This thesis has investigated what impact generative AI may have on higher education. Using a combination of a systematic literature study and interviews with representatives from four (4) large universities in Sweden. The findings indicate that generative AI is already a disruptive technology in teaching and learning in higher education, and that students now more easily can cheat or “mislead the examiner” using generative AI, for example by presenting ChatGPT generated text as text written by the students themselves. Even though there are some negatives with generative AI, this thesis shows that the Universities are better off embracing this technology instead of trying to work against it. So, what are the positives with generative AI in education? The fact that students can now converse with someone no matter their background, the fact that students can learn by using ChatGPT (if they are taught how to use it properly), the fact that learning how to use ChatGPT might increase the student’s efficiency and therefore increase their attractiveness on the work market when graduating. All of these benefits come with a big WARNING though. That warning is that higher education must teach the students that these tools are not miracle workers. That the tools can be wrong, and it is important that students learn how to question and criticise what is generated. Higher education has a responsibility to introduce the tools tempered by the understanding that they are not a replacement for knowledge, but only a powerful aid to enhance the knowledge that the students already possess. Finally, the study has been conducted during a particularly expansive period for generative AI and the reader should realise that the findings within this thesis represent early results in a young area of research.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mau-60315 |
| Date | January 2023 |
| Creators | Simonsson, Eric |
| Publisher | Malmö universitet, Fakulteten för teknik och samhälle (TS) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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