[UofT] AI-Powered Self-Assessment: Transforming How Students Understand What They Know

Our presentation will introduce a web-based platform designed to help students improve their learning through structured self-assessment. The system is based on Cognitive Structure Analysis (CSA), a method that focuses on identifying the concepts a student understands rather than simply checking whether they can produce the correct answer on a test. Research conducted by MyEdMaster across multiple countries and subject areas shows that students who use CSA can improve their academic performance by an average of 1.5 to 2.5 letter grades.
We will demonstrate how our platform allows students to access CSA self-assessment templates, evaluate their understanding of key concepts, and identify gaps in their knowledge. Once these gaps are identified, students can focus their studying on the areas where they need the most improvement. The website also supports classroom use by allowing teachers to register classes and receive aggregated reports that highlight student learning needs, helping guide instruction.
Additionally, we will discuss how AI-powered tools integrated into the platform can assist students by simplifying self-assessment, generating study prompts, and improving accessibility. Overall, the project aims to provide a scalable, user-friendly tool that empowers students to better understand their own learning and study more effectively.