Project Mentor: Professor Zilong Pan, Teaching, Learning & Technology, College of Education
Project Description:
How can AI make math learning more fun and accessible to all?
In India, math education faces a persistent challenge in captivating both students and teachers. Many students perceive math as an abstract and difficult subject, while teachers often lack the resources and innovative strategies to make learning both interactive and enjoyable. This traditional reliance on rote memorization, as opposed to fostering conceptual understanding and practical application, deepens the disengagement. Bridging this gap is crucial to creating a math learning experience that not only excites students but also empowers teachers to inspire a love for the subject. Through the integration of AI-driven tools like MathPal, this project aims to revolutionize the teaching and learning of math, making it an engaging, dynamic, and rewarding experience for educators and learners alike.
Students in this project will collaborate closely with K-12 math teachers from the Agastya International Foundation, leveraging MathPal—an AI tool designed to serve as a personalized learning partner for K-12 students and adult learners. MathPal provides learners with personalized support in a conversational style, characterized by a customizable tone. MathPal offers two main types of support: conceptual and metacognitive. For conceptual support, MathPal provides explanations and practice questions based on learners' requests, recommends relevant learning resources like instructional videos from Khan Academy, and offers step-by-step guidance or hints for solving specific problems, allowing students to seek hints without revealing answers. In terms of metacognitive support, MathPal aligns with the metacognitive knowledge framework, which includes self-awareness, understanding the learning task, and strategic thinking. It analyzes learners' performance, identifies incorrectly answered questions, and generates a comprehensive report to help students understand their strengths and weaknesses across various math units. Additionally, MathPal provides targeted tips and strategies based on performance to support personalized learning. During interactions, if learners initiate topics unrelated to math, such as music, MathPal redirects the conversation by demonstrating the application of math in the music field.
The next steps for the project include dashboard development and usability testing. Students with front-end development skills, particularly in JavaScript, as well as those familiar with machine learning techniques, especially natural language processing (NLP), are encouraged to apply.