Pattern-Based Programming Instruction

我们正在为计算机编程入门课程开发基于模式的方法的课程材料。典型的编程教学往往侧重于语言，并让学生开发原始的，往往是糟糕的解决方案的问题。 很少有时间从教学人员那里得到高质量的反馈。此外，目前的教学显示教育理论和实践之间的联系很少。 正在开发和测试一个基于模式的计算机科学入门课程。问题和代码模式被确定并选择纳入课程。基于印刷的教学材料是通过开发，评估和修订的周期。一个自动化的环境，支持基于模式的教学，并提供真正成功的教学所需的更高层次的学生实践的监督原型将产生。基本原则和理论的方法提出和介绍。 建议的教学材料和系统将提供一个坚实的测试床，为进一步研究和解释标准的问题和程序在计算。基于模式的方法显着提高了第一门课程后，学生制作的程序的质量。虽然这个项目并不侧重于任何特殊的观众，拟议的程序设计教学方法应最终提高学生的吸引力和保留。 除了内部评估外，两名外部审查员将在项目期间对材料进行两次评估。学生在新方法下的表现将被测试，并与传统教学下的学生进行比较。将评估学生和教师的看法。将制作描述性论文并提交给适当的（CS-Ed AI）会议和期刊。

We are developing curriculum materials for a pattern-based approach in introductory computer programming courses. Typical programming instruction tends to focus on the language and has students develop original and often poor solutions to problems. Little time for quality feedback from instructional staff is available. Additionally, current instruction shows little connection between educational theory and practice. A pattern-based curriculum for introductory computer science is being developed and tested. Problem and code patterns are identified and selected for inclusion in the course. Print-based instructional materials is produced via a cycle of development, evaluation, and revision. A prototype of an automated environment that supports pattern-based instruction and provides supervision for the higher level of student practice necessary for truly successful instruction will be produced. Underlying principles and theory for the approach are proposed and presented. The proposed instructional material and system will provide a solid test bed for further research and explication of standard problems and programs in computing. The pattern-based approach significantly improves the quality of programs produced by students after a first course. While this project does not focus on any special audience, the proposed approach to programming instruction should ultimately enhance both attraction and retention of students. In addition to internal evaluation, two external reviewers will assess the material twice during the project. Student performance under the new approach will be tested and compared with that of students under traditional instruction. Student and instructor perceptions will be assessed. Descriptive papers will be produced and submitted to appropriate (CS-Ed & AI) conferences and Journals.