The use of artificial intelligence (AI) tools in secondary education is emerging as a valuable resource for supporting learning, with the potential to transform students’ relationship with information and, consequently, with knowledge. This study examined the relationships between academic engagement, student motivation, AI usage, and perceived usefulness of these technologies among a group of secondary school students. A quantitative, cross-sectional design was used, applying adapted and validated scales to assess the mentioned variables. The sample consisted of 164 female students aged 12 to 16 from a privately managed educational institution in Arequipa, Peru. Statistical analysis was conducted using structural equation modeling (PLS-SEM), with bootstrapping (5,000 subsamples) to estimate the significance of the relationships. The findings suggest that both motivation and academic engagement are linked to the frequency and depth of AI use, which in turn appears to influence students’ perceived value of these technologies. Mediating relationships were also identified, providing a more comprehensive view of the factors that shape the meaningful integration of AI in school settings. This study offers empirical support for the development of pedagogical strategies aimed at fostering a critical and formative use of AI in secondary education.

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Engagement, Motivation, and Use of Artificial Intelligence in Secondary Education

  • Ygnacio Salvador Tomaylla-Quispe,
  • Olger Albino Gutierrez-Aguilar,
  • Sandra Chicana-Huanca,
  • Francisco Saravia-Ramos

摘要

The use of artificial intelligence (AI) tools in secondary education is emerging as a valuable resource for supporting learning, with the potential to transform students’ relationship with information and, consequently, with knowledge. This study examined the relationships between academic engagement, student motivation, AI usage, and perceived usefulness of these technologies among a group of secondary school students. A quantitative, cross-sectional design was used, applying adapted and validated scales to assess the mentioned variables. The sample consisted of 164 female students aged 12 to 16 from a privately managed educational institution in Arequipa, Peru. Statistical analysis was conducted using structural equation modeling (PLS-SEM), with bootstrapping (5,000 subsamples) to estimate the significance of the relationships. The findings suggest that both motivation and academic engagement are linked to the frequency and depth of AI use, which in turn appears to influence students’ perceived value of these technologies. Mediating relationships were also identified, providing a more comprehensive view of the factors that shape the meaningful integration of AI in school settings. This study offers empirical support for the development of pedagogical strategies aimed at fostering a critical and formative use of AI in secondary education.