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題名:教育測驗評量應用於產品設計教育策略及灰結構模型分析
作者:梁榮進 引用關係
作者(外文):Jung-Chin Liang
校院名稱:國立臺中教育大學
系所名稱:教育測驗統計研究所
指導教授:許天維
永井正武
學位類別:博士
出版日期:2012
主題關鍵詞:教育測驗評量灰結構模型產品設計教育策略層級分析法灰關聯分析方法GSP 表可視化Educational statistics and measurementGrey Structural ModelingIndustrial product design strategyAnalytical Hierarchy ProcessGrey Relational AnalysisGSP chartVisualization
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本研究應用教育測驗評量統計方法,進行工業產品設計策略的鑑別研究;透過專家經驗的認知,進行產品設計要素的重要性評量,並以量化方式鑑別出其重要性排序。以數値處理方式所得到的結果,經由灰色理論(Grey System Theory)與灰結構模型的分析,提供了產品設計教育策略方法,同時也提供了學習者進行產品最佳化設計的遵循原則。研究執行過程,本研究提出三項不同領域的研究案例,透過本研究所提案的數理方法,首先採用5WIH方法的量化篩選方式,評選出設計要素項目,接著以層級分析法(Analytical Hierarchy Process, AHP)進行研究評量,評量數據通過一致性指標(Consistency Index, C.I.)的檢定之後,確定評量數據的可信性(一致性) ,獲得了一致性矩陣(Clean data);接著採用灰關聯分析方法(Grey Relational Analysis, GRA)計算出排序結果,這項新提案方法本研究稱為:局部性灰色關聯度層級分析法(LGRA-AHP)。研究結果透過灰色系統學生問題表(Grey Student-Problem chart-GSP表)與灰色系統結構模型(Grey Structure Model, GSM)的可視化解析功能,實證這項模式應用在新產品設計的可行性。整體研究上,本研究的進步性貢獻有以下三個重點:
一、局部性灰關聯度層級分析法(LGRA-AHP)新方法的提案:
採用局部性灰關聯度(LGRA)與層級分析法(AHP)的結合,處理產品設計教育問題的評量與計算,評量數據透過C.I.值的可信性檢定,得到了專家經驗認知的評量數據;這項評量數據具客觀且專業,提供了教育策略評量數據,促使本研究得到最佳化設計策略結果,同時也達到了科學研究成果。彙整專家經驗的評量資料,本研究採用灰關聯度進行排序的計算,所得到的Gamma值全部是落在區間[0, 1]之間。這種研究處理方式也適用於多量化數據的運算以及處理不確定性問題的解析,革新了AHP方法的使用性,成為教育測驗評量研究可行的新方法。
二、透過GSP表和GSM結構圖的可視化提案:
研究評量之結果以S-P表理論為基礎,結合局部性灰關聯度的計算,所得到的GSP表與灰結構模型(GSM結構圖),根據客觀數據的實際差異,可以正確界定評量結果的排序結構,促使產品設計教育策略,得到有系統且最佳化策略的呈現;採用灰關聯度的數值,實際鑑別每一位學生「S」的學習能力,和每一項測驗問題「P」的難易度差異,這種以S-P表為基礎,以實際數據的差異進行圖解表達,優於傳統的S-P表只能以0和1進行圖解傳達,而能夠更正確的解析各項問題之間的結構性,同時也可以應用於其它領域的研究鑑別。
三、以量化處理設計策略方法的新提案:
整體研究以量化數據的處理方式進行,研究過程考慮了順序性(Sequence)、連續性(Continuity)、銜接性(Articulation) 和統整性(Integration)等等層面,將評量數據及排序結構建立成垂直性組織(Vertical Organization),促使不易理解、難以釐清或不易判別的產品設計教育問題,以有系統的結構組織呈現出來,不僅解決了產品設計教育策略的不明確問題,同時也創造了新的研究方法。
The paper applies educational statistics and measurement methods to do the industrial product design strategy identification research. Through experts’ cognition, the importance of product design elements can be achieved; moreover, the order of elements’ importance is shown in a quantitative way. The results obtained by the numerical approach are analyzed by the Grey Structural Modeling (GSM), which provides product design education strategy. Also, it provides the principles of optimal product design to learners. In this study, through three different research topics and the proposed research methods are as follows: first, the method of 5W1H is used to screen the data and formulate the design elements. Followed by Analytical Hierarchy Process (AHP) to make sure the data are clean and reliable through calculating the Consistency Index ( ) value. Then the order of data can be achieved by using Grey Relational Analysis (GRA) method. This innovative method is called LGRA-AHP in this paper. Finally, through the visualization function of grey student-problem chart (GSP) and GSM, the proposed method is proved to have feasibility and effectiveness in new product design. As a whole, there are three progressive contribution features of this paper.
1. The new proposal of LGRA-AHP
Through the combination of LGRA and AHP to deal with the evaluation and calculation of design education problems, the data have to pass value test to reach experts’ cognitive assessment data. The data are not only objective and professional, but also provide educational strategy evaluation data, which result in optimized design strategy in this paper. Meanwhile, it obtained scientific research effect. After integrating experts’ evaluation data, the paper uses GRA calculation to reach the order of data, and the gamma value of them are between 0 and 1. This calculation method can also be applied to large data calculation, complex questions, which become a feasible and effective method in educational measurement and statistics.
2. The visualization proposal of GSP and GSM
The assessment results are based on the S-P theory combined with LGRA calculation, and the obtained GSP chart and Grey Structural Modeling (GSM) can sort and position the assessment results accurately. It also presents the product design education strategy in a systematic and optimal way. In addition, the use of GRA makes each student’s learning ability (S) and each test item’s difficult difference (P) being identified clearly. This numerical presentation is superior to traditional S-P chart, and it is also suitable to be developed in other research fields.
3. A new proposal of dealing with design method in a quantitative way
For the overall research framework, the paper considers sequence, continuity, articulation and integration to make the data and order structural into a vertical organization. As a result, it is possible to do the systematic identification of difficult or unclear product design educational questions. This paper presents the results in a systematic structural organization which solves the vague problem in product design educational strategy.
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