HCC: Small: Learning-by-Explaining to a Virtual Human

HCC：小：通过向虚拟人解释来学习

• 批准号: 0916858
• 负责人: Jonathan Gratch
• 金额: $ 49.59万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0916858&HistoricalAwards=false
• 关键词: HCC; Small; Learning; Explaining; Virtual

The primary goal of this project is to better understand the cognitive and social factors in a learning paradigm called learning-by-explaining and to build a virtual training partner to promote better learning in this paradigm. Learning-by-explaining is an effective learning technique used by human tutors that has yet to be exploited by the intelligent tutoring system community. In this technique, students are encouraged to explain a concept either to another or themselves. Decades of research shows that generating such explanations can lead to deep understanding of the learning material, and that these learning effects are particularly strong when the explanations are delivered in a social context (i.e., explaining to a peer or tutor), as opposed to explaining to oneself. These effects have even been observed when the "other" is a computer generated character. There are competing views on why learning-by-explaining works. Cognitive theories emphasize how the act of generating an explanation helps student recognize gaps and conflicts in their mental models and creates opportunities for mental model revision and that learning partners facilitate this process by identify missing knowledge and prompting for further clarification. In contrast, social theories argue that the presence and behavior of the explainee motivates learners to invest more effort into the learning tasks, resulting in learning gains. This project aims to gain better understanding of the interplay between the cognitive and socio-relational feedback, how they impact the learning-by-explaining process and how to build an explainee agent that facilitates learning-by-explaining. The project seeks to answer two research questions: 1) Will cognitive feedback or socio-relational feedback facilitate learning-by-explaining? 2) How to build an effective virtual training partner "a virtual explainee" in the learning-by-explaining context? This project will inform the development of next generation intelligent tutoring systems and has the potential to significantly enhance basic understanding of the design of human centered computing. It explores factors related to effective multi-modal interfaces and helps to identify crucial factors that impact social impressions and effective interaction which may facilitate a new generation of more human-centric approaches to human learning. The project will also support the research activities of underrepresented groups (the senior researcher is a woman and the work will support the training of an intern from a HCBU-MI). It will enhance infrastructure for research and education by making advanced research tools and corpora freely available to the research community. These tools provide a novel method to study and enhance the effectiveness of computer-mediated and human-computer interaction, allowing the experimental manipulation of key mediating factors in such interactions. The work will advance discovery and understanding while promoting teaching and learning as it will be performed within the context of USC's Centers for Creative Technologies, a university-affiliated federal laboratory with a core mission to develop and disseminate advanced virtual reality training technology with an extensive track record in transitioning technology into the classroom.

该项目的主要目标是更好地了解认知和社会因素的学习范式称为学习解释和建立一个虚拟的培训伙伴，以促进更好地学习这种范式。通过解释学习是一种有效的学习技术，人类教师使用，尚未被开发的智能教学系统社区。在这种技术中，鼓励学生向他人或自己解释一个概念。几十年的研究表明，产生这样的解释可以导致对学习材料的深入理解，并且当解释在社会背景下传递时，这些学习效果特别强（即，向同伴或导师解释），而不是向自己解释。甚至当“他人”是计算机生成的角色时，也观察到了这些效果。关于为什么通过解释学习有效，存在着不同的观点。认知理论强调如何产生一个解释的行为，帮助学生认识到他们的心理模型的差距和冲突，并创造心理模型修正的机会，学习伙伴通过识别缺失的知识和提示进一步澄清促进这一过程。相反，社会理论认为，被解释者的存在和行为激励学习者投入更多的努力到学习任务中，从而获得学习收益。该项目旨在更好地理解认知和社会关系反馈之间的相互作用，它们如何影响解释学习过程，以及如何构建一个解释者代理，促进解释学习。该项目试图回答两个研究问题：1）认知反馈或社会关系反馈是否会促进解释学习？2)如何在讲解中学习的情境下建立有效的虚拟培训伙伴“虚拟讲解者”？该项目将为下一代智能教学系统的开发提供信息，并有可能显着提高对以人为中心的计算设计的基本理解。它探讨了与有效的多模态界面相关的因素，并有助于确定影响社会印象和有效互动的关键因素，这些因素可能会促进新一代以人为本的人类学习方法。该项目还将支持代表性不足群体的研究活动（高级研究员是一名女性，其工作将支持培训一名来自一所高等职业学院的实习生）。它将通过向研究界免费提供先进的研究工具和语料库来加强研究和教育的基础设施。这些工具提供了一种新的方法来研究和提高计算机介导的人机交互的有效性，允许在这种交互中的关键介导因素的实验操作。这项工作将推进发现和理解，同时促进教学和学习，因为它将在南加州大学创意技术中心的背景下进行，该中心是一个大学附属的联邦实验室，其核心使命是开发和传播先进的虚拟现实培训技术，在将技术过渡到课堂方面有着广泛的记录。