Development of an AI literacy self-assessment questionnaire in upper primary school students

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Authors: Kawin Thianwan, Sanit Srikoon
Cited by: 0
References: 19

Abstract

This study presents the development and validation of the AI Literacy Self-Assessment Questionnaire (AIL-SAQ) for upper primary school students. The instrument, based on established AI literacy frameworks, measures three dimensions: Learning About AI, Learning About How AI Works, and Learning for Life with AI. Study 1 (n = 335) employed Exploratory Factor Analysis to explore a three-factor structure. Study 2 (n = 579) used Confirmatory Factor Analysis, revealing excellent model fit (χ 2 = 105.066, df = 87, p = .091, CFI = .994, TLI = .993, RMSEA = .019, SRMR = .022) and high internal consistency (Cronbach's α = .934). Standardized factor loadings (.638–.774) and variance (R 2 = .407–.599) further support the AIL-SAQ's validity and reliability. • Developed and validated the AI Literacy Self-Assessment Questionnaire (AIL-SAQ) to assess AI literacy in upper primary students. • Identified and confirmed three key AI literacy dimensions: Learning About AI (LAI), Learning About How AI Works (HAI), and Learning for Life with AI (FAI). • Achieved strong construct validity and reliability with first-order Confirmatory Factor Analysis (CFA) analysis. • Addressed the lack of age-appropriate tools for measuring AI literacy in education. • Established a novel framework to enhance AI literacy assessment and curriculum design.

Fields of Study & Subjects

Teaching and Learning Programming Ethics and Social Impacts of AI Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
Social Sciences & Humanities Open
Volume
13
Pages
102424–102424
Publication date
6 January 2026
Language
EN