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題名:徑路搜尋法應用於高一學生力學知識結構與其學習成就之相關研究
作者:黃湃翔
作者(外文):Pai-Hsiang Huang
校院名稱:國立高雄師範大學
系所名稱:科學教育研究所
指導教授:江新合
洪振方
學位類別:博士
出版日期:2004
主題關鍵詞:知識結構學習成就徑路搜尋法教學評量圖形表徵knowledge structurelearning achievementsPathfinder Methodteaching assessmentgraph representation
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本研究旨在應用徑路搜尋法分析高一學生力學知識結構,探究知識結構指數對學習成就之預估效力和區辨效力,以評估徑路搜尋法應用於教學評量的可行性;並深入分析高中學生知識結構圖形表徵之組型差異,及解決問題時知識結構節點活化的情形,以提供教學診斷和教學設計之參考。本研究以高雄地區四個公立高中一年級學生共計148人為研究對象,主要研究工具係以自編之「力學知識結構測驗」、「基礎物理力學成就測驗」、「放聲思考力學解題分析」、「力學概念理解問卷」等進行資料蒐集。本研究主要研究發現與結論為:
一、知識結構量化指數能有效預估和區辨不同學習成就學生,其中以PFC指數對於力學學習成就預估效力最高,其所解釋的變異量部分達40.4%(R=.635,R2=.404);對高成就組而言,PFC指數的預估效力最佳,迴歸分析相關係數達.751,顯示PFC指數的高低最能代表其力學學習成就。
二、不同學習成就學生其知識結構圖形表徵之組型特徵確實存在差異性,高成就群學生其知識結構以上位概念為中心,結構型式具組階層性,並且呈現依據定義聯結相關概念的樹狀結構,這些知識結構組型差異的特徵,影響其物理解題時概念提取方式與概念節點的活化路徑,進而影響其解題表現。
三、針對知識結構圖形表徵及聯結鍊權值分析所找出的錯誤或缺陷的概念聯結,確實能反映學生對相關概念存在不正確理解。
The purpose of this study is to apply Pathfinder Method to analyze mechanics knowledge structure for tenth-grade students. This study investigates both the predictive efficacy and discriminative efficacy of learning achievements by knowledge structure indices, with which it aims to evaluate the feasibility of applying Pathfinder Method in teaching assessment. In the meantime, this study also analyzes both the patterns difference of knowledge structure graph representation and the node activation in problem solving, with which it aims to provide the consultation for teaching diagnosis and teaching design.
The subjects included 148 tenth-grade students from Kaohsiung district. The tools this study employed included the mechanics knowledge structure assessment, the foundation mechanics achievement test, the problem solving analysis with thinking aloud, and the questionnaire of understanding mechanics concept. The main findings and conclusions are made as follows:
1. The knowledge structure indices can effectively predict learning achievements and effectively discriminate subjects with different learning achievements. Among the three indices the most predictive of students’ learning achievements is the PFC index, which accounts for approximately 40.4% of the variance in students’ learning achievements (R=.635,R2=.404). Furthermore, PFC index has the best predictive efficacy for high-achiever group (R=751); consequently, it shows that PFC index is the most representative of their mechanics learning achievement.
2. The variations in the patterns of knowledge structure graph representation for different learning achievement students indeed existed. The knowledge structures of high-achiever group are organized with superordinate concept in the center, more hierarchical, and displayed with tree structures that connect related concepts by concept definition. These variations influence students’ concept extracted and node activation path, and thus influence their performance in physics problems solving.
3. There are some mistaken or defective concept connections derived from the analysis of the knowledge structure graph representation and the connection-chain weight, and such connections are able to reflect the incorrect understanding of related concepts by students.。
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