How can generative AI be used to optimize content creation for secondary math use? An exploratory project.

Project Abstract: As students enter high school, math topics tend to become more abstract, which proves difficult for many students and requires additional instructional support. Teachers of advanced mathematics need more resources to support their students' learning, but their options are currently limited. Even with the growth of online resources, many do not provide personalized support or are not connected to specific secondary math curricula. Some teachers are starting to turn to generative AI to help create new content, but little is known about how they should do so. Specifically, generative AI (genAI), such as ChatGPT, has not typically been created for educational purposes and given that many are based large language models (LLMs), there is a growing need to understand how these tools can be used to optimize teaching and learning in mathematics. In this project, we will use an interdisciplinary approach to explore three main areas: 1) Why and how teachers are (or are not) using generative AI, 2) Teachers needs with regard to content/resource generation, and  3) The scope of existing genAI tools.  

CORE RESEARCH TEAM

Principal Investigator: Professor Nikki Lobczowski

Assistant Professor at the Faculty of Education, Learning Science Program.

Professor Siva Reddy

Assistant Professor School of Computer Science Department of Linguistics, MILA-Quebec Artificial Intelligence Institute.

• MQ Wu, 2nd year PhD Student, Faculty of Education, Learning Science Program 

• Arkil Patel, 3rd year Ph. D student, School of Computer Science, MILA Quebec 

• Shuai Chen, 1st year PhD Student, Faculty of Education, Learning Science Program 

• Alex Krantz, 4th year Undergraduate student, Computer Science and Mathematics Dual Major  

• Michael Yu, 3rd year Undergraduate student, Computer Science Major