Abstract
Students often struggle with constructing models of system behaviour, particularly in open modelling tasks where there is no single correct answer. The challenge lies in providing effective support that helps students develop high quality models while maintaining their autonomy in the modelling process. This study presents a procedure for assessing the quality of student-generated qualitative models in open modelling tasks, based on three characteristics: correctness, parsimony, and completeness. The procedure was developed and refined using student-generated models from two secondary school tasks on thermoregulation and sound properties. The findings contribute to the development of automated support systems that guide students through open modelling tasks by focusing on quality characteristics rather than adherence to a predefined norm model.
| Original language | English |
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| Title of host publication | Workshop on advances in Artificial Intelligence for Exploratory Learning (AI4EXL) |
| Subtitle of host publication | 26th International Conference on Artificial Intelligence in Education (AIED 2025) |
| Number of pages | 9 |
| Publication status | Published - 26 Jul 2025 |
| Event | Workshop on Advances on Artificial Intelligence in Exploratory Learning - Palermo, Italy Duration: 26 Jul 2025 → 26 Jul 2025 https://transeet.eu/ai4exl/ |
Workshop
| Workshop | Workshop on Advances on Artificial Intelligence in Exploratory Learning |
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| Country/Territory | Italy |
| City | Palermo |
| Period | 26/07/25 → 26/07/25 |
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