Artificial intelligence and academic integrity: The ethics of teaching and learning with algorithmic writing technologies
Date
2023-01-25
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
The higher education landscape is changing rapidly, with artificial intelligence tools being increasingly available to students, as well as the general public. In this session, we present basic information about artificial intelligence and algorithmic writing technologies such as GPT-3 and other tools. We will contemplate the broader impact of artificial intelligence on teaching, learning, assessment, and academic integrity.
Debating whether the use of artificial might or might not constitute academic misconduct is an overly reductionist and polarizing approach to the debate. Our value proposition is that artificial intelligence is already here and as educators we have a responsibility to ensure we are taking an ethical approach about how it can be used for teaching, learning, and assessment. We discuss how artificial intelligence tools can be used to support ethical and equitable approaches to student success.
Keywords: artificial intelligence, academic integrity, academic misconduct, plagiarism, GPT-3, ChatGPT, large language models (LLM), algorithmic writing, transdisciplinary, transdisciplinarity
Cite this presentation as:
Eaton, S. E., Brennan, R., Wiens, J., & McDermott, B. (2023, January 25). Artificial intelligence and academic integrity: The ethics of teaching and learning with algorithmic writing technologies Invited talk for the Webinar Series organized by the Faculty Merit Committee (FMC) Learning Development Team, Bournemouth University, UK.
Description
Keywords
artificial intelligence, academic integrity, academic dishonesty, GPT-3, ChatGPT, large language models, algorithmic writing, transdisciplinarity
Citation
Eaton, S. E., Brennan, R., Wiens, J., & McDermott, B. (2023, January 25). Artificial intelligence and academic integrity: The ethics of teaching and learning with algorithmic writing technologies. https://prism.ucalgary.ca/handle/1880/115769