Composing Team Compositions: An Examination of Instructors' Current Algorithmic Team Formation Practices
Composing Team Compositions: An Examination of Instructors' Current Algorithmic Team Formation Practices
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组成团队组合：对讲师当前算法团队组建实践的检查
DOI：
10.1145/3610096
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发表时间：
2023
影响因子：
--
通讯作者：
Brian P. Bailey
中科院分区：
文献类型：
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作者：
Emily M. Hastings;Vidushi Ojha;Benedict V. Austriaco;Karrie Karahalios;Brian P. Bailey
使用算法团队形成工具的教师必须决定哪些标准（例如，技能、人口统计等）用于根据学生的团队合作目标将他们分组到团队中，并且有许多可能的来源来绘制这些配置（例如，文学，其他教师，他们的学生等）。然而，工具提供了相当大的灵活性，选择无效的配置可能会导致团队无法成功协作。由于这些工具的相对新奇，目前很少有知识的教师如何选择这些资源中的哪一个使用，他们如何将不同的标准与他们的目标计划的团队合作，或者他们如何确定他们的配置或生成的团队是成功的。为了缩小这一差距，我们进行了一项调查（N=77）和访谈（N=21）研究的教师使用CATME团队制造商和其他标准为基础的过程，调查教师的目标和决策时，使用团队形成工具。结果表明，教师优先考虑学生学习与不同的队友合作，并对他们的形成方法的输出进行“理智检查”，以确保生成的团队将支持这一目标，特别是关注性别和种族等标准。然而，他们有时很难将他们的教育目标与工具中的特定设置联系起来。一般来说，他们在配置工具时也没有征求学生的任何意见，尽管他们承认这些信息可能有用。通过向学生开放算法的“黑匣子”，以学习者为中心的组建团队的方法可能是一种有前途的方式，可以为教师配置算法工具提供更多支持，同时支持学生代理和学习团队合作。
Instructors using algorithmic team formation tools must decide which criteria (e.g., skills, demographics, etc.) to use to group students into teams based on their teamwork goals, and have many possible sources from which to draw these configurations (e.g., the literature, other faculty, their students, etc.). However, tools offer considerable flexibility and selecting ineffective configurations can lead to teams that do not collaborate successfully. Due to such tools' relative novelty, there is currently little knowledge of how instructors choose which of these sources to utilize, how they relate different criteria to their goals for the planned teamwork, or how they determine if their configuration or the generated teams are successful. To close this gap, we conducted a survey (N=77) and interview (N=21) study of instructors using CATME Team-Maker and other criteria-based processes to investigate instructors' goals and decisions when using team formation tools. The results showed that instructors prioritized students learning to work with diverse teammates and performed "sanity checks" on their formation approach's output to ensure that the generated teams would support this goal, especially focusing on criteria like gender and race. However, they sometimes struggled to relate their educational goals to specific settings in the tool. In general, they also did not solicit any input from students when configuring the tool, despite acknowledging that this information might be useful. By opening the "black box" of the algorithm to students, more learner-centered approaches to forming teams could therefore be a promising way to provide more support to instructors configuring algorithmic tools while at the same time supporting student agency and learning about teamwork.
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DOI：
10.1145/3372782.3406277
发表时间：
2020
期刊：
26th ACM Conference on Innovation and Technology in Computer Science Education
影响因子：
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作者：
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发表时间：
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期刊：
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影响因子：
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作者：
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通讯作者：
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影响因子：
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DOI：
10.1145/3313831.3376797
发表时间：
2020
期刊：
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影响因子：
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作者：
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