AI 中文总结
本文针对理论计算机科学课程作业人工评分反馈滞后、缺乏实践检验的问题，提出将自动评分系统DOMjudge用于理论课程，开发了DOMtutor，可提供即时反馈与实践经验。
AI 中文摘要
大学计算机科学教学往往采用较为经典且偏向理论的结构：前者指“灌输式”授课搭配作业提交与人工评分，反馈滞后（若有的话）；后者指作业常以概念层面提出，需在纸上勾勒解题思路，却不通过实践检验。理论计算机科学相关科目尤其如此，比如命题逻辑、一阶逻辑或自动机理论课程。自动执行并评估代码的框架（又称自动评分系统）有时用于辅助教学，能提供（近乎）即时反馈与实践经验，促进反思分析，但其使用通常仅限编程/实践导向课程。本文提出两点：（i）将自动评分系统也用于（尤其是）理论课程；（ii）采用已建立的DOMjudge系统，该系统还用于国际大学生程序设计竞赛等场合。
英文摘要
Teaching computer science at universities is often structured rather classically and theory oriented. The former refers to "transmission"-style lectures accompanied by exercises which are submitted and graded manually, providing delayed feedback (if any). The latter refers to exercises often posed at a conceptual level, requiring solution ideas to be sketched out on paper, but not put to the test in practice. By its nature, this is particularly true for subjects relating to theoretical computer science, such as courses on propositional or first-order logic or automata theory. Frameworks that automatically execute and evaluate code (also called autograders) are sometimes used to augment teaching. They provide (near) instant feedback and hands-on experience, prompting reflective analysis. However, their use usually is reserved for programming / practically oriented courses. We propose to (i) use autograders also (and especially) for theoretical courses and (ii) use the established DOMjudge system, which is used, among others, for the International Collegiate Programming Contest.
