控制解題環境以誘導學習者認知基模的抽象、儲存與使用--線上實驗設計

Control of problem giving and hint giving in a problem-solving environment for effective development of schemata

陳翔傑(Hsiang-Chieh Chen)

指導教授 ： 夏延德

中原大學/工學院/資訊工程研究所/碩士(2003年)

https://doi.org/10.6840/cycu200300152

摘要

摘要

人類的認知發展或智力發展，不外乎是靠著不斷的學習或經驗的累積而成。然而學習與經驗的累積大部分來自於問題解決。人類常常運用「類比推理」的能力來解決問題，把我們已知的事物或知識比擬到新事物或新問題上，達到解決問題的目的。另外，按照皮亞傑的說法，當每個人每每遇到某事物或問題時，便用某種對應的認知結構予以核對、處理時，則此種認知結構稱之為「基模」〈schema〉。因此，基模的發展與類比推理的能力不但可以用來組織經驗與知識，也進一步的促使我們有能力面對問題並解決問題。

然而，隨著時空環境的轉換，人類身處的環境愈來愈複雜，所面臨的挑戰也愈來愈多，我們解決問題的能力也就愈顯得重要。但是，隨著環境複雜度的增加，考慮的因素變多了、接受到的訊息也變多了，這種種都會影響到我們基模的發展與解決問題的能力

因此，為了減低其他不必要的雜訊對我們的影響，我們將設計一個人為的解題環境，排除一些不必要的干擾，並安排一些刺激學習者主動學習的誘因，希望透過精心的設計下，讓學習者能夠有個訓練或加強自己基模發展與解題能力的理想空間。本系統主要的實驗教材設定在小學數學的應用問題，希望藉由應用問題特有的問題基模及情境的轉換，再加上系統規劃的學習自動機、出題機制以及適時的提供提示來達到本系統的主要目的：〈a〉幫助學習者學習解應用問題的能力，〈b〉利用應用問題情境的變化來達到訓練或加強學習者的基模發展。

關鍵詞：基模、類比推理、應用問題、學習自動機、提示

關鍵字

提示 ； 學習自動機 ； 應用問題 ； 類比推理 ； 基模

並列摘要

Abstract

The development of our intellectual ability is, for the most part, built upon our ability to continuously learn from our past experience. In particular, we learn most from our experience of having (successfully) solved various problems. Humans often use reasoning by analogy to solve problems. Reasoning by analogy may be viewed as a two-step process. First, we map a new problem or a new situation into something that we already know. Then, we map or transfer our existing knowledge about that something to the new problem or situation and try to apply the transformed knowledge, hoping that it will be useful in dealing with the new problem or situation. According to Piaget, we search for a useful cognitive structure (called a schema) in our long-term memory whenever we encounter a problem or situation. If we find such a schema, we then use it in handling the problem or situation in question. Viewed from this perspective, the development of our ability in abstracting and using schemas constitutes a very important part of our problem-solving ability.

As time changes, the environment that we are in is becoming more and more complex. We are also facing different kinds of challenges. To overcome these challenges, we need to have a good problem solving ability. And yet, as the complexity of the environment grows, the difficulty of abstracting useful schemas also increases. This in turn can have a negative impact on our problem solving ability.

Since our ability of abstracting and using schemas can be very important, it is desirable that we develop an automated learning environment to train such capabilities. This learning environment should mimic the actual environment in which we continuously encounter and solve problems. However, the “small world” environment should also be such that it does not have a complexity that is as great as the complexity of the real environment. The latter aspect is very important, because we want to scaffold the learner’s ability in abstracting and using schemas.

We choose to focus on a subset of elementary word problems. The artificial problem-solving environment is such that it carefully controls the kind of problem structures that the learner will encounter. The problem-solving environment also uses an underlying scaffolding automaton to suggest in various ways to the learner that problems that are contextually different can actually be structurally the same. It is hoped that this CAL (computer-assisted learning) system can help the learner improve his/her ability in abstracting and using schemas. This in turn can help to improve the learner’s problem solving ability.

並列關鍵字

hint ； scaffolding automaton ； word problem ； analogical reasoning ； schema

參考文獻

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