Abstract
Fast advancement of technology has led to an increased interest for using information technology to provide feedback based on learning behavior observations. This work outlines a novel approach for analyzing behavioral learner data through the application of process mining techniques specifically targeting a complex problem solving process. We realize this in the context of one particular learning case, namely, domain modeling. This work extends our previous research on process-mining analysis of domain modeling behavior of novices by elaborating with new insights from a replication study enhanced with an extra observation on how novices verify/validate models. The findings include a set of typical modeling and validation patterns that can be used to improve teaching guidance for domain modeling courses. From a scientific viewpoint, the results contribute to improving our knowledge on the cognitive aspects of problem-solving behavior of novices in the area of domain modeling, specifically regarding process-oriented feedback as opposed to traditional outcome feedback (is a solution correct? Why (not)?) usually applied in this type of courses. Ultimately, the outcomes of the work can be inspirational outside of the area of domain modeling as learning event data is becoming readily available through virtual learning environments and other information systems.
| Original language | English |
|---|---|
| Pages (from-to) | 352-376 |
| Number of pages | 25 |
| Journal | Computers in human behavior |
| Volume | 57 |
| Early online date | 31 Dec 2015 |
| DOIs | |
| Publication status | Published - Apr 2016 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 4 Quality Education
Keywords
- n/a OA procedure
- Domain modeling
- Conceptual modeling
- Process-oriented feedback
- Modeling patterns
- Information systems education
- Process mining
- Learning analytics
- Teaching/learning modeling
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