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<p>The rapid growth of generative Artificial Intelligence (AI) tools, particularly ChatGPT, has brought significant changes to academic learning while also raising questions regarding differences in its adoption among students. Grounded in the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), this study examines gender as a control variable and its influence on students’ perceived knowledge levels, perceived challenges, and willingness to use ChatGPT. Using a quantitative survey design, data were collected from 179 MBA students across higher education institutions in Bengaluru through a validated instrument adapted from Chan and Hu [10]. Structural Equation Modelling (SEM) with Bias-Corrected Percentile Bootstrap (5000 resamples) was employed for data analysis using JASP software. The findings reveal that ChatGPT Usage Knowledge significantly and positively influences Willingness to use (β = 0.345, <i>p</i> &lt; 0.05), supporting the core assumptions of TAM. The results further indicate that the ChatGPT Usage Knowledge positively influences perceived Adoption Challenges (β = 0.345, <i>p</i> = 0.001), suggesting that greater familiarity with AI tools increases students’ awareness of associated complexities and limitations. In addition, Willingness significantly predicts Challenges (β = 0.182, <i>p</i> = 0.027), implying that increased engagement with ChatGPT may expose students to a wider range of practical and academic concerns. However, contrary to the gender-based assumptions proposed in UTAUT, Gender did not show a significant influence on Knowledge, Challenges, or Willingness. This suggests that gender-based differences in perceptions towards AI tools may be diminishing among postgraduate students in urban academic environments. The study provides useful implications for educators and policymakers in developing knowledge-oriented and gender-inclusive approaches for the effective integration of AI tools in higher education.</p>

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Gender effects on ChatGPT usage knowledge and adoption challenges among MBA students

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月21日

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  • Delina G,
  • Magesh Kumar,
  • Rashmi BH,
  • Gaddam Rahul Paul

摘要

The rapid growth of generative Artificial Intelligence (AI) tools, particularly ChatGPT, has brought significant changes to academic learning while also raising questions regarding differences in its adoption among students. Grounded in the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), this study examines gender as a control variable and its influence on students’ perceived knowledge levels, perceived challenges, and willingness to use ChatGPT. Using a quantitative survey design, data were collected from 179 MBA students across higher education institutions in Bengaluru through a validated instrument adapted from Chan and Hu [10]. Structural Equation Modelling (SEM) with Bias-Corrected Percentile Bootstrap (5000 resamples) was employed for data analysis using JASP software. The findings reveal that ChatGPT Usage Knowledge significantly and positively influences Willingness to use (β = 0.345, p < 0.05), supporting the core assumptions of TAM. The results further indicate that the ChatGPT Usage Knowledge positively influences perceived Adoption Challenges (β = 0.345, p = 0.001), suggesting that greater familiarity with AI tools increases students’ awareness of associated complexities and limitations. In addition, Willingness significantly predicts Challenges (β = 0.182, p = 0.027), implying that increased engagement with ChatGPT may expose students to a wider range of practical and academic concerns. However, contrary to the gender-based assumptions proposed in UTAUT, Gender did not show a significant influence on Knowledge, Challenges, or Willingness. This suggests that gender-based differences in perceptions towards AI tools may be diminishing among postgraduate students in urban academic environments. The study provides useful implications for educators and policymakers in developing knowledge-oriented and gender-inclusive approaches for the effective integration of AI tools in higher education.