BZ
Boyun Zhang
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From Students Struggles to Teachers Insights
A Dashboard of Student-AI Interactions in ML Practical Assignments
When students work on self-paced, unsupervised practical assignments in Machine Learning courses, teachers have little visibility into the difficulties students encounter. In our Machine Learning course, students completed a practical assignment using JELAI, an AI-supported programming environment. The recorded student-AI interactions were classified into pedagogically meaningful categories and visualized in a teacher-facing dashboard. An initial evaluation showed that teachers found the dashboard useful, while also identifying areas for improvement. We describe our experience and discuss the potential and challenges of using student-AI interactions to improve teaching practice.
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When students work on self-paced, unsupervised practical assignments in Machine Learning courses, teachers have little visibility into the difficulties students encounter. In our Machine Learning course, students completed a practical assignment using JELAI, an AI-supported programming environment. The recorded student-AI interactions were classified into pedagogically meaningful categories and visualized in a teacher-facing dashboard. An initial evaluation showed that teachers found the dashboard useful, while also identifying areas for improvement. We describe our experience and discuss the potential and challenges of using student-AI interactions to improve teaching practice.