應用類神經網路與模糊推論規則於數字與注音符號之智慧型電腦輔助教學研究

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應用類神經網路與模糊推論規則於數字與注音符號之智慧型電腦輔助教學研究
著者: 阮志豪; Haw, Ruan Chi
孫光天; 尹玫君; 郭耀煌; ; 資訊教育研究所
主題: 電腦輔助教學; 人工智慧; 類神經網路; 模糊理論; Computer-assisted Instruction; Artificial Intelligence; Neural Network; Fuzzy Set Theory
描述: 本研究係以人工智慧技術：利用類神經網路(Neural Network，NN)與模糊推論理論(Fuzzy Inference Theory)為主，建構一套智慧型的多媒體手寫數字與注音符號標準字型之電腦輔助教學系統。由於標準字型之書寫，傳統教學是需由教師個別教導，很難在學校班級中完成，且標準程度之判定，常因教師個人主觀意識而不同。故本研究嘗試以人工智慧技術所建立之多媒體電腦輔助教學(Computer Assisted Instruction，CAI)系統，來輔助教師們對學生標準字型書寫之教學，並提供學生們－個自我輔助學習環境，作為書寫標準的依據。本系統之成效評估，採等組前測、後測的實驗設計，研究對以台南市進學國小一年級四班學生40人為研究樣本，並依男女生隨機分成實驗組和控制組兩組。實驗組有20人(男生10人，女生10人)，接受本電腦輔助教學系統學習；控制組有20人(男生9人，女生11人)，接受一般的教學程序。再由(一)類神經判定結果與(二)模糊推論之結果，分別做評估，探討本研究之效益。研究結論與結果如下：一、模糊推論之書寫標準程度 (1)實驗組經過電腦輔助教學後，書寫標準程度高於控制組。 (2)實驗組經過電腦輔助教學後，書寫標準程度高於前測階段。 (3)書寫標準程度之模糊推論結果與類神經判定結果呈高度正相關。二、類神經判定之書寫標準程度 (1)實驗組經過電腦輔助教學後，書寫標準程度高於控制組。 (2)實驗組經過電腦輔助教學後，書寫標準程度高於前測階段。由於實驗研究所得之結果，肯定了本系統之功能與價值，對於系統內部所運用之技術與人機界面之設計，對日後智慧型電腦輔助學習之研究，提供一新的研究技術及領域。
In this thesis, we apply the neural network techniques and fuzzy set theories to construct an intelligent computer-assisted instruction (CAI) system for teaching elementary students to learn and write the standard digits and Mandarin Phonetic Symbols. The major researches include: information techniques for handwritten characters recognition, artificial intelligence, and multi-media CAI system. The performance of this system was evaluated by the quasi-experimental of education research. The examinee samples for the research are forty first-grade students. Twenty students are used as the control group and the rest students (twenty students) are used as the experiment group. The experimental results are summarized as the followings: 1.The standard degree of written characters is evaluated by the fuzzy inference rules. (1) At the post-testing, the standard-degree of experiment group was higher than the control group. (2) At the post-testing, the standard-degree of experiment group was better than that in the pre-testing (3) The correlation of standard-degree between the output of fuzzy inference rules and the output of neural network are positive and high correlation. 2.The standard-degree of written characters is evaluated by the neural networks. (1) At the post-testing, the standard-degree of experiment group was better than the control group. (2) At the post-testing, the standard-degree of experiment group was better than that in pre-testing stage. Experimental results verify the high value of this research, and the experience of this research is useful to related works.
碩士
建立日期: 1998
格式: 121 bytes
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語言: 中文
識別號: http://nutnr.lib.nutn.edu.tw/handle/987654321/4714
資源來源: NUTN IR

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應用類神經網路與模糊推論規則於數字與注音符號之智慧型電腦輔助教學研究

阮志豪; Haw, Ruan Chi 孫光天;尹玫君;郭耀煌; ;; 資訊教育研究所 1998

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