Penn State statisticians awarded AI seed grant from Social Science Research Institute
A team including two Penn State statisticians has been awarded a seed grant from the Penn State Center for Social Data Analytics and the Consortium on Moral Decision-Making, in collaboration with the Social Science Research Institute (SSRI). The awards support innovative, interdisciplinary research projects that either apply artificial intelligence (AI) and data science to advance understanding of social and behavioral processes or examine the societal, ethical and human dimensions of AI.
The project is titled "Use and Validation of AI Chatbots in Collaborative Learning in Higher Education Learning Environments." and will support the cross-disciplinary development and pilot testing of AiPRACTISE, a pipeline for socially responsible design, implementation, deployment and iterative fine-tuning of a series of multi-agent, local large language mode environments that enable AI chatbot-facilitated collaborative learning activities. The learning activities are aimed at generating better, more efficient outcomes for students and faculty The researchers will pilot test its scalability when used in collaborative assignments in classes across six departments and three Penn State campuses.
The research team includes:
- Sy-Miin Chow, Penn State College of Health and Human Development
- Youakim Badr, Penn State Great Valley, data analytics and artificial intelligence
- Marcela Borge, Penn State College of Education
- Orfeu M. Buxton, Penn State College of Health and Human Development
- Puiwa Lei, Penn State College of Education
- Matthew D. Beckman, Statistics, Penn State Eberly College of Science
- Marjorie E. Bond, Statistics, Penn State Eberly College of Science
- John Haubrick, Statistics, Penn State Eberly College of Science, and Penn State World Campus, instructional design
The project is one of six winning proposals.
SSRI aims to foster novel, interdisciplinary collaborations by researchers who aim to address critical human and social problems at the local, national and international levels and to translate and disseminate this knowledge into measurable outcomes for human behavior, health and development.