Feature reduction for neural network in determining the Bloom’s cognitive level of question items
The concept of Bloom’s taxonomy has broadly implemented as a guideline in designing a reasonable examination question paper that consist of question items belonging to various cognitive levels which are tolerate to the different capability of students. Currently, academician will identify the Bloom’...
| 第一著者: | |
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| フォーマット: | 学位論文 |
| 言語: | 英語 |
| 出版事項: |
2009
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| 主題: | |
| オンライン･アクセス: | http://eprints.utm.my/11449/6/ChaiJingHuiMFSKSM2009.pdf |
| 要約: | The concept of Bloom’s taxonomy has broadly implemented as a guideline in designing a reasonable examination question paper that consist of question items belonging to various cognitive levels which are tolerate to the different capability of students. Currently, academician will identify the Bloom’s cognitive level of question items manually. However, most of them are not knowledgeable in identify the cognitive level and this situation will result to miss categorized of question items. To overcome this problem, this study has proposed a question classification model using artificial neural network trained by the scaled conjugate gradient backpropagation learning algorithm as question classifier to classify cognitive level of question items. |
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