In response to growing demand from academics requiring resources on Artificial Intelligence (AI) for their students, Charles Sturt Librarians developed an Open Education Resource (OER) titled Using AI tools at university. This resource aims to equip university students and researchers with the knowledge and skills necessary to utilise AI tools productively, ethically and responsibly. Our project, undertaken collaboratively by Charles Sturt Librarians, seeks to democratise access to AI literacy.
Generative AI technologies and AI tools for research are increasingly prevalent in academic settings, yet students and researchers often lack guidance on the responsible and ethical use and how they can be used productively. Our OER addresses this gap by providing comprehensive information on AI tools, their applications, and ethical considerations. The resource emphasises the importance of understanding AI biases, data privacy, and the ethical implications of AI-driven decisions.
The benefits of OER for students are extensive. Research indicates that using OER enhances student learning (Cheung, 2019) and serves as an effective learning intervention by providing equal access to educational resources for all students (Grimaldi et al., 2019). Open textbooks can be continuously and easily updated to remain relevant, which is especially crucial given the rapid advancements in AI. Considering the importance of equitable access to information for our students and the challenges posed by traditional publishing models, such as high costs and restrictive licensing, OER offers valuable resources that ensure equitable access for all students.
The Pressbooks platform was used and incorporated interactive media and active learning through H5P. It seamlessly embedded in the learning management system plus allowed direct linking to specific chapters, when students had assessment requirements requiring specific AI literate information and evaluation. The project not only provided specific resources at the request of academics needing information on AI use for their students assessment tasks but was expanded to provide a complete AI literacy resource that can be used by all undertaking research. It covers algorithmic literacy (Ridley & Pawlick-Potts, 2021), understanding bias, developing competency in critical ignoring (Kozyreva et al., 2023), detecting hallucinations and communicating with AI through effective prompt engineering (Lo, 2023).
The project also had a secondary objective to familarise Librarians with developing content for an OER with then having a locally produced OER to demonstrate to academics. This initiative aligns with the broader movement towards open education and the sharing of knowledge across institutions.
Our OER, Using AI tools at university, empowers students from diverse backgrounds to engage actively with AI tools. By breaking down complex concepts into understandable modules, we foster responsible AI use and encourage student contributions to AI development. Moving forward, we aim to expand this resource and integrate it into existing digital literacy modules across disciplines. This integration will support the development of critical thinking and digital literacy skills, preparing students for the evolving digital landscape.
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[Session 3D]: Digital Capability, Artificial IntelligenceReferencesCheung, S. K. S. (2019). A Study on the University Students’ Use of Open Educational Resources for Learning Purposes. Technology in Education: Pedagogical Innovations (pp. 146-155). Springer Singapore.
Grimaldi, P. J., Basu Mallick, D., Waters, A. E., & Baraniuk, R. G. (2019). Do open educational resources improve student learning? Implications of the access hypothesis. PloS One, 14(3), e0212508.
https://doi.org/10.1371/journal.pone.0212508 Kozyreva, A., Wineburg, S., Lewandowsky, S., & Hertwig, R. (2023). Critical ignoring as a core competence for digital citizens. Current Directions in Psychological Science, 32(1), 81–88.
https://doi.org/10.1177/09637214221121570 Lo, L. S. (2023). The CLEAR path: A framework for enhancing information literacy through prompt engineering. The Journal of Academic Librarianship, 49(4), 102720.
https://doi.org/10.1016/j.acalib.2023.102720 Ridley, M., & Pawlick-Potts, D. (2021). Algorithmic literacy and the role for libraries. Information Technology and Libraries (Online), 40(2), 1-15.
https://doi.org/10.6017/ital.v40i2.12963Author KeywordsArtificial Intelligence, Algorithmic Literacy, Open Educational Resources, GenAI, Digital Literacy, AI Literacy, OER, Open Textbooks
