Computational thinking for the digital age: a systematic review of tools, pedagogical strategies, and assessment practices

Toluchuri Shalini Shanker Rao, Kaushal Kumar Bhagat
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Abstract

Computational thinking (CT) has received growing interest as a research subject in the last decade, with research contributions attempting to capitalize on the benefits that CT may provide. This study included a systematic analysis aimed at revealing current trends in the CT subject, identifying educational interventions, and emerging assessment instruments. It also gave an overview of how teachers learned CT skills and how they integrated the CT curriculum into classroom practices. We searched the data in the Web of Science database and identified 360 articles. Most importantly, it emphasized the following points: (a) the most popular subject areas in CT literature; (b) CT intervention tools; (c) CT assessment practices used so far within educational courses; and (d) effective CT approaches to influence pre-service teachers. Results from this review revealed that CT’s promotion in education had achieved significant progress in recent years. Along with the growth in the number of CT studies, the number of subjects, research questions, and teaching approaches also increased in recent years. It was also found that CT was mostly used in science, mathematics, programming, and computer science tasks, with little work in artificial intelligence (AI) and non-STEM areas. The essence of this paper implicated the researchers in designing the curriculum based on different subject domains. Furthermore, we recommended integrating augmented reality-based games using CT methodologies into the curriculum.

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数字时代的计算思维:工具、教学策略和评估实践的系统回顾
在过去的十年中,计算思维(CT)作为一个研究课题受到了越来越多的关注,研究人员试图利用计算思维可能带来的益处。本研究进行了系统分析,旨在揭示计算思维学科的当前趋势,确定教育干预措施和新出现的评估工具。研究还概述了教师如何学习 CT 技能以及如何将 CT 课程融入课堂实践。我们在 "科学网 "数据库中搜索了相关数据,并确定了 360 篇文章。最重要的是,它强调了以下几点:(a) CT 文献中最受欢迎的学科领域;(b) CT 干预工具;(c) 迄今为止在教育课程中使用的 CT 评估实践;以及 (d) 影响职前教师的有效 CT 方法。审查结果表明,近年来 CT 在教育领域的推广取得了重大进展。随着 CT 研究数量的增长,近年来 CT 研究的主题、研究问题和教学方法也在增加。研究还发现,CT 主要用于科学、数学、编程和计算机科学任务,在人工智能(AI)和非 STEM 领域开展的工作很少。本文的精髓在于让研究人员根据不同学科领域设计课程。此外,我们还建议将基于增强现实的游戏与 CT 方法整合到课程中。
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