Conaldi, Guido ORCID: https://orcid.org/0000-0003-3552-7307 and Mambrini, Francesco (2023) “Please, ChatGPT, write me an essay in my own words...”: can teachers really tell their own students from bots? In: Learning & Teaching Festival 2023 (LTF2023): Business Education into the Future, 22nd Jun, 2023, University of Greenwich, London. (Unpublished)

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Abstract

Building upon the recent contributions of Dwivedi et al. (2023) and De Vita et al. (2023), this paper delivers a critical discussion of the challenges and opportunities associated with the utilization and potential misuse of OpenAI's ChatGPT chatbot in the context of higher education, specifically emphasizing the design and implementation of authentic student assessments. Following a brief evaluation of the impact of early ChatGPT iterations (versions 3.5 and older) on the administration of student evaluations at Greenwich Business School (GBS) in 2023, the authors of this paper posit that current and future versions of generative AI technologies (such as ChatGPT for textual content and DALL-E for visual imagery) are poised to reach levels of sophistication and complexity that have the potential to precipitate a paradigm shift and disruption in "traditional" student assessments. Initial academic discourse surrounding generative AI predominantly pointed at its potential for academic misconduct and subsequent implications for academic integrity. However, the potential to harness the capabilities afforded by generative AI tools may serve as a driving force for the development of authentic assessment paradigms that fully embrace and integrate current and future AI advancements. As future students may inquire whether academic programmes and/or modules "incorporate AI," embracing this technology may inspire them to leverage AI tools to develop their critical thinking skills, learning experiences, employability, and ethical use. The pedagogical practices of educators will likely undergo increased scrutiny as the influence of generative AI permeates academic institutions on a wider scale. Within this context, the authors propose a future research agenda in this field, including potential methodologies applicable within the context of pedagogy in higher education.

Item Type:	Conference or Conference Paper (Paper)
Uncontrolled Keywords:	artificial intelligence in education; authentic assessment; academic integrity; assessment models; AI detection tools computational linguistic analysis
Subjects:	L Education > L Education (General) Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Business Greenwich Business School > Networks and Urban Systems Centre (NUSC)
Last Modified:	02 Dec 2024 15:55
URI:	http://gala.gre.ac.uk/id/eprint/46004

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