Assessing the Feasibility and Impact of Using Online Problem-Solving in Computer Science

计算机科学(31)这个项目开发了四个关于编程语言主题的问题生成器。问题生成器被设计为将问题生成为问题模板的参数化实例。他们的表现和使用经过了四个学期的评估。预计问题生成器将促进学生的主动学习，并提高学生解决问题的技能。以问题为基础的学习可以改善长期记忆。研究人员提倡使用自定进度的练习，练习建立解决问题的技能，并在课程中使用频繁的、分级的作业。教职员工越来越多地转向使用技术为学生提供实践问题。他们正在开发产生问题的程序，并将其提供给学生进行练习。但是，这种为学生提供频繁的、自定进度的练习的程序很少被尝试用于计算机科学主题，因为计算机科学中的问题并不总是定量的，而且它们通常依赖于任意计算机程序的结构。这个项目根据计算机科学课程的独特限制，调查在计算机科学主题中使用问题生成的潜力。

Computer Science (31) This project develops four problem-generators on programming languages topics. The problem generators are designed to generate problems as parameterized instances of a problem template. Their performance and use is evaluated over four semesters. The problem generators are expected to promote active learning among students and to improve the problem-solving skills of students. Problem-based learning improves long-term retention. Researchers have advocated the use of self-paced exercises, practice to build problem-solving skills, and the use of frequent, graded assignments in a course. Faculty are increasingly turning to the use of technology to provide practice problems to students. They are developing programs to generate problems, and making them available to students for practice. But, such programs that provide students with frequent, self- paced exercises have been infrequently attempted for computer science topics, because problems in computer science are not always quantitative, and they often depend on the structure of arbitrary computer programs. This project investigates the potential for use of problem-generations in computer science topics in light of the unique constraints of the computer science curriculum.