Multilingual Computational Thinking: Teaching Introductory Programming Classes Through Low-Level and High-Level Programming Languages

多语言计算思维：通过低级和高级编程语言教授编程入门课程

• 批准号: 2021446
• 负责人: Omar El Ariss
• 金额: $ 30万
• 依托单位: Texas A&M University-Commerce
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2021446&HistoricalAwards=false
• 关键词: Multilingual; Computational; Thinking; Teaching; Introductory

This project aims to serve the national interest by exploring a potentially transformative approach for improving undergraduate computer science education. Student success in computer science directly correlates with their performance in introductory programming courses. Not only do these courses provide students with basic computational skills, but they can also give students the confidence they need to persevere and obtain computer science degrees. This project is based on the hypothesis that learning introductory computer programming languages is like learning a natural language. Research has shown that multilingual children outperform monolingual children when learning English as a foreign language. The project will apply this observation to computer science by concurrently teaching students multiple programming languages, thus helping them become multilingual in computer programming languages. It is expected that multilingual learning in introductory computer programming will support subsequent student confidence and success in computer science.The project team will focus on transforming the Programming I, Programming II, and Data Structure courses to emphasize algorithmic design and computational thinking. Each course will use three different programming languages simultaneously: an assembly language and two high-level programming languages. The learning activities will include interactive videos, simulations, engaging projects, and assignments based on programming for video game development. By simultaneously teaching multiple computer programming languages, the research team expects to remove student dependency on a single programming language as well as strengthen students’ development of a solid foundation in algorithmic design and computational thinking. The research plan will investigate how students learn multiple computer programming languages, and whether it is more effective to learn multiple programming languages simultaneously or sequentially. It will also use Neo-Piagetian cognitive development theory to identify the stages through which students pass as they master algorithmic thinking, from the basics of syntax to an understanding of patterns. These stages can also be used more generally to assess students’ knowledge of programming. This project is supported by the NSF Improving Undergraduate STEM Education Program: Education and Human Resources Program, which supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, 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.

该项目旨在通过探索一种潜在的变革性方法来改善本科计算机科学教育，从而为国家利益服务。 学生在计算机科学方面的成功与他们在入门编程课程中的表现直接相关。这些课程不仅为学生提供基本的计算技能，而且还可以给学生信心，他们需要坚持下去，并获得计算机科学学位。这个项目是基于一个假设，即学习入门计算机编程语言就像学习一门自然语言。研究表明，多语言儿童在学习英语作为外语时表现优于单语儿童。该项目将通过同时教授学生多种编程语言，将这一观察应用于计算机科学，从而帮助他们掌握计算机编程语言。 预计在计算机编程入门课程中的多语言学习将支持学生在计算机科学方面的信心和成功。项目团队将专注于改造编程I，编程II和数据结构课程，以强调算法设计和计算思维。每门课程将同时使用三种不同的编程语言：一种汇编语言和两种高级编程语言。 学习活动将包括互动视频，模拟，引人入胜的项目和基于视频游戏开发编程的作业。通过同时教授多种计算机编程语言，研究团队希望消除学生对单一编程语言的依赖，并加强学生在算法设计和计算思维方面的坚实基础。该研究计划将调查学生如何学习多种计算机编程语言，以及同时或顺序学习多种编程语言是否更有效。它还将使用新皮亚杰的认知发展理论来确定学生在掌握算法思维时所经历的阶段，从语法的基础知识到对模式的理解。这些阶段也可以更广泛地用于评估学生的编程知识。 该项目由NSF改善本科STEM教育计划：教育和人力资源计划支持，该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。该奖项反映了NSF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

Multiple Programming Languages for Improving Computational Thinking in CS1

用于提高 CS1 计算思维的多种编程语言

• DOI: 10.1145/3545947.3576322
• 发表时间: 2023
• 期刊: Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2 (SIGCSE 2023
• 作者: Lee, Dongeun;Hu, Kaoning;El Ariss, Omar;Kwon, Kibum
• 通讯作者: Kwon, Kibum