Supporting Learning and Enhancement of Programming Competencies Through Use of Immediate Critiques of Antipatterns in Novice Programmer Code

这个项目旨在通过开发一个系统来自动检测学生在编程课上所犯的编码错误，从而为国家利益服务。为学生提供丰富、即时的反馈可以显著提高学习成果，从而提高编码技能。由于班级规模的迅速扩大和教师的短缺，使用人工评分员及时提供反馈是很困难的。这个项目的目标是开发一个系统，可以自动提供高质量的反馈给学生在入门编程课程。这个系统一旦开发出来，资源有限的院系就可以使用它来向学生提供及时的反馈。其结果将是拥有强大编码技能的学生，他们将准备好满足当前技术劳动力对程序员的需求。项目团队将扩展现有的系统WebTA，以研究学生在编程入门课程中犯的常见错误。在一年级的工程课程中，将使用混合方法来评估使用WebTA作为学习工具的影响。假设这种干预将：(a)提高学生的计算技能，(b)提高学生的计算和工程自我效能，(c)使学生和教师能够围绕反模式用一种共同的语言进行交谈。学生将使用WebTA参与编码、反思反馈和做出改变的紧密学习周期。第一年的讲师将协助识别和编码新手反模式，从而产生MATLAB反模式库。项目团队将与课程讲师合作，将反模式的术语和示例嵌入到他们的教学材料中。WebTA将作为一个免费的软件系统开发。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。通过参与学生学习轨道，该计划支持有前途的实践和工具的创建，探索和实施。该奖项反映了美国国家科学基金会的法定使命，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 developing a system that will automatically detect coding mistakes made by students in programming classes. Providing rich, immediate feedback to students significantly improves learning outcomes resulting in better coding skills. Providing feedback in a timely manner using human graders is difficult due to rapidly increasing class sizes and instructor shortages. The goal of this project is to develop a system that can automatically provide high-quality feedback to students in introductory programming classes. Once developed, the system can be used by departments with limited resources to provide timely feedback to students. The result will be students with strong coding skills who will be ready to meet the current demand for programmers in the technology workforce.The project team will extend an existing system, WebTA, to study the common errors that are made by students in introductory programming courses. A mixed-methods approach will be used to evaluate the impacts of using WebTA as a learning tool in a first-year engineering course. The hypothesis is that this intervention will: (a) improve students’ computing skills, (b) improve students’ computing and engineering self-efficacy, and (c) enable students and instructors to converse in a common language around antipatterns. Students will use WebTA to engage in a tight learning cycle of coding, reflecting on feedback, and making changes. First-year instructors will assist in identifying and encoding novice antipatterns, resulting in a MATLAB antipattern library. The project team will partner with course instructors to embed the terminology and examples of antipatterns in their instructional materials. WebTA will be developed as a freely available software system. 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.