Technologies to Support Online Knowledge Sharing and Retrieval for Feature-Rich Software Applications

功能丰富的软件应用程序（例如，Photoshop, Fusion 360, AutoCAD, Excel）通过扩展的命令和工具集实现广泛的任务。然而，它们广泛的功能和特定于领域的词汇表可能会使用户难以入门和扩展他们的技能。软件学习的一个相对较新的现实是帮助资源的松散连接和分布式特性，Internet上现在有了由其他用户编写的材料（例如，教程、讨论论坛、Q&A站点）。目前，用户社区有无与伦比的机会来贡献资源，以解决应用程序不同用户群的独特能力、环境和期望的结果。其他用户也有可能利用这些量身定制的资源来提高他们的技能。与此同时，当前的工具和平台不一定能吸引所有用户组的观点，寻找适当的帮助资源可能是用户受挫的一个重要来源。我的长期目标是告知并开发一些技术，使这个复杂的帮助生态系统成为所有功能丰富的软件用户的一个无缝且有益的活动。对于这个资助周期的研究，我关注三个短期目标：1)创造技术，扩大软件用户在网上贡献他们的知识和经验，强调两个未被充分代表的群体（妇女和儿童）。2)为探索性学习者创造技术，这些学习者希望找到能够扩展其软件技能的材料。3)研究新的评估方法，增加和扩大参与者池，并捕获软件学习的新措施。根据人机交互（HCI）研究中已建立的最佳实践，我的HQP和我将进行混合方法形成性研究，以创建支持用户为功能丰富的软件贡献和寻找适当的在线外部资源的新技术。在开发我们的底层算法时，我们将研究机器学习、自然语言处理和协同过滤。我们将通过实验室和实地的预期目标人群的经验评估来验证我们的方法和技术。拟议的研究将包括培训大约14名HQP，为他们提供以用户为中心的交互设计、网络技术、应用人工智能和定量/定性分析技术方面的技能。我们的研究将产生新颖的原型和设计指南，为下一代功能丰富的软件和知识共享社区提供信息。拟议的研究还将通过说明在设计新技术时首先考虑妇女和儿童受众的方法，解决计算多样性的重要方面。

Feature-rich software applications (e.g., Photoshop, Fusion 360, AutoCAD, Excel) enable a wide range of tasks through extended command and tool sets. Their widespread functionality and domain-specific vocabulary, however, can make it difficult for users to get started and to expand their skills. A relatively new reality of software learning is the loosely connected and distributed nature of help resources, with the Internet now ripe with materials (e.g., tutorials, discussion forums, Q&A sites) authored by other users. There are currently unparalleled opportunities for user communities to contribute resources that address the unique abilities, contexts and desired outcomes of an application's diverse user base. There is also the potential for other users to leverage these tailored resources to grow their skills. At the same time, current tools and platforms are not necessarily eliciting the perspectives of all user groups, and finding appropriate help resources can be a significant source of user frustration. My long-term objective is to inform and develop technologies that make contributing to and navigating this complex help ecosystem a seamless and rewarding activity for all feature-rich software users. For the research in this funding cycle, I focus on three short-term objectives: 1) Creating technologies that widen the pool of software users contributing their knowledge and experiences online, emphasizing two underrepresented groups (women and children). 2) Creating technologies for exploratory learners, who want to find materials that expand their software skills. 3) Investigating new evaluation approaches that increase and broaden participant pools, and capture new measures of software learning. Following established best practices in Human-Computer Interaction (HCI) research, my HQP and I will conduct mixed-method formative studies to create novel technologies that support users in contributing to and finding appropriate online external resources for feature-rich software. In developing our underlying algorithms, we will investigate machine learning, natural language processing, and collaborative filtering. We will validate our approaches and techniques through empirical evaluations with the intended target populations both in the lab and in the field. The proposed research will involve training approximately 14 HQP, providing them with skills in user-centred interaction design, Web technologies, applied artificial intelligence, and quantitative/qualitative analysis techniques. Our research will produce novel prototypes and design guidelines to inform the next generation of feature-rich software and knowledge-sharing communities. The proposed research will also address important dimensions of computing diversity by illustrating ways to consider women and child audiences upfront in the design of new technologies.