AI Literacy in Higher Education: Theory and Design
| Authors | |
|---|---|
| Year of publication | 2024 |
| Type | Article in Proceedings |
| Conference | New Media Pedagogy: Research Trends, Methodological Challenges, and Successful Implementations. NMP 2023. Communications in Computer and Information Science |
| MU Faculty or unit | |
| Citation | |
| web | https://link.springer.com/chapter/10.1007/978-3-031-63235-8_24 |
| Doi | http://dx.doi.org/10.1007/978-3-031-63235-8_24 |
| Keywords | AI literacy; Artificial intelligence; ChatGPT; Competency framework; Delphi method; Google Bard; Information literacy; participatory research methods |
| Description | The study focused on defining AI literacy in the context of university education. New forms of education and content are required in a rapidly changing technological environment. Students may feel uneasy about the changes that the university and their everyday world bring. This study analyses the results of a workshop in which students (18) with deep education in AI were asked to work on a framework for AI literacy using the Delphi method. The students defined ten areas essential to AI literacy: general overview and theory; ethics and social impacts; learning and trend tracking; technological skills; practical experience; critical thinking and information literacy; authorship and plagiarism; privacy and security; and experience with tools. |