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篇名 以E-Closeness評估多維度概念圖之學習成效
卷期 8:1
並列篇名 Evaluating the learning effects of multidimensional concept map by using E-Closeness method
作者 高巧汶蕭立人
頁次 051-060
關鍵字 概念圖學習評量系統數位學習相近指數評分法增強型相近指數評分法Concept MapLearning and Assessment systemClosenessEnhanced-ClosenessE-Learning
出刊日期 201908

中文摘要

概念圖 (concept map) 是一種教學策略工具,可清晰的呈現出學習者的認知概念架構,藉由學習者繪製的概念圖,教學者可從中觀察學習者對於命題(目標概念)的理解完整度及創造力。教學者在教學的過程中,可藉由呈現概念間的連結關係,幫助學習者結構化習得的知識;學習者方面也可藉由概念圖的輔助學習,增加統整歸納重點知識的能力,輔以圖像式的記憶法,延長知識保留時間。因此,透過概念圖式學習評量系統的建置,以簡易的人機介面與自動化的評分計算,可以提供教學者更便利的教學環境。傳統上概念圖學習的評分法,包括Closeness 指數評分法和與N-G 指數評量法兩種,針對兩種原有概念圖評分法進行觀察、比較與分析後,本文提出E-Closeness 評分法(Enhanced Closeness evaluation method),除採用Closeness 指數評分法所得的相似指數,更額外增加評估連結語的符合程度,以解決傳統評分法所未考慮從屬關係的問題,藉由採用更完整的資訊,E-Closeness 評分法可更準確的表徵出學習成效。

英文摘要

Concept map as an effective learning assessment tool, which can clearly present the framework of the learner’s cognitive. According to the concept map, the educators can observe the degree of completeness and creativeness of the learner's understanding of knowledge cognition. In the process of teaching, the educators can help the learners to construct the acquired knowledge by presenting the relationship between the concepts. The learners can also increase the ability of organizing and summarizing the knowledge by using the concept map. And the retention time of knowledge can be extended by using image memory. Through the concept map learning assessment system, a simple human-computer interface and automated scoring calculations can improve the problems faced by the educators and students. Traditionally, the scoring method of Concept Map Learning includes Closeness Index scoring method and N-G Index evaluation method. Both scoring methods have their advantages and disadvantages and applicability. After observing, comparing and analyzing the two existing concept map evaluating methods, this article proposes an improved scoring method, named E-Closeness(Enhanced-Closeness). It inherits the advantages of the Closeness Index scoring method and judges the degree of conformity of the link language. E-Closeness tries to solve the problem of abnormal phenomena that may be caused by the traditional evaluating method. Finally, the inference of characteristics was proposed, it can be understood that the E-Closeness scoring method can more accurately represent learning effectiveness.

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