Pereira Cipriano, B. orcid.org/0000-0002-2017-7511, Petrovska, O. orcid.org/0000-0003-1170-8816, Pombo, N. orcid.org/0000-0001-7797-8849 et al. (9 more authors) (2026) Towards improving CS students' generative AI literacy. In: Proceedings of the 31st ACM Conference on Innovation and Technology in Computer Science Education V. 2. ITiCSE 2026: ACM Conference on Innovation and Technology in Computer Science Education, 10-15 Jul 2026, Madrid, Spain. . ACM, pp. 789-790. ISBN: 9798400726330.
Abstract
The widespread adoption of Generative AI (GenAI) tools by students across different educational levels highlights the need for them to develop robust GenAI literacy, including a working understanding of these systems’ fundamental concepts, their limitations, and implications for responsible use. However, misconceptions about GenAI, such as perceiving these systems as mere search engines or database lookup systems, are commonly observed among students, while the availability of teaching resources remains fragmented, and learning objectives lack alignment. This Working Group aims to design pedagogical resources for computing science instructors, enabling them to develop students’ GenAI literacy. To achieve this, the Working Group will first identify a concise set of GenAI literacy learning objectives informed by instructor experience, research literature, and community input, and subsequently design pedagogical resources aligned with these objectives.
Metadata
| Item Type: | Proceedings Paper |
|---|---|
| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License. https://creativecommons.org/licenses/by/4.0/ |
| Keywords: | GenAI; Large Language Models; computing education; instructional design |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
| Date Deposited: | 15 Jul 2026 16:04 |
| Last Modified: | 15 Jul 2026 16:04 |
| Status: | Published |
| Publisher: | ACM |
| Refereed: | Yes |
| Identification Number: | 10.1145/3803401.3812055 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:243442 |
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Filename: 3803401.3812055.pdf
Licence: CC-BY 4.0

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