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<p>This study examines ChatGPT adoption among higher education students in Türkiye and Poland through an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework that also includes personal innovativeness. It compares country-specific adoption patterns across the two samples and offers a cautious contextual interpretation of the observed differences. Survey data were collected from 634 students in Türkiye and 531 students in Poland, and the proposed relationships were examined using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that the extended UTAUT2 framework was empirically useful in both samples, although the relative prominence of specific predictors differed across them. Descriptively, Performance Expectancy (β = 0.258, <i>p</i> &lt; 0.001) and Personal Innovativeness showed larger coefficients in the Polish sample, whereas Effort Expectancy (β = 0.104, <i>p</i> &lt; 0.01) and Social Influence (β = 0.199, <i>p</i> &lt; 0.001) appeared more prominent in the Turkish sample. Price Value showed a statistically significant reversed association with Behavioral Intention in Türkiye (β = -0.187, <i>p</i> &lt; 0.001), whereas the association was positive in Poland (β = 0.094, <i>p</i> &lt; 0.01). Habit emerged as one of the strongest predictors in the model and was positively associated with both Behavioral Intention and Use Behavior in the two samples. Taken together, the findings suggest that ChatGPT adoption in higher education is shaped by a combination of perceived usefulness, ease of use, social and practical support, habitual use, and context-sensitive evaluations of value. The study contributes to the growing literature on generative AI in higher education by showing that the same theoretical framework can reveal different adoption patterns across two national samples, while also highlighting the need for context-sensitive implementation strategies. The findings offer practical implications for higher education institutions, educators, and policy developers seeking to support the responsible and effective use of ChatGPT.</p>

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Adoption of ChatGPT for Learning-Related Information Access: A Comparative UTAUT2 Analysis of Turkish and Polish University Students

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月28日

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  • Ali İbrahim Can Gözüm,
  • Artur Strzelecki,
  • Ümit Ünsal Kaya,
  • Murat Taşdan

摘要

This study examines ChatGPT adoption among higher education students in Türkiye and Poland through an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework that also includes personal innovativeness. It compares country-specific adoption patterns across the two samples and offers a cautious contextual interpretation of the observed differences. Survey data were collected from 634 students in Türkiye and 531 students in Poland, and the proposed relationships were examined using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that the extended UTAUT2 framework was empirically useful in both samples, although the relative prominence of specific predictors differed across them. Descriptively, Performance Expectancy (β = 0.258, p < 0.001) and Personal Innovativeness showed larger coefficients in the Polish sample, whereas Effort Expectancy (β = 0.104, p < 0.01) and Social Influence (β = 0.199, p < 0.001) appeared more prominent in the Turkish sample. Price Value showed a statistically significant reversed association with Behavioral Intention in Türkiye (β = -0.187, p < 0.001), whereas the association was positive in Poland (β = 0.094, p < 0.01). Habit emerged as one of the strongest predictors in the model and was positively associated with both Behavioral Intention and Use Behavior in the two samples. Taken together, the findings suggest that ChatGPT adoption in higher education is shaped by a combination of perceived usefulness, ease of use, social and practical support, habitual use, and context-sensitive evaluations of value. The study contributes to the growing literature on generative AI in higher education by showing that the same theoretical framework can reveal different adoption patterns across two national samples, while also highlighting the need for context-sensitive implementation strategies. The findings offer practical implications for higher education institutions, educators, and policy developers seeking to support the responsible and effective use of ChatGPT.