Title

基模架構對學習系統思考方法之影響

Translated Titles

The Effects of Schemas on Learning the Methods of Systems Thinking

DOI

10.6846/TKU.2011.00164

Authors

曾奕樵

Key Words

系統動力學 ; 基模架構 ; 存量 ; 流量 ; 反饋 ; System Dynsmics ; Schemas ; Stocks ; Flows ; Feedback

PublicationName

淡江大學公共行政學系公共政策碩士在職專班學位論文

Volume or Term/Year and Month of Publication

2011年

Academic Degree Category

碩士

Advisor

韓 釗

Content Language

繁體中文

Chinese Abstract

本研究焦點著重於呈現學習者在接受十至十二小時的系統動力學相關課程後,如何應用系統動力學中的基本概念,如:流量、存量及反饋等進行問題分析。由於一般人為了詮釋外在世界,而以過去的生活經驗或知識累積為基礎,逐漸累積發展出各種認知結構,並形成存在於心智中的基模架構,故當其所學習的新觀念與舊基模架構不一致時,往往難以修正既存的認知結構,以致不僅難以理解這些新觀念,甚至會增加產生誤解的可能性。本研究旨在了解既有基模架構如何影響系統思考的學習,並提出以下五點研究發現: 第一,「直接因果關係」相信因果與相近的時間、空間相關,並以一種靜態因果關係分析存量與流量間的關係,以致所推論的存量與流量間缺乏累積關係。第二,「簡化原則」避免了細瑣澈底的分類方式,因此所推論的因素經常是模糊不清且無法量化的。第三,「直接因果關係」及「簡化原則」分別推論出預設立場及特定時段存量之系統界限,而忽略了應存在於系統中的因素。第四,「單向因果架構」是一種簡化的線性因果模式,認為一個原因通常都只會影響一個結果,而「直接因果關係」則聚焦於鄰近因素間的因果關係,導致缺乏覺察應存在於系統中反饋迴路的能力。最後,上面所提到以靜態因果關係分析存量與流量間關係的「直接因果關係」,以及推論出預設立場系統界限之「簡化原則」,使得學習者產生誤認關鍵存量的情形。 基於上述研究發現,本研究建議,未來在進行與本研究議題相關的研究時,研究標的可採用與本研究不同類型問題的報告,以釐清學習者運用系統動力學基本概念之情形與問題類型間的相關性。此外,可觀察學習者在接受與系統思考相關課程的過程,並對學習者進行訪談,以便於取得更貼近學習者本身學習歷程的資料。最後,建議讓學習者在接受課程前先就他們自行選擇的問題進行分析,而在課程結束後針對同一問題再次進行分析,因此可比較學習者在接受課程之前與之後在分析問題情形上的差異性。

English Abstract

This research focused on presenting the difference between the basic concepts of System Dynamics such as stocks, flows and feedback, and the situation that learners analyzed their problems after they took ten to twelve hours System Dynamics course. Generally, in order to interpret the outside world because, we usually developed a variety of cognition structures that were in turn transformed into schemas based on our life experiences or accumulated knowledge. As a result, when we are learning new concepts inconsistent with our existent schemas, it is often very hard to have our cognition structures modified. Moreover, it is very likely that we tend to misunderstand these new concepts when we apply them. The purpose of this research is to find out how our existent schemas affect our learning of systems thinking. The major findings of this research are stated as follows: First,“direct causal relationship”tends to perceive that cause and effect are closely related in time and space, and that the relations between stocks and flows are static. As a result, the stocks and flows inferred by the learners often lack accumulation relaitonships. Second,“simplistic rule”tends to avoid detail and thorough classification of information that usually leads to ambiguity and unquantifiablity of factors. Third, “direct causal relationship”and“simplistic rule”that presumes system boundary of a specific period of stocks often excluded a number of factors that ought to exist in the system. Fourth,“one-way causal framework”is a kind of simplistic linear causal pattern which considers that a cause only affects one outcome; “direct causal relationship”focuses on the causal relationships between close factors. Both of them tend to prevent the ability of detecting feedback loops in the system. Finally, “direct causal relationship” that analyzes the relationship between stocks and flows from a static causal perspective and “simplistic rule” that presumes specific system boundaries tend to make the learners mistake the stocks that are in fact crucial. Based on the research findings stated above, the following suggestions for future research are proposed. First, future research may consider to analyze learners’ reports focusing on different type of problems so as to identify the relationships between the situations that learners apply the basic concepts of System Dynamics and the types of the problems. Second, future researchers may consider to observe the learners in the process of learning systems thinking and make interviews so as to collect first hand data for conducting analyses. Finally, it is suggested that a pretesting and posttesting research design that compares the situations of the learners in analyzing problems before and after they take the systems thinking course may be considered so as to learn the real effects of the course.

Topic Category 管理學院 > 公共行政學系公共政策碩士在職專班
社會科學 > 政治學
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