All research, whether qualitative or quantitative, basic or applied, disciplinespecific or interdisciplinary, is based on theory (Flynn, Sakakibara, Schroeder, Bates, & Flynn, 1990). Theory helps us to understand why things happen when much of our data tells us only what is happening. Whether the theory develops as a logical extension of related concepts (deductively) or in response to the observation of an unexplained phenomenon (inductively), the rigor that supports theory building affords a level of interpretation and generalizability that can have a snowball effect on later progress in research and implementation. Building theory does come with substantial costs, but they are worthwhile. First, to build upon theory, researchers must be familiar with the latest literature on related topics. Processing and incorporating this information serve to improve our work by incorporating multiple viewpoints and factors into a nuanced understanding of phenomena and the variables that affect them. Second, theory building requires isolating or simultaneously examining multiple facets of key variables. Everything else must remain constant or be constantly mutable to understand the effect that variables have. This rigorous approach means effecting only incremental changes to learning environments over time. Slow progress can be difficult to accept from a practical standpoint in which we are preoccupied with helping the students we know personally as quickly as possible. However, building theory allows us to understand how to better help our future students and many others, accelerating our progress toward computing literacy for all. In this special issue, we aim to reduce the costs for researchers who are studying how novices learn programming. We have selected papers that provide comprehensive literature reviews across several areas of interest, including K-12, higher education, sociocultural and cognitive factors. The literature reviews inform rigorous empirical studies and systematic literature reviews that build theory about novice programmers. By developing sound foundations, the theory-focused papers in this issue provide a strong basis for future work in both theory and design. In the first article, Concepts before Coding: Non-Programming Interactives to Advance Learning of Introductory Programming Concepts in Middle School, Grover, Jackiw and Lundh explore methods of teaching programming concepts without requiring programming. They identified four concepts that middle school students tend to struggle with and developed nonprogramming activities, both digital and unplugged, to help students learn COMPUTER SCIENCE EDUCATION 2019, VOL. 29, NOS. 2–3, 103–105 https://doi.org/10.1080/08993408.2019.1613091

中文翻译：

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客座社论

所有研究，无论是定性的还是定量的、基础的还是应用的、特定学科的还是跨学科的，都基于理论（Flynn、Sakakibara、Schroeder、Bates 和 Flynn，1990）。当我们的大部分数据只告诉我们正在发生的事情时，理论可以帮助我们理解事情发生的原因。无论理论是作为相关概念的逻辑扩展（演绎）发展还是响应对无法解释的现象的观察（归纳），支持理论构建的严谨性提供了一定程度的解释和概括性，可以对以后的进展产生滚雪球效应在研究和实施中。建筑理论确实带来了巨大的成本，但它们是值得的。首先，要建立在理论基础上，研究人员必须熟悉相关主题的最新文献。通过将多种观点和因素融入对现象和影响它们的变量的细微理解中，处理和整合这些信息有助于改进我们的工作。其次，理论构建需要隔离或同时检查关键变量的多个方面。其他一切都必须保持不变或不断变化才能理解变量的影响。这种严格的方法意味着随着时间的推移只会对学习环境产生增量变化。从实践的角度来看，缓慢的进展可能难以接受，因为我们全神贯注于尽快帮助我们认识的学生。然而，构建理论使我们能够了解如何更好地帮助我们未来的学生和许多其他人，加速我们向所有人普及计算能力的进程。在本期特刊中，我们旨在降低研究新手如何学习编程的研究人员的成本。我们选择了在多个感兴趣的领域提供全面文献综述的论文，包括 K-12、高等教育、社会文化和认知因素。文献综述为建立关于新手程序员的理论的严格的实证研究和系统的文献综述提供了信息。通过建立良好的基础，本期以理论为重点的论文为未来的理论和设计工作提供了坚实的基础。在第一篇文章“编码前的概念：非编程交互以促进中学介绍性编程概念的学习”中，Grover、Jackiw 和 Lundh 探索了无需编程即可教授编程概念的方法。他们确定了中学生容易遇到的四个概念，并开发了数字和不插电的非编程活动，以帮助学生学习计算机科学教育 2019，VOL。29，没有。2–3, 103–105 https://doi.org/10.1080/08993408.2019.1613091