A Mixed User-Centered Approach to Enable Augmented Intelligence in Intelligent Tutoring Systems: The Case of MathAIde app

TL;DR

This paper presents MathAIde, an intelligent tutoring system that integrates augmented intelligence with a user-centered design, demonstrating effective AI-human collaboration for math education in resource-limited settings.

Contribution

It introduces a mixed-methods, user-centered approach to integrating augmented intelligence into ITS, emphasizing teacher involvement and practical deployment.

Findings

MathAIde improves efficiency and usability in math tutoring.

Teacher-centered AI suggestions enhance decision-making.

System shows high adoption potential in classrooms.

Abstract

This study explores the integration of Augmented Intelligence (AuI) in Intelligent Tutoring Systems (ITS) to address challenges in Artificial Intelligence in Education (AIED), including teacher involvement, AI reliability, and resource accessibility. We present MathAIde, an ITS that uses computer vision and AI to correct mathematics exercises from student work photos and provide feedback. The system was designed through a collaborative process involving brainstorming with teachers, high-fidelity prototyping, A/B testing, and a real-world case study. Findings emphasize the importance of a teacher-centered, user-driven approach, where AI suggests remediation alternatives while teachers retain decision-making. Results highlight efficiency, usability, and adoption potential in classroom contexts, particularly in resource-limited environments. The study contributes practical insights into designing ITSs that balanceuser needs and technological feasibility, while advancing AIED research by demonstrating the effectiveness of a mixed-methods, user-centered approach to implementing AuI in educational technologies.