Developing an AI Model to Improve Students’ Team Experiences
Sara Beckman, Senior Lecturer
Business, Haas School
Applications for Fall 2024 are closed for this project.
Solutions to today’s increasingly “wicked problems” demand teaming across disciplinary boundaries. Teaming in organizations is the “engine of organizational learning…a way of working that brings people together to generate new ideas, find answers and solve problems. But people have to learn to team; it doesn’t come naturally.” (Amy Edmondson Harvard Business School)
Good teaming skills allow teams to leverage diversity to better frame and solve problems and ultimately innovate better. Diverse teams have been shown to either significantly under or out-perform more homogeneous teams. They underperform when they are either blind to the diversity present or treat the diversity with stereotypes. They outperform when they have a learning perspective that allows them to leverage the multiple bodies of knowledge that become available when they take this perspective.
Through this research project, we aim to create a robust curriculum and toolkit for students to be able to learn better about teaming, a skill that is required in any future work they will do. This project entails analyzing the data produced by the teaming questionnaires to discern the core problems that students experience on projects and then creating a user-friendly toolkit for them to use to improve their teaming capabilities and experiences.
This work aims to address the following research questions:
What are the key success factors for making a good team experience on student projects?
How might teaming tools be best provided to students to improve their immediate teaming experiences?
How might a teaming toolkit be best leveraged over time to develop teaming capabilities?
Role: Contribute to developing the TxD teaming curriculum’s AI platform while iterating across user feedback and conducting general machine learning-based research.
Qualifications: All URAPs will be expected to be highly motivated, organized, and self-directed. We seek candidates who have experience using or building APIs with Large Language Models (LLMs) such as OpenAI or others. It would also be beneficial if you have prior experience or exposure building web/mobile applications with AI agents (such as chatbots). Lastly, experience with training ML models would be a plus but is not required.
Completing CS61B is required, and it would be a plus if you have also taken any of these courses - CS188, DATA100, CS186, and/or CS189. Additionally, a strong interest in education, user experience (UX) research, human-computer interaction (HCI), or computer-supported collaborative work (CSCW) is highly valued.
Hours: to be negotiated
Related website: https://www.teamingxdesign.com/
Social Sciences