In-Depth Feedback on Programming Assignments Using Pattern Recognition and Real-Time Hints

被引：3
|
作者：
Rubinstein, Amir [1 ]
Parzanchevski, Noam [1 ]
Tamarov, Yossi [1 ]
机构：
[1] Tel Aviv Univ, Blavatnik Sch CS, Tel Aviv, Israel
来源：
PROCEEDINGS OF THE 2019 ACM CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION (ITICSE '19) | 2019年
关键词：
Clustering; Automated Grading; Feedback; Pattern Recognition;
D O I：
10.1145/3304221.3325552
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Automatic grading of students' programs is a challenge in computer science (CS) education. In the last two years we have been using a machine learning tool called 'Sense Education' in our '\Intro to CS' course. The tool provides real-time pedagogical hints while students work on solutions, and in-depth feedback on submissions. It also provides a "bird's eye" view of the class's current capabilities, misconceptions, and biases in approaches to solutions. We describe this effort and several test cases. Our goal is to provide teachers with tips on how to effectively use such tools.
引用
收藏
页码：243 / 244
页数：2
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