An Exploratory Approach to Predicting Performance in an Online Electronics Collaborative Problem-Solving Task

Q3 Social Sciences ETS Research Report Series Pub Date : 2024-10-24 DOI:10.1002/ets2.12385
Jonathan Steinberg, Carol Forsyth, Jessica Andrews-Todd
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Abstract

In a study of 370 postsecondary students in electronics, engineering, and other science classes, we investigated collaborative problem-solving (CPS) skills that best predict performance at individual levels in an online electronics environment. The results showed that while monitoring was a consistent predictor across levels, other skills such as executing, sharing information, planning, and maintaining communication each predicted individual performance at one or more levels of the task. The availability of background data on students' content classes and associated content knowledge to analyze the model results can help identify possible cues for instructors across domains to help students improve specific CPS skills to achieve high performance in activities conducted in collaborative learning environments.

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在线电子协作问题解决任务绩效预测的探索性方法
在一项针对370名电子、工程和其他科学类的高等教育学生的研究中,我们调查了在线电子环境中最能预测个人水平表现的协作解决问题(CPS)技能。结果表明,虽然监控是跨级别的一致预测因素,但其他技能(如执行、共享信息、计划和维护沟通)各自预测任务的一个或多个级别上的个人表现。学生内容课的背景数据和相关内容知识的可用性可以帮助教师识别跨领域的可能线索,以帮助学生提高特定的CPS技能,从而在协作学习环境中进行的活动中取得高绩效。
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来源期刊
ETS Research Report Series
ETS Research Report Series Social Sciences-Education
CiteScore
1.20
自引率
0.00%
发文量
17
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