Natural language processing (NLP) has advanced rapidly in recent years, to the point where algorithms can now generate focused texts that are increasingly indistinguishable from human writing. OpenAI’s Generative Pre-Trained Transformer (GPT-3) has been at the forefront of these developments, with major implications for language-based assessment from K to postgraduate levels. With this technology becoming publically available in January 2021, educators will have to readily confront some difficult realities regarding the assessment and evaluation of critical writing and the nature of both plagiarism and authourship. Beyond GPT-3, there are other text and research generating technologies on the horizon which embolden the impetus for educators and researchers to reconsider the definition of academic integrity.
In this webinar, attendees will explore a short history of text generators, examples of GPT-3 generated texts, and possible ideas and approaches to addressing these technologies practice.
- Understand the current state of algorithmic writing
- Interpret the impact that text generating technology will have on academic integrity
- Generate ideas and approaches to addressing the problematic impacts through curriculum design
Facilitators: Ryan Morrison and Dr. Michael Mindzak, PhD