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: 1314399
• 负责人: Amy Ko
• 金额: $ 35.62万
• 依托单位: University of Washington
• 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 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1314399&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，探索都是一个关键组成部分。重要的研究和传统智慧表明，实现高质量设计的最佳方法是探索多种变体并对其进行迭代评估。当新手学习一项新技能或新系统时，他们必须探索和实践可用的选项。同样，当专家试图理解和改进现有的设计时，他们必须探索不同的方法来修改其行为。不幸的是，使用今天的工具进行探索是有风险的、容易出错的，而且很麻烦。例如，当用户认为当前的设计不有效时，可用于选择性回滚更改的唯一机制是线性撤消和版本控制，这使得很难将回滚隔离到特定的编辑，否则用户必须手动删除不希望的编辑，这是缓慢且容易出错的。此外，今天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，这些手工过程抑制了探索，降低了用户和设计的效率。为了解决这些问题，来自四个合作机构的pi聚集在一起，开展了一项既广泛又深入的研究计划，重点关注系统实施和进化过程中变化的创建和管理。我们的目标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实地研究来评估他们的所有方法，他们将调查如何以更有效的方式教育用户处理各种变化。基于表示软件变化的选择演算，他们将开发一种正式定义和推理变化的理论。他们将利用人类行为的理论，如极简学习、注意力投资和信息觅食，来发展变异觅食理论。他们将开发一种基础设施，包括用户编辑操作的多级转录本，支持一种新颖的选择性撤销形式，使用户能够调查现有的变体，返回到任何以前的变体，并混合和匹配来自多个变体的元素。他们将开发算法来记录与变体的交互，以便对它们进行探索和重用，以探索和测试新的变体；这些记录将被自动生成的数据增强，以帮助用户理解他们尚未明确探索的行为。使用这个基础结构，pi将发明可视化、搜索工具和交互技术，为用户提供有效的方法来发现、理解、探索、重用和创建变体，并能够问“为什么”问题来理解系统变体之间的差异。对于新手来说，“创意花园”将帮助他们探索新的策略，以确定哪些变化有助于解决问题以及如何实施它们。更广泛的影响：这项研究将通过为研究人员和全世界提供一个集成的、开源的网络开发环境来增强研究和教育的基础设施。因此，这项工作将使数以千万计的最终用户程序员能够创造性地为网络构建内容和应用程序，从而造福社会。这些pi将通过将他们的研究整合到创造力和软件工程的本科课程中，以及每年为至少300名高中生提供夏令营支持，在促进学习的同时推进发现。项目成果将通过出版物和报告向研究人员传播，通过上述营地和全国女童合作项目向计算机教育工作者传播，并通过公共部署传播。项目负责人期望有很高的兴趣，因为这项工作将基于JavaScript，这是当今最流行的编程语言，对更好的工具有很高的需求。这项研究将通过调查如何支持男性和女性最终用户程序员来解决代表性不足的问题，方法是让代表性不足群体的高中成员参与进来，并让许多pi参与进来。女学生。