ClassAid: A Real-time Instructor-AI-Student Orchestration System for Classroom Programming Activities
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866912884625244160 |
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| author | Zhang, Gefei Sun, Guodao Xia, Meng Liang, Ronghua |
| author_facet | Zhang, Gefei Sun, Guodao Xia, Meng Liang, Ronghua |
| contents | Generative AI is reshaping education, but it also raises concerns about instability and overreliance. In programming classrooms, we aim to leverage its feedback capabilities while reinforcing the educator's role in guiding student-AI interactions. We developed ClassAid, a real-time orchestration system that integrates TA Agents to provide personalized support and an AI-driven dashboard that visualizes student-AI interactions, enabling instructors to dynamically adjust TA Agent modes. Instructors can configure the Agent to provide technical feedback (direct coding solutions), heuristic feedback (hint-based guidance), automatic feedback (autonomously selecting technical or heuristic support), or silent operation (no AI support). We evaluated ClassAid through three aspects: (1) the TA Agents' performance, (2) feedback from 54 students and one instructor during a classroom deployment, and (3) interviews with eight educators. Results demonstrate that dynamic instructor control over AI supports effective real-time personalized feedback and provides design implications for integrating AI into authentic educational settings. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_06734 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | ClassAid: A Real-time Instructor-AI-Student Orchestration System for Classroom Programming Activities Zhang, Gefei Sun, Guodao Xia, Meng Liang, Ronghua Human-Computer Interaction Generative AI is reshaping education, but it also raises concerns about instability and overreliance. In programming classrooms, we aim to leverage its feedback capabilities while reinforcing the educator's role in guiding student-AI interactions. We developed ClassAid, a real-time orchestration system that integrates TA Agents to provide personalized support and an AI-driven dashboard that visualizes student-AI interactions, enabling instructors to dynamically adjust TA Agent modes. Instructors can configure the Agent to provide technical feedback (direct coding solutions), heuristic feedback (hint-based guidance), automatic feedback (autonomously selecting technical or heuristic support), or silent operation (no AI support). We evaluated ClassAid through three aspects: (1) the TA Agents' performance, (2) feedback from 54 students and one instructor during a classroom deployment, and (3) interviews with eight educators. Results demonstrate that dynamic instructor control over AI supports effective real-time personalized feedback and provides design implications for integrating AI into authentic educational settings. |
| title | ClassAid: A Real-time Instructor-AI-Student Orchestration System for Classroom Programming Activities |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2602.06734 |