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.

Learn more

Research description:

This project aims to develop emotionally aware AI math tutors that can teach children mathematics in a personalized and adaptive way. The system will analyze each learner’s performance and error patterns as well as their expressed and hidden emotions using advanced emotion decoding algorithms to deliver individualized instruction and targeted explanations for specific concepts.In addition to tracking learning progress, the AI tutor will continuously monitor the student’s emotional states (e.g., frustration, confusion, or engagement) using emotion recognition technologies based on facial expressions, voice tone, and behavioral cues and hidden emotions and physiology using transdermal optional imaging. By adapting its responses and instructional strategies according to both cognitive and emotional feedback, the system will enhance not only mathematical understanding but also learners’ motivation and emotional well-being.

Training will be provided in affective computing, AI analytics, and AI ethics. The SUDS Scholar responsibilities will include:

Attending regular team meetings to discuss project goals, technical requirements, and assigned tasks.
Learning and applying programming and AI-related skills through discussions, mentorship, and collaboration with team members.
Assisting in implementing and testing modules for emotion recognition and adaptive learning feedback.
Supporting data collection and analysis to evaluate students’ learning performance and emotional responses.
Refining and improving the system based on test results and user feedback to enhance learning effectiveness and emotional engagement.
Developing interdisciplinary experience that combines artificial intelligence, emotion recognition, and educational technology.

Year: 2026

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

Student:
Andrew Tu, University of Toronto

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

Learn more