Artificial Intelligence Literacy Questionnaire (AILQ)

Description, Purpose, and Construct

The Artificial Intelligence Literacy Questionnaire (AILQ; Ng et al., 2024) is a self-report measure designed to assess secondary school students’ AI literacy across affective, behavioral, cognitive, and ethical (ABCE) dimensions. It was developed based on AI literacy frameworks, identifying competencies in four areas: (1) affective learning (intrinsic motivation and self-efficacy/confidence), (2) behavioral learning (behavioral commitment and collaboration), (3) cognitive learning (knowledge application, evaluation, and creation), and (4) ethical learning. The initial version contained 60 items and underwent expert validation, qualitative interviews, and a pilot study. After exploratory and confirmatory factor analyses, a refined version with 32 items was established. Findings on reliability and validity were reported.

Author, Affiliation, and Contact Information

• Ng, Davy Tsz Kit (Faculty of Education, University of Hong Kong) – ORCID: 0000-0002-2380-7814
• Wu, Wenjie (Faculty of Education, Chinese University of Hong Kong)
• Leung, Jac Ka Lok (Division of Integrative Systems and Design, Hong Kong University of Science and Technology) – ORCID: 0000-0001-6490-7005
• Chiu, Thomas Kin Fung (Faculty of Education, Chinese University of Hong Kong) – ORCID: 0000-0003-2887-5477
• Chu, Samuel Kai Wah (School of Nursing and Health Studies, Hong Kong Metropolitan University) – ORCID: 0000-0003-1557-2776
• Corresponding Author: Ng, Davy Tsz Kit – [email protected]

Test Type, Format, and Factors

This original inventory/questionnaire consists of 32 items measured on a 5-point Likert scale ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (5). The four key dimensions assessed are:

• Affective learning: Intrinsic motivation, self-efficacy, confidence, career interest
• Behavioral learning: Behavioral commitment, collaboration
• Cognitive learning: Knowledge application, evaluation, and creation
• Ethical learning: AI ethics

Reliability, Validity, and Factor Analysis

• Internal Consistency: Cronbach’s alpha = 0.93
• Convergent Validity: AVE exceeded 0.50 for all latent factors except intrinsic motivation (0.44) and AI ethics (0.46).
• Discriminant Validity: Assessed using Heterotrait–Monotrait ratio of correlations (HTMT), with values below 0.85 considered acceptable.
• Exploratory Factor Analysis: The four factors explained 51.41% of the total variance.
• Confirmatory Factor Analysis: Model comparison favored the second-order model (χ²(452) = 1001.54, p < 0.01; RMSEA = 0.06; CFI = 0.92; TLI = 0.91; SRMR = 0.06) over the third-order model.

Population, Age Group, and Location

• Age Range: 12-17 years
• Population: Human; Male; Female
• Location: Hong Kong
• Respondents: Secondary school students

Keywords and Index Terms

• Keywords: Affective Learning, Behavioral Learning, Cognitive Learning, Ethical Learning, Artificial Intelligence Literacy, Secondary Students
• Index Terms: Artificial Intelligence, Educational Measures, High School Students, Secondary Education, Digital Literacy, Artificial Intelligence (Attitudes Toward)

Files and Availability

No file available for download.

Reference

Ng, D. T. K., Wu, W., Leung, J. K. L., Chiu, T. K. F., & Chu, S. K. W. (2024). Design and validation of the AI Literacy Questionnaire: The affective, behavioural, cognitive and ethical approach. British Journal of Educational Technology, 55(3), 1082–1104. https://doi.org/10.1111/bjet.13411