dataset; Visualizing Contribution Levels in Group Programs: A Dot-Voting Peer-Assessment Approach
收藏DataCite Commons2026-05-13 更新2026-04-25 收录
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https://figshare.com/articles/dataset/dataset_Visualizing_Contribution_Levels_in_Group_Programs_A_Dot-Voting_Peer-Assessment_Approach/26838772/1
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Group programs, such as discussions or workshops, are critical components of active learning in higher education. However, evaluating these activities can be challenging. This study aimed to examine the validity of peer assessment among students (PAAS) using the dot voting method, commonly employed in business decision-making. The results from the Generalised Linear Mixed Model indicate that increasing group size enhances the variability of contributions within the group, while repeated participation by the same members reduces this variability. Specifically, groups of eight members exhibited significantly higher variability in contributions compared to groups of four members, showing a moderate positive correlation. Furthermore, the variability decreased after the second repetition. Additionally, visualizing individual voting data through heat maps enabled the observation of temporal changes in the number and type of votes cast for each participant. These findings suggest that peer assessment using the dot voting method can effectively visualize student contributions in group programs by analysing the variability of contributions and the voting items attributed to each individual.
提供机构:
figshare
创建时间:
2025-10-17



