Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale
By Bingcheng Wang, Pei-Luen Patrick Rau, Tianyi Yuan. Behavior and Information Technology, 2022
608 citations recorded by the source corpus.
ABSTRACT As artificial intelligence (AI) became a part of daily life, it has become important to determine user competence in using AI technology. Here, we propose the concept of AI literacy and develop a quantitative scale for obtaining accurate data regarding the AI literacy of ordinary users. We first identified the primary core constructs of AI literacy, including awareness, use, evaluation, and ethics. Next, we generated 65 items to capture these four constructs; only 31 items were retained after a three-step content validation process. Then, we conducted a survey, and collected two samples of data. By reducing the number of items using the first sample and performing reliability and validity tests on the second sample, we obtained a 12-item instrument for the quantitative measurement of AI literacy. The results confirmed that the proposed four-construct model is an adequate representation of AI literacy. Further, AI literacy is significantly related to digital literacy, attitude towards robots, and users’ daily usage of AI. This study will not only aid researchers in understanding how user competence in using AI technology affects human–AI interactions but will also help designers develop AI applications that are aligned with the AI literacy levels of the target users.
Subfields: Artificial Intelligence, Safety Research
View Paper: https://www.semanticscholar.org/paper/767098d2e324258fec0d33148eec44f7955b56ce
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Citations in the corpus
- Factors Influencing University Students’ Behavioral Intention to Use Generative Artificial Intelligence: Integrating the Theory of Planned Behavior and AI Literacy (2024, unknown): “This resonates with the findings of Wang et al. (2023), who emphasize that the level of AI literacy shapes university students’ attitudes toward AI.”
- MAILS - Meta AI Literacy Scale: Development and Testing of an AI Literacy Questionnaire Based on Well-Founded Competency Models and Psychological Change- and Meta-Competencies (2023, background): “In general, few measurement instruments with initial validations and theoretical foundations exist (Karaca et al., 2021; Wang et al., 2022), besides practically-oriented instruments often developed for a specific intervention study in an educational context.”