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<p>This study introduces the SPARK-AI Model, a standardized framework for integrating artificial intelligence (AI) into 21st-century classrooms through a mixed-methods design. Data were collected from 1676 participants; 568 teachers and 1108 students using the SPARK-AI Model Scale and semi-structured interviews. Factor analysis identified five components: Scaffolded AI Integration, Pedagogical Intentionality, Adaptive Feedback, Responsible Ethical Use, and Knowledge Transformation, explaining 89.78% of the variance. The scale exhibited strong validity and reliability, with coefficients above 0.70. Findings reveal that, although the model is psychometrically robust and moderately accepted, AI use in Nigerian higher education remains limited. Both quantitative and qualitative evidence indicate that AI is mainly employed for peripheral tasks, including plagiarism detection, grading, and resource provision, rather than core instructional activities. Teachers expressed concerns about sustainability and infrastructural limitations, while students were generally optimistic about AI’s potential to enhance interactivity and personalized learning. The study highlights the need for infrastructural investment, targeted teacher training, and strategic pedagogical planning to translate AI’s potential into practice. The SPARK-AI Model provides a theoretical and practical framework for ethically guided, scaffolded, and contextually relevant AI integration in education.</p>

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A standardized framework for structured pedagogy and responsible knowledge (SPARK) Building for integrating artificial intelligence into 21st century classrooms

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月16日

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  • Usani Joseph Ofem,
  • Eunice Ngozi Ajuluchukwu,
  • Stephen Undie,
  • Faith Sylvester Orim,
  • Patricia Akwaya Olom,
  • Joy Adie,
  • James Omaji Ukatu,
  • Asenath Sylvester Ebaye

摘要

This study introduces the SPARK-AI Model, a standardized framework for integrating artificial intelligence (AI) into 21st-century classrooms through a mixed-methods design. Data were collected from 1676 participants; 568 teachers and 1108 students using the SPARK-AI Model Scale and semi-structured interviews. Factor analysis identified five components: Scaffolded AI Integration, Pedagogical Intentionality, Adaptive Feedback, Responsible Ethical Use, and Knowledge Transformation, explaining 89.78% of the variance. The scale exhibited strong validity and reliability, with coefficients above 0.70. Findings reveal that, although the model is psychometrically robust and moderately accepted, AI use in Nigerian higher education remains limited. Both quantitative and qualitative evidence indicate that AI is mainly employed for peripheral tasks, including plagiarism detection, grading, and resource provision, rather than core instructional activities. Teachers expressed concerns about sustainability and infrastructural limitations, while students were generally optimistic about AI’s potential to enhance interactivity and personalized learning. The study highlights the need for infrastructural investment, targeted teacher training, and strategic pedagogical planning to translate AI’s potential into practice. The SPARK-AI Model provides a theoretical and practical framework for ethically guided, scaffolded, and contextually relevant AI integration in education.