Advancing the Science of Collaborative Problem Solving
Advancing the Science of Collaborative Problem Solving
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DOI：
10.1177/1529100618808244
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发表时间：
2018-11-01
影响因子：
25.4
通讯作者：
Hesse, Friedrich W.
中科院分区：
文献类型：
--
作者：
Graesser, Arthur C.;Fiore, Stephen M.;Hesse, Friedrich W.
协作解决问题（CPS）一直受到国际关注，因为现代世界中的许多复杂工作都是由团队进行的。但是，缺乏进入和参与劳动力的人的系统教育和CPS培训。 2015年，全球教育进步测试的国际学生评估计划（PISA）记录了CPS的水平较低。这一结果不仅强调了巨大的社会需求，而且为心理科学家提供了一个重要的机会，可以开发，采用和实施有关CP的理论和实证研究，并与教育者和政策专家合作，以改善CPS的培训。本文为心理科学提供了一些指示，以参与对全球CP的日益关注。首先，它确定了关注CPS的现有理论框架和实证研究。其次，它提供了有关最近技术如何自动化CPS流程和评估分析的示例，以便可以分析更大的数据集，以便学生可以立即收到有关其CPS性能的反馈。第三，它确定了为CPS创建研究，教育和培训的基础设施时的一些挑战，辩论和不确定性。预计CPS的教育和评估将在受到心理科学告知的较大数据集和理论框架的支持下得到改善。这将需要跨学科的努力，包括心理科学，教育，评估，智能数字技术和政策方面的专业知识。
Collaborative problem solving (CPS) has been receiving increasing international attention because much of the complex work in the modern world is performed by teams. However, systematic education and training on CPS is lacking for those entering and participating in the workforce. In 2015, the Programme for International Student Assessment (PISA), a global test of educational progress, documented the low levels of proficiency in CPS. This result not only underscores a significant societal need but also presents an important opportunity for psychological scientists to develop, adopt, and implement theory and empirical research on CPS and to work with educators and policy experts to improve training in CPS. This article offers some directions for psychological science to participate in the growing attention to CPS throughout the world. First, it identifies the existing theoretical frameworks and empirical research that focus on CPS. Second, it provides examples of how recent technologies can automate analyses of CPS processes and assessments so that substantially larger data sets can be analyzed and so students can receive immediate feedback on their CPS performance. Third, it identifies some challenges, debates, and uncertainties in creating an infrastructure for research, education, and training in CPS. CPS education and assessment are expected to improve when supported by larger data sets and theoretical frameworks that are informed by psychological science. This will require interdisciplinary efforts that include expertise in psychological science, education, assessment, intelligent digital technologies, and policy.