A Mixed User-Centered Approach to Enable Augmented Intelligence in Intelligent Tutoring Systems: The Case of MathAIde app
Fuente:
arXiv
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| Autores principales: | , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866916949511897088 |
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| author | Guerino, Guilherme Rodrigues, Luiz Bianchini, Luana Alves, Mariana Marinho, Marcelo Veloso, Thomaz Macario, Valmir Dermeval, Diego Vieira, Thales Bittencourt, Ig Isotani, Seiji |
| author_facet | Guerino, Guilherme Rodrigues, Luiz Bianchini, Luana Alves, Mariana Marinho, Marcelo Veloso, Thomaz Macario, Valmir Dermeval, Diego Vieira, Thales Bittencourt, Ig Isotani, Seiji |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_00103 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Mixed User-Centered Approach to Enable Augmented Intelligence in Intelligent Tutoring Systems: The Case of MathAIde app Guerino, Guilherme Rodrigues, Luiz Bianchini, Luana Alves, Mariana Marinho, Marcelo Veloso, Thomaz Macario, Valmir Dermeval, Diego Vieira, Thales Bittencourt, Ig Isotani, Seiji Human-Computer Interaction Artificial Intelligence 68T01 H.5.0; I.2.0 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. |
| title | A Mixed User-Centered Approach to Enable Augmented Intelligence in Intelligent Tutoring Systems: The Case of MathAIde app |
| topic | Human-Computer Interaction Artificial Intelligence 68T01 H.5.0; I.2.0 |
| url | https://arxiv.org/abs/2508.00103 |