形成性评价
计算机科学
编码(社会科学)
同行反馈
分级(工程)
人机交互
多媒体
人工智能
数学教育
心理学
数学
统计
工程类
土木工程
作者
Hieke Keuning,Johan Jeuring,Bastiaan Heeren
出处
期刊:ACM Transactions on Computing Education
[Association for Computing Machinery]
日期:2018-09-28
卷期号:19 (1): 1-43
被引量:188
摘要
Formative feedback, aimed at helping students to improve their work, is an important factor in learning. Many tools that offer programming exercises provide automated feedback on student solutions. We have performed a systematic literature review to find out what kind of feedback is provided, which techniques are used to generate the feedback, how adaptable the feedback is, and how these tools are evaluated. We have designed a labelling to classify the tools, and use Narciss’ feedback content categories to classify feedback messages. We report on the results of coding a total of 101 tools. We have found that feedback mostly focuses on identifying mistakes and less on fixing problems and taking a next step. Furthermore, teachers cannot easily adapt tools to their own needs. However, the diversity of feedback types has increased over the past decades and new techniques are being applied to generate feedback that is increasingly helpful for students.
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