Students' Feedback Requests and Interactions with the SCRIPT Chatbot: Do They Get What They Ask For?
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866908462200389632 |
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| author | Scholl, Andreas Kiesler, Natalie |
| author_facet | Scholl, Andreas Kiesler, Natalie |
| contents | Building on prior research on Generative AI (GenAI) and related tools for programming education, we developed SCRIPT, a chatbot based on ChatGPT-4o-mini, to support novice learners. SCRIPT allows for open-ended interactions and structured guidance through predefined prompts. We evaluated the tool via an experiment with 136 students from an introductory programming course at a large German university and analyzed how students interacted with SCRIPT while solving programming tasks with a focus on their feedback preferences. The results reveal that students' feedback requests seem to follow a specific sequence. Moreover, the chatbot responses aligned well with students' requested feedback types (in 75%), and it adhered to the system prompt constraints. These insights inform the design of GenAI-based learning support systems and highlight challenges in balancing guidance and flexibility in AI-assisted tools. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_17258 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Students' Feedback Requests and Interactions with the SCRIPT Chatbot: Do They Get What They Ask For? Scholl, Andreas Kiesler, Natalie Artificial Intelligence Building on prior research on Generative AI (GenAI) and related tools for programming education, we developed SCRIPT, a chatbot based on ChatGPT-4o-mini, to support novice learners. SCRIPT allows for open-ended interactions and structured guidance through predefined prompts. We evaluated the tool via an experiment with 136 students from an introductory programming course at a large German university and analyzed how students interacted with SCRIPT while solving programming tasks with a focus on their feedback preferences. The results reveal that students' feedback requests seem to follow a specific sequence. Moreover, the chatbot responses aligned well with students' requested feedback types (in 75%), and it adhered to the system prompt constraints. These insights inform the design of GenAI-based learning support systems and highlight challenges in balancing guidance and flexibility in AI-assisted tools. |
| title | Students' Feedback Requests and Interactions with the SCRIPT Chatbot: Do They Get What They Ask For? |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2507.17258 |