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Experiment on extraversion distribution in groups through a group formation algorithm
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DOI：10.1016/j.caeo.2024.100181.png)
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Advances in technology have sparked a surge of interest in systematic group formation in educational contexts. The experimental study investigates group formation by extraversion distributions on group work outcomes, expected to influence group hierarchy. As an initial step in the experimental randomization process, an algorithmic group formation tool ensured an equal partitioning and aligned students into two experimental conditions with either consistent, homogeneous, or varied, heterogeneous, levels of extraversion. Over the course of one semester, a total of 114 students enrolled in several paralleled seminars, were surveyed on both subjective data (satisfaction with group work) and objective data (group performance) to evaluate the effect of the experimental intervention. The formation of extraversion at the group level contributed to the respective outcomes, emphasizing the value of collective social capital for both individuals and groups. Specifically, a homogeneous distribution of extraversion had a positive impact on group performance, as evident in improved grades on course group assignments and increased active participation in group meetings. Findings emphasize considering personality traits at group-level to enhance the success of groups.
Keyword:
Educational technology
Higher education
Group formation algorithm
Media in education
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