Developing and Validating an AI Literacy Instrument for Elementary School Students: A Psychometric Study Using the ADDIE Framework
Artificial intelligence (AI) literacy has emerged as a critical competency in elementary education as learners increasingly engage with AI-mediated and technology-rich learning environments. This study developed and validated a multidimensional AI literacy instrument for elementary school students using a research and development approach grounded in the ADDIE framework and informed by AI literacy, constructivist learning, and digital citizenship theories. The instrument comprised five dimensions: AI recognition, conceptual understanding, functional application, evaluation and creation, and AI ethics. Content validation by four experts demonstrated strong theoretical relevance across all dimensions. Empirical testing involving 250 Indonesian elementary school students examined the instrument's psychometric properties. Exploratory factor analysis supported a five-factor structure with acceptable factor loadings and sampling adequacy (KMO > .80; Bartlett's test, p < .001), explaining a substantial proportion of total variance. Reliability analysis indicated satisfactory internal consistency across retained subscales (Cronbach's α > .70), although conceptual understanding required minor item revision. Descriptive findings revealed stronger competencies in ethical AI use and functional application than in conceptual understanding of AI processes. The study contributes a psychometrically grounded and developmentally appropriate instrument supporting AI literacy assessment, curriculum innovation, instructional evaluation, and responsible AI integration within primary education contexts for early twenty-first-century educational transformation.
Authors
- Torang Siregar (ORCID: https://orcid.org/0009-0006-1416-0461)
- Mhel Cedric D. Bendo (ORCID: https://orcid.org/0009-0004-6873-3910)
Institutions
- Polytechnic University of the Philippines (PH)
Publication Details
- Journal
- Knowledge Commons (Lakehead University)
- Published
- 2026-09-12
- DOI
- https://doi.org/10.17613/mkc7m-2rc52
- Primary Topic
- Teaching and Learning Programming
- Type
- article
- Field-Weighted Citation Impact
- 0.00