AI-Enhanced Technical Interview Preparation
Creating scalable, personalized technical interview practice for data science students by combining expert human interviews with AI simulation.
Overview
Creating scalable, personalized technical interview practice for data science students by combining expert human interviews with AI simulation. This project identifies effective interviewing patterns through real student interactions, then develops an adaptive AI platform that helps students articulate technical concepts, improve communication skills, and prepare for industry positions at their own pace.
Project Details
Started
2024-01
Status
Active
Topics
Funding
- Academic Innovation Fund (2024): $12,435
Research Team
- Michael IonCo-Principal InvestigatorUniversity of Michigan
- Kevyn Collins-ThompsonCo-Principal InvestigatorUniversity of Michigan
Related Scholarship
Papers
Simulated Teaching and Learning at Scale: Balancing Fidelity and Effectiveness in Tutoring Interactions
Michael Ion, Kevyn Collins-Thompson, S. Asthana
Bayesian Hierarchical Modeling of Large-Scale Math Tutoring Dialogues
Michael Ion, Kevyn Collins-Thompson
Joint Statistical Meetings (2025) - Under review
Talks & Presentations
Adaptive Knowledge Assessment in Simulated Coding Interviews
Michael Ion, S. Asthana, Fengquan Jiao, Tianyi Wang, Kevyn Collins-Thompson
iRAISE Workshop at AAAI Conference (2025)