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    题名: 利用雲端知識工具輔助大學生自我導向學習之多型態多文本閱讀素養研究(2/3)
    Using Cloud Epistemic Tool to Assist University Students` Self-Directed Learning in Multimodal and Multitext Reading Literacy
    作者: 洪煌堯
    Hong, Huang-Yao
    李元萱
    贡献者: 教育系
    关键词: 多型態多文本閱讀;認知監控;後設認知監控;知識鷹架
    multi-modal multiple-text reading;cognitive monitoring;metacognitive monitoring;epistemic scaffolding
    日期: 2021-08
    上传时间: 2022-07-13 11:25:48 (UTC+8)
    摘要: 在網路開放式的環境，人們常主動的進行資訊搜尋，也常被動接收搜尋引擎所呈現給我們的訊息，或是閱讀社群媒體中社群伙伴所推或是轉發的文章。除了文字文本外，網路上還充斥著多型態的文本，例如：圖片、表格、動畫、影音影片…等。在多重來源訊息閱讀過程中，如何辨別與判斷文本的來源與所持的證據？能否推論作者的立場與作文用意？如何進行有效搜尋，避免對搜尋引擎推薦與排序機制的依賴？如何在多重訊息來源與文本中進行學習？都是現代人的多文本閱讀挑戰。本案基於「多文本使用整合架構」，從讀者的準備、執行、產出三階段深入探討多文本閱讀的可能介入機制。藉助雲端計算、人工智慧和機器學習等技術，本案的目的為： 1. 建立「多文本閱讀互動系統」，透過系統促發的知識認知監測機制，和互動式閱讀理解系統，強化大學生對訊息的反思意識和多文本閱讀素養建構。 2. 發展基於社群媒體的「多文本閱讀聊天機器人」，誘發學生去思考資訊的正確性、可信度、及多重驗證的主動建構歷程。 3. 利用學習分析(Learning Analytics)深度剖析學生多文本閱讀歷程、人機互動、閱讀行為潛在群組與關聯性分析。 申請人希望透過科技知識中介工具介入，增進學習者多文本閱讀時之認知、後設認知、與行為策略的應用。
    In the open online environment, people may actively search for information to read or passively to read information that is tweeted or shared by friends on social media. Besides printed texts, there are also multimodal texts including graphs, tables, animations, and videos. While reading these multi-modal and multi-source texts, people are facing challenges such as how to evaluate the source and evidence of the texts, how to infer the purpose of the author, how to perform effective search to avoid dependence on the engine’s recommendation, and how to learn amid the multi-source and multiple text reading. Based on the theory of an Integrated Framework of Multiple Text Use, this project will investigate university students’ multiple text reading from the preparation, execution, and production stages to provide possible effective intervention. With the advent of cloud-computing, artificial intelligence, and machine learning, the project centers on the three aims. 1. Develop a “Multiple Text Reading Interactive System” to enhance university students’ reflection and multiple text reading literacy via the system prompted epistemic metacognition monitoring and the interactive reading system. 2. Develop a “Multiple Text Reading Chatbot” based on the Messenger platform to prompt university students’ evaluation on the veracity, trustworthiness, and multiple justification process. 3. Apply Learning Analytics to investigate students’ multiple text reading process, human-machine interaction, and latent profiles behind the reading behaviors as well as associations among all the examined aspects. I hope to develop the above technology-enhanced epistemic tools to improve university students’ cognitive strategies, metacognitive strategies, and behaviors during their multiple text read.
    關聯: 科技部, 計畫編號: MOST108-2511-H007-006-MY3, 研究期間: 10908 ~ 11007, 研究經費: 1220千元
    数据类型: report
    显示于类别:[教育學系] 國科會研究計畫

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