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<p>This study presents the development and validation of the AI Literacy Questionnaire for Children (AILQ-C), a psychometrically robust instrument designed to assess elementary students’ multidimensional awareness, attitudes, and perceived competencies related to artificial intelligence. Grounded in UNESCO’s AI Competency Framework, the AILQ-C captures human-centred, ethical, practical, and system-design dimensions aligned with the framework’s developmental progression (Understand–Apply–Create), focusing on students’ perceptions and orientations toward these competencies. An initial 30-item pool, derived from theoretical review and expert input, underwent face and content validation, cognitive interviews, and pilot testing, resulting in a refined 24-item instrument. Field testing with 480 students (Grades 4–8; Mage = 11.2, SD = 1.1; 51% girls) from ten schools across diverse socio-economic settings in eastern India confirmed a four-factor structure, with strong item discrimination (DI = 0.42–0.76), high internal consistency (α = 0.84–0.89), and robust convergent and discriminant validity. Measurement invariance analyses demonstrated configural, metric, and scalar invariance across gender and grade levels. While validated within an Indian school context, the instrument provides a developmentally appropriate tool for examining children’s AI literacy profiles and informing future research and educational interventions. The AILQ-C may support teachers, researchers, and policymakers in exploring students’ engagement with AI-related concepts and identifying areas for targeted learning support.</p>

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Measuring AI literacy in elementary students: development and validation of a psychometric instrument

  • 期刊论文

  • 发表日期：

    2026年5月6日

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  • Arnab Kundu,
  • Tripti Bej

摘要

This study presents the development and validation of the AI Literacy Questionnaire for Children (AILQ-C), a psychometrically robust instrument designed to assess elementary students’ multidimensional awareness, attitudes, and perceived competencies related to artificial intelligence. Grounded in UNESCO’s AI Competency Framework, the AILQ-C captures human-centred, ethical, practical, and system-design dimensions aligned with the framework’s developmental progression (Understand–Apply–Create), focusing on students’ perceptions and orientations toward these competencies. An initial 30-item pool, derived from theoretical review and expert input, underwent face and content validation, cognitive interviews, and pilot testing, resulting in a refined 24-item instrument. Field testing with 480 students (Grades 4–8; Mage = 11.2, SD = 1.1; 51% girls) from ten schools across diverse socio-economic settings in eastern India confirmed a four-factor structure, with strong item discrimination (DI = 0.42–0.76), high internal consistency (α = 0.84–0.89), and robust convergent and discriminant validity. Measurement invariance analyses demonstrated configural, metric, and scalar invariance across gender and grade levels. While validated within an Indian school context, the instrument provides a developmentally appropriate tool for examining children’s AI literacy profiles and informing future research and educational interventions. The AILQ-C may support teachers, researchers, and policymakers in exploring students’ engagement with AI-related concepts and identifying areas for targeted learning support.