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<p>This study examines how anxiety and self-efficacy affect ChatGPT adoption among higher education students in Jaipur, India, positioned at the intersection of educational technology, AI integration, and psychological readiness theory. The investigation explores how these psychological factors influence ChatGPT adoption intentions and behaviors both directly and through interaction effects, employing the UTAUT-3 framework to advance understanding of technology acceptance mechanisms. Three primary factors motivated this research: the rapid deployment of AI tools like ChatGPT necessitates urgent understanding of psychological facilitators and barriers to effective educational integration; growing concerns about potential AI-related digital divides require empirical investigation; and the gap in literature examining psychological moderating mechanisms in AI adoption contexts demands theoretical advancement. Using a mixed-methods sequential explanatory design, this study surveyed 210 students equally distributed between government (<i>n</i> = 105) and private (<i>n</i> = 105) higher education institutions in Jaipur, India, followed by qualitative interviews to contextualize quantitative findings. Results confirm self-efficacy as a strong positive predictor of ChatGPT adoption (β = 0.58, <i>p</i> &lt; 0.001) while establishing anxiety as a significant barrier (β = −0.34, <i>p</i> &lt; 0.001), with self-efficacy demonstrating a crucial buffering effect that mitigates anxiety’s negative influence on adoption intentions (interaction effect: β = 0.23, <i>p</i> &lt; 0.01). The comprehensive model achieved substantial explanatory power (R² = 0.672 for behavioral intention, R² = 0.648 for use behavior), validating the integrated psychological-technological approach and revealing that students with high self-efficacy maintain positive adoption intentions despite elevated anxiety levels, while those with low self-efficacy experience compounded negative effects when anxiety is present. Educational managers and technology implementation teams should prioritize self-efficacy enhancement over anxiety reduction when planning AI adoption interventions, as building students’ confidence in AI competencies provides more sustainable adoption outcomes than merely addressing technological concerns. This study advances technology acceptance theory by empirically establishing psychological factors as central rather than peripheral determinants in AI adoption processes, while identifying and quantifying the buffering mechanism through which self-efficacy mitigates anxiety’s detrimental effects, thereby providing theoretical foundations for understanding psychological resilience in educational technology adoption contexts.</p>

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Examining the role of anxiety and self-efficacy as psychological barriers to ChatGPT adoption in academic contexts

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月26日

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  • R K Tailor,
  • Drashti Tailor

摘要

This study examines how anxiety and self-efficacy affect ChatGPT adoption among higher education students in Jaipur, India, positioned at the intersection of educational technology, AI integration, and psychological readiness theory. The investigation explores how these psychological factors influence ChatGPT adoption intentions and behaviors both directly and through interaction effects, employing the UTAUT-3 framework to advance understanding of technology acceptance mechanisms. Three primary factors motivated this research: the rapid deployment of AI tools like ChatGPT necessitates urgent understanding of psychological facilitators and barriers to effective educational integration; growing concerns about potential AI-related digital divides require empirical investigation; and the gap in literature examining psychological moderating mechanisms in AI adoption contexts demands theoretical advancement. Using a mixed-methods sequential explanatory design, this study surveyed 210 students equally distributed between government (n = 105) and private (n = 105) higher education institutions in Jaipur, India, followed by qualitative interviews to contextualize quantitative findings. Results confirm self-efficacy as a strong positive predictor of ChatGPT adoption (β = 0.58, p < 0.001) while establishing anxiety as a significant barrier (β = −0.34, p < 0.001), with self-efficacy demonstrating a crucial buffering effect that mitigates anxiety’s negative influence on adoption intentions (interaction effect: β = 0.23, p < 0.01). The comprehensive model achieved substantial explanatory power (R² = 0.672 for behavioral intention, R² = 0.648 for use behavior), validating the integrated psychological-technological approach and revealing that students with high self-efficacy maintain positive adoption intentions despite elevated anxiety levels, while those with low self-efficacy experience compounded negative effects when anxiety is present. Educational managers and technology implementation teams should prioritize self-efficacy enhancement over anxiety reduction when planning AI adoption interventions, as building students’ confidence in AI competencies provides more sustainable adoption outcomes than merely addressing technological concerns. This study advances technology acceptance theory by empirically establishing psychological factors as central rather than peripheral determinants in AI adoption processes, while identifying and quantifying the buffering mechanism through which self-efficacy mitigates anxiety’s detrimental effects, thereby providing theoretical foundations for understanding psychological resilience in educational technology adoption contexts.