控制解題環境以激發和量測學生對於簡單基模的建立與使用

Control of Problem Solving Environment for Stimulating and Measuring the Construction and Use of Simple Schemas

林佳穎(Chia-Ying Lin)

指導教授 ： 夏延德

中原大學/工學院/資訊工程研究所/碩士(2002年)

https://doi.org/10.6840/cycu200200399

摘要

環境無時無刻不在變，人必須不斷的學習以順應環境的變遷。人必須隨時從週遭的環境中學習。然而，學習有效與否則取決於學習的過程是否為主動、是否對其週圍環境變化的觀察敏銳。換句話說，環境提供了各種不同的資訊可供學習，人藉由學習了解更多的事情；而同時，許多干擾學習的「雜訊」亦出現，將妨礙學習的成果，致使原本應當注意的事情，因此忽略不見。有時，即使注意到了，卻未記入腦中；或在需要回想起某些訊息時，腦中卻是空白！即便記得過去從週遭的環境中學得的片段訊習，不見得有助於解決眼前遇到的狀況。這些存在於自然解題環境中的不確定因素及環境的複雜度為人類解題帶來了許多障礙。
然而，從環境中學習是很重要的能力，意即身為一個解題者，我們可以組織及累積解題過程中所獲得的知識，並將之有效的運用於日常生活的解題活動中。
基於此，我們嘗試提供一人為的解題環境(artificial environment for problem solving)，此環境為自然解題環境(natural environment for problem solving)的縮影，它過濾了自然環境中除了問題以外的雜訊。在這個環境裡，提供了在自然解題環境中所可能會出現的學習刺激，並設計了一連串的策略來控制這些學習刺激的出現時機，讓學生不但可主動在此環境中學習新知識，並在學習過程中自己發現某些解題所需的基模(schema)，更能在一連串的訓練過程中，將腦中所存的簡單基模整合、消化，真正融會貫通成為屬於自己的東西，而能適時的在遇到類似或相關問題時將已存的基模拿出來運用，幫助解決問題。

關鍵字

人為的解題環境 ； 基模 ； 類比解題 ； 類比學習 ； 認知

並列摘要

We live in an environment that is constantly changing. To successfully adapt to this environment, we must learn continuously. In order for any learning activity to be truly effective, however, it has to be an active process. That is, the learner must take charge, and constantly pay attention to his/her surrounding environment and learn from it. A surrounding environment offers many aspects that can be and should be learned. However, there may be a lot of “noises” in the environment. The presence of these noises often makes it difficult for the learner to notice what he/she ought to notice. Even if the learner does notice some thing that may be useful, he/she may still decide not to “record” it in his/her memory. And even if the learner did record something that he/she finds useful to remember, he/she may nevertheless fail to retrieve it from memory when in fact it is what is needed in order for a problem to be solved. And even if the learner did retrieve the piece of knowledge that is potentially useful from memory, he/she may still fail to solve the problem successfully, because the reasoning process that he/she uses may be incomplete. Altogether, these uncertainties make “learning from environment” an uneasy task.
Nonetheless, “learning from environment” is an important ability that we should have. It is desirable that we, as problem solvers, are able to organize and accumulate our problem solving knowledge and effectively apply that self-acquired knowledge in our daily problem solving activities. The more effective we do this, the better problem solvers we are more likely to be.
In this thesis, we try to provide a potential learner with a problem-solving environment that is a “miniature but simplified” version of the real world. In this environment, there are learning stimuli that may occur in the real world. As a miniature version of the real world, there are noises too. However, there are much less noises when compared to their real-world counterpart. Various strategies are used to control the problem-solving environment, so as to scaffold the learner’s schema acquisition (and use) capabilities. The learner still takes an active role in doing problem solving. However, the problem-solving environment works in such a way that it will be easier for the learner to notice and decide that some things ought to be assimilated (as schemas in memory) and some things ought to be accommodated (into existing schemas in memory). As part of the design rationale, the learner should also find it natural to retrieve some previously acquired schema and use it in problem solving.

並列關鍵字

learning by analogy ； schema ； cognitive ； problem solving by analogy ； artificial environment for problem solving

參考文獻

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