Writing to Learn to Program for Undergraduate Engineers

这个国家对正确、健壮的软件的依赖促使这项工作的重要性和重要性。国家安全的关键方面取决于美国政府抵御日常网络入侵的能力。同样，国家基础设施依赖于智能电网和数以千计的其他软件驱动的控制系统，这些系统监管供水、运营工厂和运营汽车。然而，教学生如何编写高效、无错误的软件仍然是一项挑战。这个项目调查了一种新的编程教学法，通过在三个方面提出想法，将显著改善我们所依赖的程序员的培训。首先，该项目调查了识字编程思想如何融入支持学习的技术和课堂环境，即将非正式写作和编程结合起来。其次，该项目通过将写作学习(WTL)原则纳入编程的新领域，为WTL文献做出了贡献。第三，该项目通过调查与学习编程相关的学习过程以改进编程教学，为计算机科学教育文献做出贡献。该项目的目标和范围包括通过研究WTL策略如何支持初学者程序员发展来促进对技术丰富的环境中学习的理解。该项目采用个案研究设计，强调同时收集和分析定性和定量数据，并在最后口译阶段进行混合。通过访谈、写作样本、编程指标和写作指标的组合，这个项目将1)了解写作如何帮助学生将总体概念与编程解决方案的具体实现联系起来；2)确定混合写作在促进编程掌握方面所起的作用；3)确定在学习编程的同时从混合写作中受益最大的学习者类型(例如，计算专业和非计算专业)。

This country's dependency on correct, robust software drives the significance and importance of this work. Vital aspects of national security depend on the US government's ability to withstand daily cyber intrusions. Likewise, the national infrastructure depends on the smart grid and thousands of other software-driven control systems that regulate water supplies, run factories, and operate cars. Yet, teaching students how to write efficient, error-free software continues to be a challenge. This project investigates a new programming pedagogy that will significantly improve training for the programmers we rely on, by advancing ideas on three fronts. First, the project investigates the integration of literate programming ideas into technology supporting learning and into classroom environments, i.e., marrying informal writing and programming. Second, the project contributes to the writing-to-learn (WTL) literature by incorporating WTL principles into a new domain of programming. Third, the project contributes to computer science education literature by investigating the learning processes associated with learning to program in order to improve programming pedagogy.The goals and scope of this project include advancing the understanding of learning in technology-rich environments by examining how WTL strategies can support novice programmer development. This project employs a case study design that emphasizes concurrent qualitative and quantitative data collection and analysis with mixing occurring during the final interpretation stage. Through a combination of interviews, writing samples, programming metrics, and writing metrics, this project will 1) capture understanding of how writing helps students connect big-picture concepts to specific implementations of programming solutions; 2) identify roles that intermingled writing takes in promoting programming mastery; and 3) identify types of learners (e.g., computing majors, non-computing majors) that most benefit from intermingled writing while learning to program.