Automated Feedback in Undergraduate Computing Theory Courses

计算理论提出并回答了诸如“哪些问题是可有效计算的，哪些是不可有效计算的？”回答这些问题对任何计算机科学家和任何类型的软件开发都很重要。例如，在花费大量时间编写程序来解决问题之前，最好确定问题是否可计算。不幸的是，许多学生对计算理论感到困惑，因为它比其他计算机科学主题更加抽象和数学化。就像在其他知识领域一样，学生需要通过实践来更好地掌握计算理论。一个问题是，对他们的工作的反馈不是即时的，当学生等待反馈时，他们停止了与材料的互动。他们可能要等好几天，因为批改作业通常会花费老师很多时间，而老师可能有很多作业要批改。这个项目将通过开发一个自动化的反馈工具来提高对计算机理论学生反馈的速度和潜在的质量。反馈将告诉学生一个解决方案是否正确，一个令人信服的原因，为什么一个不正确的解决方案是不正确的，并提供有关解决方案质量的信息。学生将能够使用这种即时反馈来改进他们的解决方案，获得更多的练习，并增加他们对材料的理解。除了构建反馈工具外，本项目还旨在对反馈工具的有效性进行研究。这个项目有潜力为培养强大的计算机劳动力做出贡献，并支持学生独立学习技能的发展。虽然理解计算理论概念是非常重要的，但它是具有挑战性的。通常，作为第一步，学生在计算理论课上学习各种计算模型。为了理解更复杂的计算问题，学生需要充分理解这些模型的可能性和局限性。JFLAP （Java形式语言和自动机包）是一个广泛使用的工具，它为学生提供了一种与这些概念交互的方式。然而，与该领域的其他交互式工具一样，它不提供关于学生解决方案的详细反馈。该项目将在JFLAP之上构建一个反馈和分级工具，以增加反馈工具具有广泛适用性的可能性。为了实现这一目标，该项目将在三个研究领域的背景下开发和评估该工具：(1)计算机科学教育：使用该工具的学生是否比不使用该工具的学生更好地理解理论计算机科学概念？(2)理论计算机科学：软件如何产生一个令人信服的理由来解释为什么学生的解决方案是不正确的？(3)人工智能：如何对学生解决方案的质量进行反馈？该项目的研究和软件开发活动将涉及10名本科生，他们将被招募，重点包括妇女和失聪/听障学生。因此，该项目将直接促进这些学生的科学和专业发展。项目成果将在科学会议和研讨会以及该大学的创新博览会上传播，该博览会将有35,000名参观者参加，其中包括中学生和高中生。开发反馈工具并完成对其有效性的研究，有可能改善计算理论的教学和学习。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。

Computing theory poses and answers questions such as "Which problems are efficiently computable and which are not?" Answering such questions is important for any computer scientist and for any kind of software development. For example, it is better to determine if a problem is computable before spending a lot of time trying to write a program to solve it. Unfortunately, many students struggle with computing theory, because it is more abstract and mathematical than other computer science topics. As in any other knowledge area, students need to practice to get better at computing theory. A problem is that feedback on their work is not immediate and, while students wait for feedback, they stop interacting with the material. They may have to wait for days, since grading an assignment often takes a lot of instructor time and the instructors may have many assignments to grade. This project will increase the speed and, potentially, the quality of feedback to computing theory students by developing an automated feedback tool. The feedback will tell students whether a solution is correct or not, a convincing reason why an incorrect solution is incorrect, and provide information about the quality of a solution. Students will be able to use this immediate feedback to improve their solutions, get more practice, and increase their understanding of the material. In addition to building the feedback tool, this project aims to conduct research on the feedback tool's effectiveness. This project has the potential to contribute to the education of a strong computing workforce and to support development of students' independent learning skills. Although understanding computing theory concepts is very important, it is challenging. Typically, as a first step, students in computing theory classes learn about various models of computation. To understand more complex computational issues, students need to fully comprehend the possibilities and limitations of these models. JFLAP (Java Formal Languages and Automata Package) is a widespread tool that provides a way for students to interact with these concepts. However, like other interactive tools in this area, it does not provide detailed feedback on student solutions. This project will build a feedback and grading tool on top of JFLAP, to increase the likelihood that the feedback tool will have broad applicability. To accomplish this goal, the project will develop and evaluate the tool in the context of three research areas: (1) Computer Science Education: Do students who use the tool understand theoretical computer science concepts better than students who do not use the tool? (2) Theoretical Computer Science: How can software generate a convincing reason for why a student solution is incorrect? and (3) Artificial Intelligence: How can feedback be given about the quality of a student's solution? The project's research and software development activities will involve ten undergraduate students, who will be recruited with emphasis on including women and deaf/hard-of-hearing students. Thus, the project will directly contribute to these students' scientific and professional development. Project outcomes will be disseminated at scientific conferences and workshops, as well as at the University's innovation fair, which is attended by 35,000 visitors, including middle and high school students. Developing the feedback tool and completing research on its effectiveness has the potential to improve instruction and learning of computing theory.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.