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研究生:陳婉誼
研究生(外文):Chen, Wan-Yi
論文名稱:應用功能性近紅外光光譜術於歷史科教學法評估:互動式響應系統輔助教學法與傳統講述教學法之比較
論文名稱(外文):Applying functional near-infrared spectroscopy in history class for the course instruction evaluation: comparison between interactive response system- assisted instruction and traditional didactic instruction
指導教授:孫家偉孫家偉引用關係
指導教授(外文):Sun, Chia-Wei
口試委員:程海東郭浩中林慶波張立鴻呂隆昇
口試委員(外文):Chen, Hai-DungKuo, Hao-ChungLin, Ching-PoChang, Li-HungLu, Long-Sheng
口試日期:2021-10-04
學位類別:碩士
校院名稱:國立陽明交通大學
系所名稱:光電工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2021
畢業學年度:110
語文別:中文
論文頁數:110
中文關鍵詞:功能性近紅外光光譜術傳統講述教學法互動式響應系統(即時反饋系統)多元評量認知負荷理論機器學習
外文關鍵詞:functional near-infrared spectroscopytraditional didactic instructioninteractive response systemmultiple assessmentcognitive load theorymachine learning
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近年來隨著科技的日新月異,透過行動載具進行互動式教學的即時反饋機制可改善傳統授課中以講述為主的困境;目前多數研究中比較教學方式的優異時都是透過測驗成績、量表或問卷以及行為觀察等方式來進行評估,但隨著多元評量的興起以及考量到前述方法中衍生的社會期許偏誤和個人主觀評斷可能會降低研究的信度,為了避免前列問題,我們期望能夠應用功能性近紅外光光譜術來評估不同教學法於歷史課堂中的影響差異,以從生理角度來進行觀測並提供客觀且量化的評估依據。
鑒於前述,本研究基於非侵入式功能性近紅外光光譜術來同步量測課堂中學生的前額葉血氧濃度變化,總計共採集10筆傳統講述教學法與12筆互動式響應系統輔助教學法的血氧數據進行分析。首先,在個案探討方面將課堂事件記錄與血氧濃度變化趨勢進行對照後,從中發現到了與各項理論背景相應的生理實證;接著,在T檢定的統計結果中也確實能夠找到兩種教學法間具有顯著性差異的腦血氧資訊,並與認知負荷理論概念具有關聯性;最後,我們將經過處理的血氧特徵匯入不同的機器學習演算法來辨識教學法組別,而根據結果顯示,被選中的最佳特徵與認知負荷的影響有關,且從支援向量機、線性區別分析與二次區別分析三種分類器所得到的測試準確率分別可達85.7 %、71.4 %以及85.7 %的水準。
綜合前述結果證明藉由功能性近紅外光光譜術來評估教學法的可行性,並能夠進一步為相關理論提供神經科學上的實證。
With the rapid development of science and technology for the past few years, instant feedback of interactive instruction by mobile devices can improve the problems of traditional didactic instruction. Most studies compare the pros and cons of teaching methods by exam scores, scales or questionnaires, and behavioral observations. However, with the rise of multiple assessments, social desirability bias and subjective judgment of those approaches may reduce the reliability of results. To avoid these problems mentioned above, we expected to apply functional near-infrared spectroscopy (fNIRS) to evaluate teaching methods from the physiological point of view and provide an objective and quantitative basis of evaluation.
In this research, based on non-invasive fNIRS, we synchronously measured the changes in cerebral oxygen concentration in the prefrontal cortex during class. Furthermore, we acquired 10 data with traditional didactic instruction and 12 data with interactive response system-assisted instruction in total. First, in the case studies, we checked the real-time recordings during the lecture against the trend of changes in hemoglobin concentration. Through the results, we find empirically physiological evidence corresponding to several theoretical backgrounds. And then, T-test results also can indeed find significant differences between two instructions from cerebral oxygen information and be related to cognitive load theory. Finally, we fed the processed cerebral oxygen features into different machine learning algorithms to distinguish two instructions. Through the results, the best-selected features are relative to the effect of cognitive load, and the testing accuracy obtained by support vector machine (SVM), linear discriminant analysis (LDA), and quadratic discriminant analysis (QDA) classifiers can reach 85.7 percent, 71.4 percent, and 85.7 percent, respectively.
As mentioned above, the results prove the feasibility of instruction evaluation through fNIRS and can provide neuroscience evidence for the relevant theory.
中文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
誌謝. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
圖目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
表目錄. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
第一章 緒論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 研究背景與動機. . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 研究目的與重要性. . . . . . . . . . . . . . . . . . . . . . . . 4
第二章 文獻探討. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1 教育神經科學. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1.1. 教育學. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1.2. 心理學. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.3. 神經科學. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2 傳統講述教學法. . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2.1. 傳統講述教學法的定義. . . . . . . . . . . . . . . . . . 11
2.2.2. 傳統講述教學法的流程. . . . . . . . . . . . . . . . . . 12
2.2.3. 傳統講述教學法的優勢與限制. . . . . . . . . . . . 14
2.3 互動式響應系統輔助教學法. . . . . . . . . . . . . . . . 15
2.3.1. 互動式響應系統的簡介. . . . . . . . . . . . . . . . . . 15
2.3.2. 互動式響應系統—Nearpod. . . . . . . . . . . . . . . 15
2.3.3. 互動式響應系統輔助教學法相關文獻. . . . . . 17
2.4 研究相關理論依據. . . . . . . . . . . . . . . . . . . . . . . . . 19
2.4.1. 學習者中心教育. . . . . . . . . . . . . . . . . . . . . . . . . 19
2.4.1.1 學習者中心簡介. . . . . . . . . . . . . . . . . . . . . . . . 19
2.4.1.2 學習者中心的理論基礎. . . . . . . . . . . . . . . . . 20
2.4.1.3 學習者中心教育於本研究的應用. . . . . . . . . 21
2.4.2. 社會文化理論. . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.4.2.1 理論中心—近側發展區的概念. . . . . . . . . . . 22
2.4.2.2 鷹架理論的起源. . . . . . . . . . . . . . . . . . . . . . . . 23
2.4.2.3 社會文化理論於本研究的應用. . . . . . . . . . . 23
2.4.3. 認知負荷理論. . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.4.3.1 記憶的類型. . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.4.3.2 認知負荷的類型. . . . . . . . . . . . . . . . . . . . . . . . 25
2.4.3.3 認知結構的觀點. . . . . . . . . . . . . . . . . . . . . . . . 26
2.4.3.4 認知負荷效應. . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.4.3.5 認知負荷理論於本研究的應用. . . . . . . . . . . 32
2.4.4. 問題教學法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.4.5. 暫停策略. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.5 近紅外光光譜術. . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.5.1. 組織內的擴散光學. . . . . . . . . . . . . . . . . . . . . . 36
2.5.2. 修正的比爾-朗伯定律. . . . . . . . . . . . . . . . . . . 37
2.5.3. 近紅外光光譜訊號組成. . . . . . . . . . . . . . . . . . 39
2.5.4. 近紅外光光譜術相關應用文獻. . . . . . . . . . . . 41
第三章 研究方法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.1 研究工具—近紅外光腦血氧儀. . . . . . . . . . . . . . 43
3.1.1 目標區域. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.1.2 硬體介紹. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.2 研究流程設計. . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3.1 招募對象. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3.2 收案流程. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
第四章 分析方法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.1 數據預處理. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.1.1 運動偽影校正. . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.1.2 雜訊濾波. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
4.1.3 歸一化. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
4.1.4 特徵萃取. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
4.2 統計分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
4.2.1 前提條件評估. . . . . . . . . . . . . . . . . . . . . . . . . . . 55
4.2.2 後設分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.3 機器學習. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.3.1 背景概述. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.3.2 特徵選擇. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
4.3.3 分類器. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4.3.3.1 支援向量機. . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4.3.3.2 線性區別分析. . . . . . . . . . . . . . . . . . . . . . . . . 69
4.3.3.3 二次區別分析. . . . . . . . . . . . . . . . . . . . . . . . . 72
4.3.4 留一交叉驗證. . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.3.5 混淆矩陣. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
4.3.6 評估指標. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
第五章 研究結果與討論. . . . . . . . . . . . . . . . . . . . . . . 77
5.1 個案探討. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
5.1.1 傳統講述教學法個案分析. . . . . . . . . . . . . . . . . 78
5.1.2 互動式響應系統輔助教學法個案分析. . . . . . 81
5.1.3 個案訪談整理. . . . . . . . . . . . . . . . . . . . . . . . . . . 84
5.1.4 綜合結果討論. . . . . . . . . . . . . . . . . . . . . . . . . . . 87
5.2 統計分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
5.2.1 前提條件評估結果. . . . . . . . . . . . . . . . . . . . . . . 88
5.2.2 獨立樣本T檢定. . . . . . . . . . . . . . . . . . . . . . . . . 89
5.2.3 後設分析結果. . . . . . . . . . . . . . . . . . . . . . . . . . . 91
5.3 機器學習. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
5.3.1 特徵選擇與分配結果. . . . . . . . . . . . . . . . . . . . . 93
5.3.2 支援向量機分類結果. . . . . . . . . . . . . . . . . . . . . 94
5.3.3 線性區別分析分類結果. . . . . . . . . . . . . . . . . . . 96
5.3.4 二次區別分析分類結果. . . . . . . . . . . . . . . . . . . 98
5.3.5 綜合結果討論. . . . . . . . . . . . . . . . . . . . . . . . . . . 99
第六章 總結、限制與未來展望. . . . . . . . . . . . . . . . . 101
6.1 總結. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
6.2 限制與未來展望. . . . . . . . . . . . . . . . . . . . . . . . . . . 102
參考文獻. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
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