Co-Occurrence #2 – Generative AI and Chat-GPT: A Powerful Tool for Educators, but Not Without Challenges (EP.25)

Mayo Clinic Educator's Central - A podcast by Mayo Clinic

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Co-Occurrence #2 - Generative AI and Chat-GPT: A Powerful Tool for Educators, but Not Without Challenges (EP.25) With Jon Fila Can generative artificial intelligence large language models like Chat-GPT be useful to educators? If so, what are some ways it can help us and what should we be careful about relying on it for?  In this episode, author Jon Fila joins host Stacy Craft to explore how generative AI chat models like Chat-GPT can help educators create engaging and personalized content for their students, reduce their workload, foster creativity and collaboration, and increase accessibility. They also discuss the privacy concerns, ethical use, and the working limitations and biases of these models as well as touch on how learner adoption might impact what learning looks like. This episode is Part two of our limited series, "Co-Occurrence," featuring conversations exploring AI and related technologies as well as possible, probably and actual impacts on education. From discussions around what we know, what we hope for, and what is happening concretely today - this limited series will give you some things to ponder and actionable takeaways. Questions? Feedback? Ideas? Contact us at [email protected] Editor: Jaquan Leonard Additional Resources: University of Cambridge - Faculty News; “Chat GPT. We Need to Talk.”   Nakandakari, Fernando. “Chat GPT in Education: Transforming Learning Experiences through AI Conversations.” Jestor (2023): n. pag. Chat-GPT Teaching with AI Toolkit Fila, Jon. Embracing AI: Beyond the Basics Strategies for Educational Transformation. 2023. Mohd Javaid, Abid Haleem, Ravi Pratap Singh, Shahbaz Khan, Ibrahim Haleem Khan, Unlocking the opportunities through ChatGPT Tool towards ameliorating the education system, BenchCouncil Transactions on Benchmarks, Standards and Evaluations, Volume 3, Issue 2, 2023, 100115, ISSN 2772-4859, https://doi.org/10.1016/j.tbench.2023.100115.

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