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

在NSF改善本科STEM教育计划：教育和人力资源（IUSE：EHR）的支持下，该项目旨在通过改善计算机科学教育来服务于国家利益。 为了实现这一目标，该项目将确定学生对代码的理解时出现的误解，并制定策略来克服这些误解。 该项目将专注于使用自动分析来教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，这是计算教育最基本和最重要的目标之一。跟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，并将他们的推理扩展到广义输入，从而形成抽象的，广泛的理解。本项目旨在确定自动化方法的哪些方面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。本项目有两个目标。首先，它的目的是了解学生在跟踪特定的，具体的输入代码时所面临的学习障碍，以及他们最终在将推理概括为抽象的符号输入时所面临的障碍。第二，该项目旨在了解这些障碍为什么会出现以及如何克服。 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辅导员，可以捕捉和回应学生的选择，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结合使用，以支持学生对代码进行推理的能力的发展。 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群体。这项工作涉及克莱姆森大学，一个大型的赠地公立机构，佛罗里达大西洋大学，一个HSI，和霍华德大学，一个HBCU。评价工作由Rose-Hulman领导。计算是国家社会和商业的基础。要成为成功的计算机专业人士，学生程序员需要开发调试和推理技能，这是这个项目的重点。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。IUSE：EHR项目是一个面向学生的学习项目;通过面向学生的学习项目，IUSE：EHR项目支持有前途的实践和工具的创建、探索和实施。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。

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.