Computer-Assisted Learner Group Formation Based on Personality Traits

Group work is claimed as one of the instructional techniques to improve the performance of students. However, the composition of the group determines the productivity/success of the group. This study has investigated possibilities of developing computerized tools to form groups. In doing so, it has addressed the task of developing a Bayesian prediction model to predict academic performance based on personality attributes and a mathematical model to form effective heterogeneous groups by taking into account personality attributes and performance information. The study has proved that while there are many ways to arrange students to work in cooperative groups, automatic grouping based on the above principles, may be a better option to maximize benefits from group work. Gruppenarbeit wird als eine Lehrform betrachtet, mit der die Leistung von Studierenden gesteigert werden kann, wobei jedoch die Produktivitat und der Lernerfolg stark von der Zusammensetzung der Gruppe abhangig ist. Die Arbeit untersucht Moglichkeiten zur Entwicklung von Computer-gestutzten Werkzeugen zur Gruppenbildung. In diesem Zusammenhang wurden zwei Komponenten entwickelt: ein Bayes'sches Netz zur Vorhersage des zu erwartenden Leistungsniveaus auf der Grundlage von Personlichkeitsmerkmalen, sowie ein mathematisches Modell zur Bildung erfolgreicher Lerngruppen, das sowohl Personlichkeitsmerkmale als auch Leistungsinformation einbezieht. Die Untersuchung hat gezeigt, dass im Vergleich zu alternativen Ansatzen zur Gruppenbildung ein automatisches Verfahren das Potential zur Maximierung des Nutzens von Gruppenarbeit bietet.

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