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This study examined the aspects affecting students’ ongoing utilization of Generative AI (GAI) in education, highlighting the significance of prompting capability within the Technology Acceptance Model (TAM) framework. The study sought to examine the influence of prompting capability on perceived utility, perceived simplicity of use, attitude, and the intention to continue utilizing GAI tools. A quantitative methodology was utilized, including a standardized questionnaire administered to 312 university students in Vietnam. Data were examined utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the measurement and structural models. The findings indicated that all hypotheses were validated, showing that prompting capability greatly impacted perceived usefulness and perceived simplicity of use, which subsequently enhanced attitude and sustained desire to utilize GAI. Moreover, attitude and perceived utility surfaced as crucial factors influencing students’ ongoing involvement with GAI tools. The results underscored the significance of user competencies, especially prompting ability, in optimizing the educational advantages of GAI. This study enhances the literature by integrating prompting Capacity into the Technology Acceptance Model (TAM) and provides practical insights for educators and policymakers to improve the acceptance of Generative Artificial Intelligence (GAI) in educational settings.

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Understanding Students’ Continued Use of Generative AI in Learning: The Critical Role of Prompting Capacity

  • 会议论文

  • 发表日期：

    2025年

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  • Ai-Van Huynh,
  • Bui Thanh Khoa

摘要

This study examined the aspects affecting students’ ongoing utilization of Generative AI (GAI) in education, highlighting the significance of prompting capability within the Technology Acceptance Model (TAM) framework. The study sought to examine the influence of prompting capability on perceived utility, perceived simplicity of use, attitude, and the intention to continue utilizing GAI tools. A quantitative methodology was utilized, including a standardized questionnaire administered to 312 university students in Vietnam. Data were examined utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the measurement and structural models. The findings indicated that all hypotheses were validated, showing that prompting capability greatly impacted perceived usefulness and perceived simplicity of use, which subsequently enhanced attitude and sustained desire to utilize GAI. Moreover, attitude and perceived utility surfaced as crucial factors influencing students’ ongoing involvement with GAI tools. The results underscored the significance of user competencies, especially prompting ability, in optimizing the educational advantages of GAI. This study enhances the literature by integrating prompting Capacity into the Technology Acceptance Model (TAM) and provides practical insights for educators and policymakers to improve the acceptance of Generative Artificial Intelligence (GAI) in educational settings.