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

Abstract

本子計畫著重學習者在使用搜尋、標籤及註記等工具時的後設認知歷程，我們將先 以各種資訊系統運作時所使用的個人資訊、篩選過程及推薦機制等為基礎，探討學習者 如何認知與使用系統介面所呈現的資訊，以及系統是否提供可能的後設認知輔助，進而 由後設認知及批判學習的角度，提出我們自己設計的工具，並搭配適宜的學習活動，以 提升學習者對資訊工具機制及引導的覺察。 本計畫將以標籤與註記技術為基礎來發展任務彙報工具，透過書寫、合作標籤與註 記等學習活動來促進使用者的反思與批判思考，使之看到工具的限制與導引力量，並由 學習觀點對工具加以評價。同時，本計畫將各種搭建在社會網絡上的數位服務視為學習 媒體，探討學習者如何透過介面來理解系統，進而發展以視覺化為主的工具，搭配學習 活動來輔助學習者進行社會媒體的識讀與解碼，並意識到共識形成過程中資訊工具扮演 的角色。 以上述研究成果為基礎，本計畫將進一步提醒學習者所處的社群動態，以避免同質 性過高的鏡像回饋。同時將著重於語意網路等新發展，設計工具以呈現學習者本身的知 識反芻等可能問題。最後，我們將總結三年的研究成果，提出對於在全球資訊網上擴充 以後設認知為主的學習設計建議。

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.