摘要
建构主义学习理论认为协作发生在学习过程的始终,协作学习过程也是会话的过程。协作学习活动的规范设计与顺利实施有利于促进学习者之间知识共享与协同建构。如何评价协作学习是当前教育技术领域研究的焦点问题。围绕整合技术进行协作学习评价问题,我们访谈了卡耐基梅隆大学著名教授卡洛琳·佩恩斯坦·罗泽。罗泽教授认为会话在协作学习情境中具有独特价值,不仅是一种使思维清晰可见的方式,而且参与者的多样化视角有利于知识的协同创新。罗泽教授的研究聚焦于整合语言学、教育学、心理学等相关理论,深入理解协作学习中会话的社会及其实际本质,搭建提高人与人、人与计算机之间会话效果的计算系统。其研究视角是运用社会语言学和会话分析理论设计语言表征的方式和新的计算模型,使语言模式可以被机器学习;研究内容是从计算的视角分析语言与社会之间的关系,开发用于评价在线协作学习过程的工具(如Tag Helper和Light SIDE),以便为协作学习的组织者或促进者提供适合特定情境的干预机制和反馈报告。罗泽教授及其团队的重要贡献还体现在优化协作学习过程的自动化分析方法,促进协作学习支持技术从静态支持向动态支持范式转变,研发新的干预机制与动态支持技术促进大规模协作学习等。
Constructivist learning theory holds that collaboration occurs in the learning process, and collaborative learning process is the process of conversation. The normative design and smooth implementation of collaborative learning activities are conducive to promoting knowledge sharing and collaborative construction among learners. How to evaluate the effect of collaborative learning is the current focus of research in the field of education technology. We interviewed Carolyn Penstein Rosé, a well-known professor from Carnegie Mellon University, in order to analyze and evaluate the effect of collaborative learning. Professor Rosé considers that conversation has a unique value in collaborative learning situations since it is a way to make the mind clear and visible, and furthermore, the diverse perspectives of participants are conducive to collaborative innovation of knowledge. Her research program is focused on better understanding the social and pragmatic nature of conversation, and using this understanding to build computational systems that can improve the efficacy of conversation between people, and between people and computers. In order to pursue her research goals, she integrates and extends approaches from computational discourse analysis and text mining, conversational agents, and computer supported collaborative learning. Her research perspective is the method of using insights from theories in sociolinguistics and discourse analysis to motivate the design of novel representations of language which enables automated social interpretation of language. Designing computational models that reflect these insights makes the patterns in language learnable. Her research content is from the computational perspective to analyze the relationship between language and the society,and to develop tools for evaluating online collaborative learning processes(such as Tag Helper and Light SIDE), in order to provide appropriate intervention mechanism and feedback reports for the organizers or promoters of the collaborative learning. The important contribution of professor Rosé and her group also includes: the automation analysis method of optimizing collaborative learning process, enabling the paradigm shift of collaborative learning support technology from static support to dynamic support; the design and development of new intervention mechanisms and dynamic support technologies for large-scale collaborative learning, and so on.
出处
《现代远程教育研究》
CSSCI
2017年第6期3-10,共8页
Modern Distance Education Research
基金
教育部哲学社会科学研究重大课题"‘互联网+’教育体系研究"(16JZD043)
关键词
评价协作学习
会话分析
文本挖掘
机器学习
计算社会语言学
Assessment of Collaborative Learning
Conversation Analysis
Text Mining
Learning Through Discussion
Machine Learning
Computational Sociolinguistics
