Collaborative Research: Retaining and Engaging Computer Science majors By Solving and Visualizing Algorithmic Problems on Real-world Data Sets

协作研究：通过解决和可视化现实世界数据集上的算法问题来留住和吸引计算机科学专业的学生

• 批准号: 1726809
• 负责人: Kalpathi Subramanian
• 金额: $ 54.16万
• 依托单位: University of North Carolina at Charlotte
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1726809&HistoricalAwards=false
• 关键词: Collaborative; Research; Retaining; Engaging; Computer

The first two years of undergraduate Computer Science education are the most critical for building students? foundational knowledge and sustaining their interest in computer science. Both knowledge and interest help students not only develop good skills in computer science, but also increase their resolve to stay in the computer science major. This project will try to increase student knowledge and interest by adding new functionality to a software program called BRIDGES. BRIDGES helps instructors create engaging assignments for sophomore-level courses on data structures and algorithms. To help them learn about data structures, BRIDGES enables students to easily populate their own data structures with large, dynamic data sets from real-world information systems, such as popular social networks and scientific sources. Bridges also allows students to interact with visualizations of their own data structures. Preliminary results have shown that, in comparison to their peers whose data structures courses did not use BRIDGES, students in BRIDGES-enabled courses have greater knowledge gains and better progression through the major. This project will enhance BRIDGES by adding code analysis functions and new data sources that are relevant to student interests. These enhancements aim to support deeper coverage of data structures topics, which may further increase student engagement and learning. To study the impact of BRIDGES more thoroughly, BRIDGES will be adopted and studied at three other institutions. This expansion will enable evaluation of the impact of BRIDGES on different student populations. This project serves the national interest through its focus on increasing retention of students and building a more diverse STEM workforce.The goal of this project is to extend the BRIDGES curriculum to provide engaging, relevant assignments and strengthen basic programming skills such as array addressing to reduce the number of withdrawals in the first weeks of data structure courses. A second goal is to follow best practices for engaging underrepresented students in computing. Computational complexity will be incorporated through system support in BRIDGES for performance reporting and real world algorithmic problems at different scales to afford experience with orders of growth. The project will also extend beyond the data structures course and into typical CS1/CS2 courses. BRIDGES will be adopted at three partnering institutions, including non-PhD granting institution and a liberal arts college, and will directly reach over 1000 students each year. That diversity will support studying the impact of BRIDGES on student engagement and learning across populations of students. In addition, students from the STARS Computing Corps, a national alliance for broadening participation in computing, will incorporate BRIDGES materials within their outreach programs that introduce computing concepts to K-12 students to reach an even more diverse population of students.

计算机科学本科教育的前两年是培养学生最关键的阶段。基础知识和保持他们对计算机科学的兴趣。知识和兴趣不仅可以帮助学生培养良好的计算机科学技能，还可以增强他们留在计算机科学专业的决心。这个项目将尝试通过给一个叫做BRIDGES的软件程序添加新功能来增加学生的知识和兴趣。BRIDGES帮助教师为二年级的数据结构和算法课程创建引人入胜的作业。为了帮助他们学习数据结构，BRIDGES使学生能够轻松地用来自现实世界信息系统（如流行的社交网络和科学来源）的大型动态数据集填充自己的数据结构。bridge还允许学生与他们自己的数据结构的可视化进行交互。初步结果表明，与没有使用BRIDGES的数据结构课程的同龄人相比，使用BRIDGES的课程的学生获得了更多的知识，并在专业中取得了更好的进展。该项目将通过增加与学生兴趣相关的代码分析功能和新数据源来增强BRIDGES。这些增强旨在支持更深入地覆盖数据结构主题，这可能会进一步提高学生的参与度和学习。为了更彻底地研究BRIDGES的影响，BRIDGES将被另外三所机构采用和研究。这一扩展将使评估桥梁对不同学生群体的影响成为可能。该项目致力于提高学生保留率和建立更多样化的STEM劳动力，符合国家利益。这个项目的目标是扩展BRIDGES课程，提供有吸引力的、相关的作业，并加强基本的编程技能，比如数组寻址，以减少数据结构课程头几周的提款次数。第二个目标是遵循最佳实践，让未被充分代表的学生参与计算。计算复杂性将通过BRIDGES的系统支持纳入不同规模的性能报告和现实世界算法问题，以提供增长顺序的经验。该项目还将扩展到数据结构课程之外，并进入典型的CS1/CS2课程。“桥梁”计划将在三所合作院校实施，包括非博士学位授予机构和一所文理学院，每年将直接惠及1000多名学生。这种多样性将有助于研究桥梁对学生参与和跨学生群体学习的影响。此外，来自STARS计算队（一个扩大计算机参与的国家联盟）的学生将把BRIDGES的材料纳入他们的推广计划，向K-12学生介绍计算机概念，以接触到更多不同的学生群体。

项目成果

BRIDGES: Real world data, assignments and visualizations to engage and motivate CS majors

BRIDGES：真实世界的数据、作业和可视化，以吸引和激励计算机专业的学生

• DOI: 10.1007/s10639-023-11958-4
• 发表时间: 2023
• 期刊: Education and Information Technologies
• 影响因子: 5.5
• 作者: Burlinson, David;Mcquaigue, Matthew;Goncharow, Alec;Subramanian, Kalpathi;Saule, Erik;Payton, Jamie;Goolkasian, Paula
• 通讯作者: Goolkasian, Paula

Visualization, Assessment and Analytics in Data Structures Learning Modules

数据结构学习模块中的可视化、评估和分析

• DOI: 10.1145/3159450.3159460
• 发表时间: 2018
• 期刊: SIGCSE '18 Proceedings of the 49th ACM Technical Symposium on Computer Science Education
• 作者: Mcquaigue, Matthew;Burlinson, David;Subramanian, Kalpathi;Saule, Erik;Payton, Jamie
• 通讯作者: Payton, Jamie

Real-World Assignments at Scale to Reinforce the Importance of Algorithms and Complexity

大规模的现实世界作业以强化算法和复杂性的重要性

• 发表时间: 2020
• 期刊: CCSC NE
• 作者: Strahler, Jason;Mcquaigue, Matthew;Goncharow, Alec;Burlinson, David;Subramanian, Kalpathi;Saule, Erik;Payton, Jamie
• 通讯作者: Payton, Jamie

Engaging Early Programming Students with Modern Assignments Using BRIDGES ∗

使用 BRIDGES 让早期编程学生参与现代作业*

• DOI: 10.5555/3417639.3417654
• 发表时间: 2020
• 期刊: Journal of Computing Sciences in Colleges
• 作者: A. Beckman;Matthew Mcquaigue;Alec Goncharow;David Burlinson;K. Subramanian;Erik Saule;J. Payton
• 通讯作者: J. Payton

Experiences on Teaching Parallel and Distributed Computing for Undergraduates

本科生并行与分布式计算教学体会

• DOI: 10.1109/ipdpsw.2018.00068
• 发表时间: 2018
• 期刊: 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW
• 作者: Saule, Erik