
The aim of this paper is to present an empirical study for defining the appropriate triggers for personality related stereotypes. These stereotypes are used for modelling the students in a Computer Supported Collaborative Learning (CSCL) system for UML. The system builds individual student models to provide adaptive and intelligent advice concerning their knowledge and the most adequate colleagues for collaboration. Most of existing CSCL systems and Intelligent Learning Environments (ILE’s) also include student models. However, the vast majority of them use the student models to describe the students from the perspectives of knowledge and/or participation in collaborative activities. In our approach, the student models additionally to the knowledge describe the students regarding specific personality characteristics related to their learning and collaboration attitudes. The student models are built using the stereotype-based method, which entails the definition of the stereotypes, their facets and the triggers (the triggering conditions for a student to belong to a stereotype). As the definition of the triggers is a task of high importance for the effectiveness and accuracy of the student models, we conducted an empirical study among experienced trainers of software engineering.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
