HCC: Large: Collaborative Research: Variations to Support Exploratory Programming

HCC：大型：协作研究：支持探索性编程的变体

• 批准号: 1314365
• 负责人: Anita Sarma
• 金额: $ 85.72万
• 依托单位: University of Nebraska-Lincoln
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2015-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1314365&HistoricalAwards=false
• 关键词: HCC; Large; Collaborative; Research; Variations

In any design or learning activity, exploration is a key component. Significant research and conventional wisdom show that the best way to achieve a high-quality design is to explore multiple variations and iteratively evaluate them. When novices learn a new skill or system, they must explore and practice the available options. Similarly, when experts try to understand and improve an existing design, they must explore different approaches to modifying its behavior. Unfortunately, exploration is risky, error-prone, and cumbersome using today's tools. For instance, when users decide their current design is not effective, the only mechanisms available for selectively backtracking out of changes are linear undo and version control, which make it difficult to isolate backtracking to specific edits, or else users must manually remove undesired edits, which is slow and fallible. Further, today's tools do not support comparing two variants of a design or combining elements from multiple variants. Research is showing that these manual processes inhibit exploration, making users and designs less effective.To address these problems PIs from four partner institutions have come together to undertake a research program that is both broad and deep, focusing on the creation and management of variations during a system's implementation and evolution. The goal is to discover new theories, algorithms, visualizations, and tools that support variations in code. The team will evaluate all of their approaches through lab and field studies, and they will investigate how users can be educated in more effective ways to work with variations. Based on a choice calculus for representing variations in software, they will develop a theory for formally defining and reasoning about variations. They will leverage theories of human behavior such as Minimalist Learning, Attention Investment, and Information Foraging, to develop a theory of Variation Foraging. They will develop an infrastructure including multiple levels of transcripts of users' editing operations that will support a novel form of selective undo and enable users to investigate their existing variants, return to any previous variant, and mix and match elements from multiple variants. They will develop algorithms to enable recording of interactions with variants so they can be explored and reused to explore and test new variants; these recordings will be augmented with automatically created data to help users understand behaviors they have not explicitly explored. Using this infrastructure the PIs will invent visualizations, search facilities, and interaction techniques that provide effective ways for users to find, understand, explore, reuse and create variants, and be able to ask "why" questions to understand the differences among variations of a system. For novices, an "Idea Garden" will help them explore new strategies for identifying which variations can help solve a problem and how to implement them.Broader Impacts: This research will enhance infrastructure for research and education by producing an integrated, open source web development environment for use by researchers and the world. The work will therefore benefit society by empowering the tens of millions of end-user programmers to creatively build content and applications for the web. The PIs will advance discovery while promoting learning by integrating their research into undergraduate courses on creativity and software engineering, and by supporting summer camps for at least 300 high school students per year. Project outcomes will be disseminated to researchers through publications and presentations, to computing educators through the above-mentioned camps and the National Girls Collaborative Project, and through public deployment. The PIs expect high interest because the work will be based on JavaScript, which is today's most popular programming language and for which there is a high demand for better tools. The research will address underrepresentation via its focus on investigating how to support both male and female end-user programmers, by involving high-school members of underrepresented groups, and by engaging many of the PIs? female students.

在任何设计或学习活动中，探索是关键组成部分。 重要的研究和传统观点表明，实现高质量设计的最佳方法是探索多种变化并迭代地评估它们。 当新手学习新技能或系统时，他们必须探索和练习可用的选项。 同样，当专家试图理解和改进现有设计时，他们必须探索改变其行为的不同方法。 不幸的是，使用当今的工具，探索是风险，容易出错且笨拙的。 例如，当用户确定其当前设计无效时，可选择性地回溯更改的唯一机制是线性撤消和版本控制，这使得很难隔离回溯到特定的编辑，否则用户必须手动删除不受欢迎的编辑，，这是缓慢而容易失真的。 此外，当今的工具不支持比较设计的两个变体或组合来自多个变体的元素。 研究表明，这些手动流程会抑制探索，使用户和设计的效率降低。解决这些问题的问题，来自四个合作伙伴机构的PI已齐心协力，进行了一项既广泛而深刻又深入的研究计划，重点是创建和管理变化期间的变化和管理。系统的实施和进化。 目的是发现支持代码变化的新理论，算法，可视化和工具。 该团队将通过实验室和现场研究评估他们的所有方法，他们将研究如何以更有效的方式对用户进行差异的教育。 基于代表软件变化的选择演算，他们将开发一种理论，用于正式定义和推理变化。 他们将利用人类行为的理论，例如极简主义学习，注意力投资和信息觅食，发展一种变异理论。 他们将开发一个基础架构，包括用户编辑操作的多个级别的成绩单，该运营将支持一种新颖的选择性撤消形式，并使用户能够调查其现有变体，返回任何以前的变体，并混合多个变体的元素。他们将开发算法以启用与变体的相互作用记录，以便可以探索和重新使用以探索和测试新变体；这些记录将通过自动创建的数据进行增强，以帮助用户了解他们尚未明确探索的行为。 使用此基础架构PI将发明可视化，搜索设施和交互技术，这些技术为用户提供了有效的方法，可以找到，理解，探索，重复使用和创建变体，并能够提出“为什么”问题，以理解某种变化之间的差异系统。 对于新手而言，“想法花园”将帮助他们探索新的策略，以确定哪些变化可以帮助解决问题以及如何实施问题。BROADER的影响：这项研究将通过产生集成的开源网络开发来增强研究和教育的基础架构研究人员和世界的使用环境。 因此，这项工作将通过增强数以万计的最终用户程序员来创造性地构建网络的内容和应用程序来使社会受益。 PI将通过将他们的研究纳入有关创造力和软件工程的本科课程以及每年至少300名高中生的夏令营来促进学习的同时提高发现。 项目成果将通过出版物和演示文稿传播给研究人员，通过上述营地和国家女子合作项目以及通过公共部署来计算教育者。 PI期望高度兴趣，因为这项工作将基于JavaScript，该作品是当今最受欢迎的编程语言，并且对更好的工具的需求很高。 这项研究将通过关注如何调查如何支持男性和女性最终用户程序员，参与代表性不足的群体的高中成员以及与许多PIS参与来支持男性和女性最终用户程序员的代表性不足？女学生。