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摘要： In Computer Science, mathematics plays a fundamental role in developing analytical thinking and algorithmic reasoning skills. However, students often struggle to grasp the significance and applicability of mathematics in this field. They need a clear understanding of math concepts and skills for the application of mathematical constructs in computational problem-solving. One of the challenges for math teachers is to help poorly prepared students at introductory levels. This requires an innovative approach that bridges the gap between theory and application. Computational problem-solving requires more than just memorizing formulas. Examples of real- world problem-solving applications of formulas can be integrated into computational solution techniques to develop students' intuitive concepts of math at introductory levels. Proper integration of motivational activities with practice-based math instructions in multiple classes requires careful planning and execution.

摘要： Undergraduate computer science and software engineering students benefit significantly from in-depth reviews of their code early and often in their courses. Performing these reviews is time-consuming for teaching assistants and professors to complete, consequently impacting the timeliness and consistency of the provided feedback. When code feedback is not delivered close to the time of authorship, the utility of the review for students is diminished. Prior work with Automatic Static Analysis Tools has shown promise at using artificial intelligence to automate code reviews, with some success integrating them into classroom environments. To leverage new advances in Generative Pre-Trained Transformer (GPT) models, this work reports on an Automatic Review Tool (ART) to provide timely, automatically generated code reviews. ART was evaluated in a second-semester computer science course by integrating ART into the course's Github-based assignment submission system. A cohort of student volunteers (N = 74) read the ART reviews and provided feedback using a survey spanning two of their course assignments. The results of this pilot study show that students perceived ART was successful at detecting defects and offering style-based suggestions, and students were receptive to receiving future automated reviews of their work.

摘要： We present our methodology for a four-credit course that serves as a capstone to the Computer Science B.S. degree program. Our course is split between two semesters as a 1-credit course in the fall and a 3-credit course in the spring. The general concept is that students use the fall to pick a project and develop a proposal that is then implemented during the spring. But there is much more that we include.

关键词： 高校   实验室   管理   问题   优化  

摘要： 文章对南昌师范学院数学与信息科学学院计算机实验室的基本现状进行了介绍,对管理体系、开放力度和信息化管理方面存在的问题进行了分析,并提出了实验室的优化建议。

关键词： 虚拟教研室   计算机科学与技术专业   国家一流专业   地方院校  

摘要： 虚拟教研室是信息化时代为全面提高教师教书育人能力开展的新型基层教学组织建设和改革的重要探索。文章以丽水学院计算机科学与技术国家级一流本科专业建设为契机,结合本专业的专业定位、特色优势以及丽水学院作为山区地方性本科院校的特点,从完善虚拟教研室制度和团队建设、构建特色鲜明的专业核心价值体系、增强人才培养的协同度、共建共享各类优质教学资源库、开展高水平的跨专业跨校跨域教学教研活动等5个方面思考与探索了地方本科院校计算机科学与技术专业虚拟教研室的建设路径,最后总结了本虚拟教研室当前的实施情况、所遇问题及解决方案。

关键词： 高职院校   非计算机专业   计算机应用能力  

摘要： 在信息高速发展的当下,信息技术已融入人们的生产生活中。作为新一代学生,必须要具备较强的计算机应用能力,从而跟紧时代发展步伐。对于高职院校而言,如何使非计算机专业学生具备一定的计算机基础知识、较强的计算机应用能力,使其成为顺应科技、社会发展的专业技术人才成为现下重要的研究课题。本文对高职院校非计算机专业学生计算机应用能力培养存在的问题以及相应应对策略展开简要论述。

摘要： Software design complexity estimation is a critical aspect of the software development process, determining project timelines, budgets, and resource allocation. Accurate estimations are essential for successful project planning and management. Traditional estimation methods often face challenges, resulting in inaccuracies and project delays. Some of the limitations of traditional estimation approaches include 1) Design complexity, where the numerous variables make the manual calculation and comprehension very cumbersome and prone to errors. 2) Project requirements, customer design, or technology requirements can change during the development process, rendering initial estimates outdated and unreliable. 3) Available data limitations, where the accessible historical data might not be representative of the current project, making it challenging to extrapolate accurate estimates. 4) Subjective decisions, where traditional estimation methods often rely on the expertise and intuition of human estimators, leading to biased and inconsistent results. 5) Finally, the customary manual estimation is time-consuming, impacting the overall project timeline.