How to Form Groups? Optimizing Group Formation of University Students PDF Download

Author: Adrienne Mara Aimée Müller
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Languages : en
Pages : 0

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Book Description
Abstract Collaborative learning through group work is considered a highly effective method for improving learning outcomes and developing valuable social skills. However, group formation is a complex process that can significantly impact the success of collaborative learning. For this reason, it is important to understand, how learners can be effectively grouped together, to ensure successful learning outcomes. The relevance of the present research arises from the tension that group work is, on the one hand, understood as a form and goal of university teaching, and, on the other hand, often fails in its execution without being able to control the relevant factors. Learners differ in various aspects, that influence the quality and quantity of interactions between them. This dissertation utilizes algorithmic group formation to examine the potentially relevant criteria for effective group formation in four experimental Studies, exploring online group work (Studies 1 & 2) and face-to-face group work (Studies 3 & 4). Study 1 examines group formation in a four-week online course for prospective students. The group formation was experimentally carried out based on the variance of the personality traits extraversion and conscientiousness. It was hypothesized that it is advantageous regarding the results to have group variances heterogeneous in extraversion and homogeneous in conscientiousness. Study 2 was similar in the methodology of study 1, with variation of one of the grouping criteria. Based on the variance of the personality trait extraversion and prior knowledge, online groups were formed here to experimentally test which form of group formation leads to the best results. Taken together, study 1 and study 2 provide evidence that successful learning in the online setting is associated with course design and individual differences, among other factors. Simultaneously, students often encounter challenges in organizing their online learning in groups and are prone to experiencing significant dropout rates in such settings. Therefore, study 3 and study 4 explored the effectiveness of group formation strategies in face-to-face groupwork settings to enhance students' groupwork experiences. Study 3 examines whether the heterogeneity or homogeneity of the personality-trait extraversion, as distributed among group members, affects outcomes such as time spent, satisfaction, and performance. Surprisingly, groups with a homogeneous distribution of extraversion reported higher levels of satisfaction than groups with a heterogeneous distribution. The results of study 4 replicated and extended those of study 3 by investigating the effects of grouping from different perspectives in several student institutions. The results indicated that a homogeneous distribution of extraversion among group members significantly contributed to the success of group work. The presented studies contribute to a better understanding of how algorithmic group formation and individual predictors can be utilized to promote successful group learning in several domains. Implications for research and practical applications can be derived from the research findings of the four studies.