Teaching introductory CS: Shifting from detecting/punishing cheating to gaining programming behavior insight

教授入门级计算机科学：从检测/惩罚作弊转向获得编程行为洞察

• 批准号: 2111323
• 负责人: Mariam Salloum
• 金额: $ 51.49万
• 依托单位: University of California-Riverside
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2111323&HistoricalAwards=false
• 关键词: Teaching; introductory; CS; Shifting; detecting

This IUSE project aims to serve the national interest by giving computer science instructors insight into how students create programs, or solutions to their coding assignments. Plagiarism in programming courses is a significant problem. When a student submits a solution to a programming assignment that has been copied from classmates or online sources, the student may earn a high grade on the assignment but is likely not to gain an understanding of the concepts being illustrated in the assignment. Currently, when a programming assignment is given in a class, an instructor only sees a student's final submission. This project will analyze programming log files to allow instructors to see the student's entire programming process, much like "showing your work" on a mathematics assignment. The project aims to prevent cheating, by creating simple approaches that let students know their programming activity is visible to instructors. As a result they will be less likely to cheat and will gain a better mastery of the concepts being illustrated in the assignment. This project will develop various technologies. First, a "progression highlighter" will provide a concise view of every program run by a student. Second, a "coding trail" will provide a concise visual summary of a student's run. Third, an "anomaly detector" will detect coding styles that depart from the class' style. Fourth, a "drastic change detector" will detect unusual changes in code from one run to the next, suggestive of a student giving up and copy-pasting someone else's solution. Finally, an "overall concern" metric will take all the above items, plus similarity checker results, to provide an overall "concern" score to instructors. The efficacy of these technologies will be measured by analyzing the behavior of at least 100 students based on programming behavior from past quarters, that have been collected using a prototype of the tool. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track which is funding this project, the program supports the creation, exploration, and implementation of promising practices and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个IUSE项目旨在通过让计算机科学教师了解学生如何创建程序或解决他们的编码作业来服务于国家利益。编程课程中的抄袭是一个严重的问题。当学生提交的编程作业的解决方案是从同学或在线资源中复制的，学生可能会在作业中获得高分，但可能不会理解作业中所阐述的概念。目前，在课堂上布置编程作业时，教师只能看到学生提交的最终报告。这个项目将分析编程日志文件，让教师看到学生的整个编程过程，就像在数学作业上“展示你的工作”一样。该项目旨在防止作弊，通过创造简单的方法，让学生知道他们的编程活动是可以被老师看到的。这样一来，他们就不太可能作弊，也能更好地掌握作业中所阐述的概念。这个项目将开发各种技术。首先，“进度亮点”将提供学生运行的每个项目的简明视图。其次，“编码轨迹”将为学生的运行提供简洁的视觉总结。第三，“异常检测器”将检测偏离类风格的编码风格。第四，“剧烈变化检测器”将检测到代码从一次运行到下一次运行的不寻常变化，暗示学生放弃并复制粘贴别人的解决方案。最后，“总体关注”度量将采用上述所有项目，加上相似性检查结果，为讲师提供总体“关注”分数。这些技术的有效性将通过分析至少100名学生的行为来衡量，这些行为是基于过去几个季度的编程行为，这些行为是使用工具的原型收集的。NSF IUSE: EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。通过资助该项目的“参与学生学习”项目，该项目支持有前途的实践和工具的创建、探索和实施。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Progression Highlighting for Programming Courses

编程课程的进度突出显示

• 发表时间: 2021
• 期刊: ASEE annual conference
• 作者: N. Alzahrani, F. Vahid

Ultra-Lightweight Early Prediction of At-Risk Students in CS1

CS1 中高危学生的超轻量级早期预测

• DOI: 10.1145/3545945.3569764
• 发表时间: 2023
• 期刊: SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education
• 作者: Gordon, Chelsea;Zhao, Stanley;Vahid, Frank
• 通讯作者: Vahid, Frank

Variability-Inducing Requirements for Programs: Increasing Solution Variability for Similarity Checking

程序的可变性要求：增加相似性检查的解决方案可变性

• DOI: 10.1145/3587102.3588855
• 发表时间: 2023
• 期刊: ITiCSE 2023: Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education
• 作者: Pang, Ashley;Vahid, Frank
• 通讯作者: Vahid, Frank

Experiences Teaching Coral Before C++ in CS1

在 CS1 中教授 C 之前的 Coral 经验

• DOI: 10.1145/3545945.3569732
• 发表时间: 2023
• 期刊: SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education
• 作者: Vahid, Frank;Downey, Kelly;Areizaga, Lizbeth;Pang, Ashley
• 通讯作者: Pang, Ashley

Impact of Several Low-Effort Cheating-Reduction Methods in a CS1 Class

CS1 课程中几种省力的减少作弊方法的影响

• DOI: 10.1145/3545945.3569731
• 发表时间: 2023
• 期刊: SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education
• 作者: Vahid, Frank;Downey, Kelly;Pang, Ashley;Gordon, Chelsea
• 通讯作者: Gordon, Chelsea