Proceedings of the Symposium on Chemoinformatics
31th Symposium on Chemical Information and Computer Sciences, Tokyo
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Oral Session
Forest Learning Method for Chemistry
*mikio kaihara
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Pages O4

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Abstract
Because chemistry has characteristics, for example, quite complexity and diverse, we have difficulty when learning it, especially at first. When the more, we would like to learn chemistry, the more, we would face with the difficulty for understand the total concept of chemistry. In other words, we know, "you can't see the forest for the trees." Therefore, we propose Forest Learning Method (FLM) in order to understand the total image of chemistry. This is the application of the Thinking Figures Method and the Mind Map, dedicated to mainly idea processor. Both methods have similarities, for example, radial thinking methods, jointing a word and the other word, using arrows or branches. Much more, both methods recommend using a word or short sentences as possible as we can. This is because both were primary proposed for idea processors. In case of FLM, we would accept sentences or chemical equation because we would be able to learn chemistry, more continuously. We should say that FLM is specialized type of the Thinking Figures Method or the Mind Map for learning. As a result of applying FLM to students, we found that they would be able to learn each section of chemistry, for example, electrical chemistry, chemical equilibration and so on, more hierarchically, and totally.
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© 2008 The Chemical Society of Japan
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