|標題:||從Web 2.0到Web 3.0：資訊科技對學習動機、歷程與評量的影響---子計畫二：發展對web資訊服務的後設認知工具以輔助學習|
Developing Tools for Meta-Cognition on Web Information Services to Assist Learning
This project focuses on meta-cognition processes of learners when they employ information tools for search, tagging and annotation. We will start with examining the types of personal information, selection processes, and recommendation mechanisms used by varied information services before investigating how learners recognize and utilize information on screen. Some information systems may already provide tools that help meta-cognition if users are aware of such functionality. Based on our analysis, we will propose our own set of tools from viewpoints of meta-cognition and critical learning, and design matched learning activities for promoting the awareness level of learners toward the mechanisms of information tools and their implicit but persuasive influence. We will develop a set of task debriefing tools based on tagging and annotation technology and learning activities such as collaborative authoring, tagging and annotation to trigger learners’ reflection and critical thinking. The purpose is to reveal the influential power of available information tools and their limitations, especially in terms of learning. In the meantime, we consider varied social-network-based digital services learning media, thus investigate how learners interpret systems via their interfaces and form their attitude toward such social media in their daily learning processes. We will then develop visualization tools as well as activities to help learners’ literacy and ability of decoding on social media so that they become more aware of the role played by seemingly friendly information services in the process of consensus formation. Based on our research findings, we will identify and develop tools that help reminding learners about the dynamics of their learning communities, so as to preventing feedbacks from knowledge and opinion mirrors resulted from overly homogeneous groups. We will also follow the trend of new information technologies on the web, including semantic networks employed by intelligent agents, in order to reveal in advance possible learning problems such like self-feedback owing to personal historical data recorded by the system and later recommendation based on such information. Finally, we will bring together all research discoveries during this three-year project and propose our suggestions for learning tool design in terms of enhancing meta-cognition for learning on the web.