Task-Specific Languages as Scaffolding for Programming in Discrete Mathematics Classes

该项目旨在通过在课堂上设计和实施特定任务编程（TSP）语言来服务于国家利益。编程是科学家、工程师和数学家用来深入了解他们的问题的强大工具。教育工作者已经展示了如何将编程融入其他科目，成为增强学习的强大工具，从代数到语言艺术。然而，美国只有不到5%的高中生学习编程。大多数学生没有机会使用编程来支持他们的学习。TSP语言通常不是通用语言。此外，考虑到语言的语法、语义和接口的特定领域，很少有语言能够顺利地适应给定的学习环境。TSP语言被明确设计用于特定课程的集成，以满足教师的需求，并且可以在不到10分钟的教学时间内使用。TSP语言可以使编程的力量，以提高学习更容易。这个项目将使用TSP语言的电子书组合，研究本科生学习的计数过程。该项目将测试TSP语言在离散数学中的价值，离散数学是一些计算机科学课程的入门课程。本项目将测试两种不同的TSP语言的使用，并将TSP语言与传统的编程语言（如Python）进行比较。拟议的工作有可能推进以下方面的知识：（1）编程在离散数学学习中的作用，（2）任务特定语言对支架学习的价值，（3）编程的替代表示形式将如何影响学生使用TSP语言，以及（4）单独使用或与传统语言结合使用TSP语言如何增强学生的真实感和迁移知识的能力。学生们将在使用TSP语言解决计数问题时大声思考。我们将分析有声思维的数据，以评估学生对组合数学和语言的理解。该项目的成果将通过国家和国际计算机教育和数学教育会议传播。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。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。

This project aims to serve the national interest by designing and implementing task-specific programming (TSP) languages in classrooms. Programming is a powerful tool that scientists, engineers, and mathematicians use to gain insight into their problems. Educators have shown how programming integrated into other subjects can be a powerful tool to enhance learning, from algebra to language arts. However, less than 5% of high school students in the US learn programming. Most students do not have an opportunity to use programming to support their learning. TSP languages are not typically universal languages. Additionally, considering the specific domains of a language’s syntax, semantics, and interface, few languages fit smoothly into a given learning context. TSP languages are explicitly designed for integration in specific classes, to meet teacher needs, and to be usable with less than ten minutes of instruction. TSP languages can make the power of programming to enhance learning more accessible. This project will use TSP languages in ebook combinations to study undergraduate student learning of counting processes. The project will test the value of TSP languages in discrete mathematics, which is a gateway course in some computer science programs. This project will test the use of two different TSP languages and contrast the TSP languages with a traditional programming language such as Python. The proposed work has the potential to advance knowledge about (1) the role of programming in learning in discrete mathematics, (2) the value of task-specific languages to scaffold learning, (3) how alternative representational forms of programming will influence student use of TSP languages, and (4) how the use of TSP languages alone or in combination with traditional languages will enhance students’ sense of authenticity and ability to transfer knowledge. Students working in pairs will think aloud as they solve counting problems using TSP languages. The think aloud data will be analyzed to assess students’ understanding of combinatorics and the languages. The results of this project will be disseminated through national and international computing education and mathematics education conferences. 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, 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.