This event will be held on Zoom, with an in-person viewing party in the iSchool Terrace Lab. Please register below to receive the Zoom link to the event.
Contemporary large language models (LLMs), though the culmination of years-long effort, have exploded into much greater use in education in the last year. LLMs provide a wide range of opportunities, as seen in tools like Khanmigo, and unique challenges compared to previous-generation technologies, such as hallucinations, irreproducibility, and perspective-switching.
In this talk, Dr. Ryan Baker will discuss ongoing efforts at the Penn Center for Learning Analytics to leverage large language models for educational research and development, focusing on their efforts to use LLMs to identify meaningful categories in texts. He will discuss three projects within this talk. In the first project, ChatGPT is used to attempt to produce better models multidimensionally assessing student scientific inquiry skill from their explanations. In the second project, mixed-initiative qualitative coding was conducted, partnering humans with ChatGPT in different ways, and studying which combinations produce the greatest complementarities. In the third project, LLMs were used to provide feedback for student errors within introductory computer programming. Dr. Baker will discuss the successes and failures of these approaches and what lessons we can draw from these projects for the use of ChatGPT for assessing text responses.