Well-structured collaborative learning groups scripted based on Collaborative Learning Flow Patterns
(CLFPs) often result in successful collaborative learning outcomes. Formulation of such learner groups based on
instructor defined criteria promises potentially effective performance of participating students. However, forming
student groups manually based on multiple criteria often fails due to its complexity and the time limitations of practitioners.
Hence, an intelligent assistance which supports ...
Well-structured collaborative learning groups scripted based on Collaborative Learning Flow Patterns
(CLFPs) often result in successful collaborative learning outcomes. Formulation of such learner groups based on
instructor defined criteria promises potentially effective performance of participating students. However, forming
student groups manually based on multiple criteria often fails due to its complexity and the time limitations of practitioners.
Hence, an intelligent assistance which supports adaptive collaboration scripting based on instructor defined criteria,
while adhering to CLFPs is presented. Constraint Optimization techniques have been used for learner group formation and
preliminary tests revealed that the proposed approach could be utilized when formulating student groups while satisfying team formation criteria.
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