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題名：利用網路化心智模式診斷系統診斷七年級學生之「擴散與滲透作用」心智模式
作者：董曜瑜
作者(外文)：Tung, Yao-Yu
校院名稱：國立彰化師範大學
系所名稱：科學教育研究所
指導教授：王國華
學位類別：博士
出版日期：2018
主題關鍵詞：心智模式診斷；資料探勘；擴散與滲透作用；data mining；diagnosis of mental models；diffusion and osmosis
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本研究主要目的在利用網路化心智模式診斷系統診斷國中7年級學生的擴散與滲透概念之心智模式。研究對象為台灣北部及中部七年級學生共1107位，透過問卷調查法以擴散與滲透作用二階層診斷測驗(DODT)的問卷資料收集，藉由資料探勘的關聯規則分析及網路化心智模式診斷系統(WMMD)的分析，以建立學生答題反應之關聯，從中探尋學生可能存在之心智模式類型。並於分析後，篩選30位學生以事件晤談法探究學生形成相關心智模式的可能因素。
在研究方法中，除了對於學生於DODT的迷思概念分析外，藉由DODT的各題得分情形進行學生的集群分析(Cluster Analysis)，將學生分為高中低分三群，透過R軟體輔以Apriori演算法將學生於DODT的作答反應進行各群及全體的關聯規則分析，藉以比較各群及全體的規則差異，並匯整成有效之關聯規則，以作為WMMD系統的分析基礎。而後，透過關聯規則的基礎作為WMMD的匯入使用，並以解釋融貫性理論(The theory of Explanatory Coherence)作為概念組合之融貫性篩選，而形成學生於於擴散與滲透作用之心智模式。而晤談法以DODT中的事件作為發展，以半結構式晤談法進行晤談，以釐清學生在作答反應的組合中的選答因素。
研究結果顯示，（1）DODT測驗的迷思概念診斷結果，有關「擴散的過程」具有4種迷思概念、「粒子的本質與運動」具有5種迷思概念、「滲透的過程」具有4種迷思概念、「生命力對擴散與滲透的影響」具有1種迷思概念、「濃度與滲性」具有1種迷思概念。（2）關聯規則分析中，可得到有效規則25個，而其中僅有2個規則是三群學生普遍共有，而有5個規則是其中二群所共有，其餘18個規則皆為其中一群的規則，顯示了不同群學生之作答情形具有獨特傾向與作答關聯，可用以預測學生可能概念組合情形。（3）由關聯規則的結果，藉WMMD系統的分析比較，並以解釋融貫性理論的評估，發現了存在於擴散與滲透作用之23種次心智模式，而其對應物質本因模式有11種、粒子本因模式有4種、外在變因模式有4種、混合變因模式有3種、類科學模式有1種。（4）另外，由晤談的結果，探討影響擴散與滲透作用心智模式形成之因素，發現存在學生本體論的影響（如物質的本質、直觀解釋）、先前學習的概念及科學理論、以及巨觀與微觀的轉換困難而產生不同類比物的表徵呈現，是影響學生於擴散與滲透作用心智模式形成之主要因素。
The purpose of this research was to diagnose seventh grade students’ mental model on diffusion and osmosis concepts through a web-based mental model diagnostic system. The research method was questionnaire survey, consisting of 1107 students in the junior high schools in northern and central Taiwan. The questionnaires were collected by Diffusion and Osmosis Diagnostic Test (DODT), through association rule analysis of data. The analysis of Web-based Mental Model Diagnostic System (WMMD) was to establish students’ response, and explore the types of mental models that students may have. After the analysis, 30 students were selected to explore the possible factors of students’ formation of mental models by Interview-About-Evants (IAE).
In the research, in addition to the analysis of students’ misconception in DODT, the students were divided into three groups by cluster analysis according to their response of each question in DODT. The R with Apriori algorithm analyzed the association rules of each group and the whole in the DODT response, so as to compare the rules of each group and the whole, and integrate them into effective association rules, which were used as the analysis basis of the WMMD system. Then, the association rules were input into WMMD system, and the theory of Explanatory Coherence (TEC) was cohesively to assess the concept combination and thus the students formed the mental models of diffusion and osmosis. The events in the interview were developed by DODT, and the semi-structured interview was to clarify the factors in the students’ response.
The results revealed that: (1) The students’ misconception was found in DODT: five misconception in ‘the Particulate & Random Nature of Matter’, one misconception in ‘Concentration & Tonicity’ and ‘the Influence of Life Forces on Diffusion & Osmosis’ respectively, and four misconception on ‘the Process of Diffusion’ and ‘the Process of Osmosis’ respectively. (2) In the association rule analysis, 25 effective rules can be obtained. And only 2 of them were common on the three groups, while 5 of them were common on the two groups, and remaining 18 rules were rules on one group. It showed that every group of students’ response had unique tendencies and association response, which can be used to predict the possible combination of students’ concepts. (3) By the results of the association rules, through the analysis and comparison of the WMMD system, and assessment of TEC, we found 23 sub-mental models about diffusion and osmosis. There were 11 types of matter nature model, 4 types of particle nature model, 4 types of external force model, 3 types of mixed model, and 1 type of science-like model. (4) In addition, the results of the interview, we found the factors to influence mental models about diffusion and osmosis were students’ ontology (such as the nature of matter, intuitive interpretation), the prior learning and scientific theory, and transformation difficulty between microscopic and macroscopic, producing the representation of analogies.
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