable access to AI technologies. Such initiatives are essential for mitigating gender-related barriers and further empowering students in their digital learning journeys.