Document Type

Journal Article

Publication Title

Journal of University Teaching and Learning Practice

Volume

20

Issue

6

Publisher

University of Wollongong

School

Centre for Learning and Teaching

RAS ID

60332

Comments

Kelly, A., Sullivan, M., & Strampel, K. (2023). Generative artificial intelligence: University student awareness, experience, and confidence in use across disciplines. Journal of University Teaching & Learning Practice, 20(6), 12. https://doi.org/10.53761/1.20.6.12

Abstract

The global higher education sector has been significantly disrupted by the proliferation of generative artificial intelligence tools such as ChatGPT, especially in relation to its implications for assessment. However, few studies to date have explored student perspectives on these tools. This article reports on one of the first large-scale quantitative studies of student views on generative artificial intelligence at an Australian university (n = 1,135). When the survey was conducted, most students had low knowledge, experience, and confidence in using these tools. These results varied across disciplines and across some student sub-groups, such as mature-age students and international students. Confidence appeared to increase with experience, although the data also revealed a portion of students that have never used these tools yet still felt confident in using them. In exploring these results, this article aims to shed new light on this fast-evolving landscape and inform the future direction of supporting students to engage with generative artificial intelligence tools appropriately. Practitioner Notes 1. Students need to be explicitly taught how to use generative artificial intelligence tools appropriately. 2. Learning activities that build student skills in using generative artificial intelligence should be embedded into curricula. 3. The ways in which students learn how to use generative artificial intelligence will need to vary based on the needs of each disciplinary area. 4. Student reports of self-confidence in using generative artificial intelligence may be overstated. 5. Assessment tasks need to be redesigned to reduce the academic integrity risks associated with using generative artificial intelligence.

DOI

10.53761/1.20.6.12

Access Rights

free_to_read

Creative Commons License

Creative Commons Attribution-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 License.

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