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计划或编码任务的解决方案来服务国家利益。编程课程中的窃是一个重大问题。当学生向已从同学或在线资源复制的编程任务提交解决方案时，学生可能会获得高级分配的成绩，但可能不了解对作业中所示的概念的了解。当前，当课堂中给出编程作业时，讲师只会看到学生的最终提交。该项目将分析编程日志文件，以允许讲师查看学生的整个编程过程，就像在数学分配上“显示您的工作”一样。该项目旨在通过创建简单的方法来防止作弊，让学生知道他们的编程活动对教师可见。结果，他们将不太可能作弊，并且将更好地掌握作业中所说明的概念。该项目将开发各种技术。首先，“进步荧光笔”将为学生提供的每个计划提供简洁的视图。其次，“编码轨迹”将提供学生跑步的简明视觉摘要。第三，“异常检测器”将检测到脱离班级风格的编码样式。第四，“剧烈的变更检测器”将检测到从一次运行到下一个代码的异常变化，这表明学生放弃并复制了他人的解决方案。最后，“整体关注”指标将采用以上所有项目以及相似性检查器的结果，为讲师提供总体“关注”分数。这些技术的功效将通过根据过去几个季度的编程行为分析至少100名学生的行为来衡量，这些行为已使用该工具的原型收集。 NSF IUSE：EHR计划支持研发项目，以提高所有学生STEM教育的有效性。通过为该项目提供资金的敬业学生学习轨道，该计划支持了有希望的实践和工具的创建，探索和实施。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估来进行评估的审查标准。

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

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

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

Common Logic Errors for Programming Learners: A Three-decade Literature Survey

编程学习者常见的逻辑错误：三年的文献调查

• DOI: 10.18260/1-2--36814
• 发表时间: 2021
• 期刊: 2021 ASEE Annual Conference
• 作者: Alzahrani, Nabeel;Vahid, Frank
• 通讯作者: Vahid, Frank