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A Survey Instrument to Assess Students' AI and Generative AI Knowledge

arXiv 2608.21391 ↗First posted 31 Jul 2026cs.CY cs.AIcited by 0

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Abstract (arXiv)

In this research-to-practice paper we present a survey that can be used to assess students' AI knowledge. As the use of artificial intelligence (AI), including generative artificial intelligence (GenAI), has proliferated, so has the need to educate students about the topic. A range of AI literacy frameworks have been proposed, outlining the essential knowledge that students should have. Alongside, different ways of assessing AI knowledge have been developed. As yet, there is a lack of assessment instruments capable of evaluating multiple forms of student knowledge, including technical concepts, practical applications, and ethical concerns about AI use. In this article, we present a study implementing a comprehensive instrument to assess AI knowledge. The instrument combines measures from multiple scales to capture a range of literacy features and actual knowledge. We implemented the instrument in a higher education setting to assess its viability and usefulness and found that the instrument exhibited useful diagnostic capabilities and was able to identify common misconceptions among students. Although students performed well overall, there was a significant misunderstanding of how AI, especially GenAI systems, work. It also identified a lack of higher-level knowledge. The instrument is publicly available for use by others. We foresee its usefulness as a diagnostic that goes beyond understanding students' attitudes and perceptions of AI and GenAI use and tests multiple aspects of students' knowledge and conceptual understanding. This can enable the development of targeted instruction.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 17 references that are in the map. First posted on arXiv 31 Jul 2026.

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References · 4

  1. 2023MAILS -- Meta AI Literacy Scale: Development and Testing of an AI Literacy Questionnaire Based on Well-Founded Competency Models and Psychological Change- and Meta-Competenciescited by 17
  2. 2024GLAT: The Generative AI Literacy Assessment Testcited by 10
  3. 2024Integrating AI Education in Disciplinary Engineering Fields: Towards a System and Change Perspectivecited by 3
  4. 2024A Roles-based Competency Framework for Integrating Artificial Intelligence (AI) in Engineering Coursescited by 3

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