Overcoming Impediments to Computer Science Students' Understanding of Code: Scaling Up Automated Methods and Broadening Participation

克服计算机科学学生理解代码的障碍：扩大自动化方法并扩大参与范围

• 批准号: 1914820
• 负责人: Gloria Washington
• 金额: $ 8.85万
• 依托单位: Howard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1914820&HistoricalAwards=false
• 关键词: Overcoming; Impediments; Computer; Science; Students

With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR), this project aims to serve the national interest by improving computer science education. To achieve this goal, the project will identify misunderstandings that arise when students reason about code and develop strategies to overcome these misunderstandings. The project will focus on using automated analysis to teach students how to use mental execution and/or tracing to predict the execution behavior of program code, one of the most basic and important objectives of computing education. The ability to trace through a segment of code to understand its behavior is central to learning how to write new programs, as well as to reason about, debug, and improve existing programs. The best programmers can predict behavior on specific inputs, and extend their reasoning to generalized inputs, developing an abstract, broad understanding. This project seeks to identify the aspects of automated methods that are most effective in identifying and overcoming learning obstacles associated with students' reasoning about software code.This project has two objectives. First, it aims to understand the learning obstacles students face in tracing code on specific, concrete inputs, and the obstacles they ultimately face in generalizing that reasoning to abstract, symbolic inputs. Second, the project aims to understand why these obstacles arise and how they can be overcome. To collect and analyze information about student reasoning, as well as to provide student feedback, the project will develop an online reasoning tutor that can capture and respond to students' choices, written explanations, and verbal explanations. These online reasoning tutors will be used in conjunction with other instructional strategies to support development of students' abilities to reason about code. To enable the findings to be broadly applicable to all students, the research will include diverse student populations. The effort involves Clemson University, a large land-grant public institution, Florida Atlantic University, an HSI, and Howard University, an HBCU. The evaluation effort is led through Rose-Hulman. Computing is fundamental to the nation's society and commerce. To become successful computing professionals, student programmers need to develop the debugging and reasoning skills that are the focus of this project. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. This is an Engaged Student Learning project; through the Engaged Student Learning track, the IUSE: EHR 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.

在NSF改善本科STEM教育计划的支持下：教育和人力资源（IUSE：EHR），该项目旨在通过改善计算机科学教育来满足国家利益。 为了实现这一目标，该项目将确定当学生推论代码并制定克服这些误解的策略时会产生误解。 该项目将专注于使用自动分析来教学学生如何使用心理执行和/或跟踪来预测程序代码的执行行为，程序代码是计算教育的最基本和最重要的目标之一。追踪一段代码以了解其行为的能力对于学习如何编写新程序以及推理，调试和改进现有程序至关重要。最好的程序员可以预测特定输入的行为，并将其推理扩展到广义输入，从而发展一个抽象的广泛理解。该项目旨在确定自动化方法的各个方面，这些方法最有效地识别和克服与学生对软件代码的推理相关的学习障碍。该项目有两个目标。首先，它旨在了解学生在特定的具体，具体投入的守则中所面临的学习障碍，以及他们最终在将这些推理推广到抽象的象征性输入方面所面临的障碍。其次，该项目旨在了解为什么出现这些障碍以及如何克服它们。 为了收集和分析有关学生推理的信息以及提供学生反馈，该项目将开发一个在线推理导师，可以捕获和回应学生的选择，书面解释和口头解释。 这些在线推理导师将与其他教学策略一起使用，以支持学生能力推理代码的能力。 为了使研究结果广泛适用于所有学生，研究将包括不同的学生人数。这项工作涉及克莱姆森大学（Clemson University），佛罗里达大西洋大学（HSI）和HBCU霍华德大学（HOWARD University）的一家大型土地授予公共机构。评估工作是通过罗斯·霍尔曼（Rose-Hulman）领导的。计算对于国家的社会和商业至关重要。为了成为成功的计算专业人员，学生程序员需要发展该项目的重点的调试和推理技能。 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。这是一个敬业的学生学习项目；通过参与的学生学习轨道，IUSE：EHR计划支持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评估的审查标准。