SUDS Project:

Using advanced machine learning approaches to optimize psychological test efficiency interview

Research description:

This project will involve students to use advanced machine learning approaches to analyze large scale datasets of psychological tests with responses collected from participants all over the world. The goal of this project is to analyze response patterns from participants, train computational models to optimize the assessment of participants’ psychological traits (e.g., personality) and abilities (e.g., IQ) in an effective and efficient manner, and implement computational models in an app for use by real-world users.

The student will be responsible for data cleaning, data analysis, using machine learning techniques to optimize the models, implementing the models on a website for use by users, and writing a paper for publication.

Year: 2024

Researcher:
Kang Lee, Department of Applied Psychology and Human Development, Ontario Institute for Studies in Education, University of Toronto

Student: 
Rogers Yang, University of Toronto

Through SUDS, undergraduate students engage in hands-on research focused on data sciences and AI methodology applications.