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研究生:張雅芳
研究生(外文):Ya-Fang Chang
論文名稱:用意念重現來探究學習表現
論文名稱(外文):Investigating Learning Performance by Brainwave Monitoring
指導教授:邱昭彰邱昭彰引用關係
指導教授(外文):Chao-Chang Chiu
口試委員:謝瑞建邱怡欣
口試委員(外文):Jui-Chien HsiehYi-Hsing Chiu
口試日期:2014-07-15
學位類別:碩士
校院名稱:元智大學
系所名稱:資訊管理學系
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:中文
論文頁數:33
中文關鍵詞:腦波監控注意力放鬆度動機學習成就
外文關鍵詞:EEG monitoringmotivationattentionmeditationmotivationperformance
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臺灣在民國103年起實施十二年國民基本教育,因此,確保每一位國民中小學學生的基本學力,不會因為廢止升學考試而下降則是一個重要的核心課題。一般補救教學的課程設計以「評量-教學-再評量」的過程,評量系統旨在提升學生學力篩選品質,根據評量系統的資料分析去擬定課程目標並選擇適合受試者能力的教材。
現行的評量系統闕漏學生學習動機的核心問題,造成測驗分數被低估而影響篩選品質,因此,運用EEG直接量測學生在有無動機增強的受測情形下之腦波變化和測驗結果。以準實驗研究進行,隨機選取國小五年級學生兩班,立意取樣自然學科全班成績前百分之30學生為高分組,全班成績後百分之30學生為低分組,一班為實驗組,另一班為控制組,A班實驗組15人,在激勵策略介入前後的腦波變化以及測驗結果進行分析,並且和B班控制組15人,在沒有激勵策略介入之前後的腦波變化以及測驗結果作比較。
本研究結果顯示,有激勵策略介入的實驗組低分組學生成績高於控制組低分組學生且達到顯著性,腦波結果顯示動機被增強的學生在注意力平均值的上升,放鬆度短期大幅度的變化反應出受試者對於測驗的投入,顯示腦波可以偵測受試者的努力程度。低成就學生的動機被增強後所得的評量結果可以被解釋為學生的真實表現。
對於教學現場的建議,師長要協助孩子訂立合適的學習目標,正向去看成績的進步代替分數的高低,並鼓勵孩子在學習上的努力,讓低成就的學生有成功的經驗,對於學習抱持正面愉快的情緒,教導學生自我激勵,重視內在動機的價值取代外在動機的增強。
未來研究的方向朝向建立各學科注意力與放鬆度的模式,以此作為評鑑的標準,從神經生理的角度真正落實認知、情意、技能的評量向度。
Since 2014, 12-year compulsory education has been implemented in Taiwan. Students can gain admission to the vast majority of high schools without having to take an entrance exam. To ensure the quality of each student, remedial teaching plays a significant role in students' basic academic competence.
Remedial teaching generally includes the processes of "assess - teaching - reassessment". Assessment system aims to enhance the quality in student's basic competence selection. The assessment system provides the data of the students' basic ability, academic ability, and learning motivation. Based on the data, teachers can only set up the teaching goals and implement appropriate learning materials for the students. The current assessment system tends to ignore some vital aspects of students' learning motivation during the assessment process. That is, the assessment system cannot fully reflect whether the scores are underestimated by the unmeasured aspects such as students’ lack of motivation and levels of efforts. It is also unknown that whether student guessing influences the results. Caused by incomplete results of assessment, teaching resources cannot be effectively used to help low-achieving students.
The researcher uses EEG to conduct a quasi-experimental study.
The brainwave data of the experimental group are collected before and after the interventions of motivation strategies. The data, then, are compared with the data of the control group that are not intervened by motivation strategies.
The results of this study show that post-test scores of low-proficiency subjects intervened by motivation strategies are higher in comparison with those in the control group. In addition, the EEG demonstrates that in post-tests of the experimental group, subjects' attention performance index is increased and meditation changes are higher than the control group. The results achieved significant difference.
書名頁 i
論文口試委員審定書 ii
授權書 iii
中文摘要 vi
英文摘要 viii
誌謝 x
目錄 xi
表目錄 xiv
圖目錄 xv
第一章、緒論 1
第二章、文獻探討 4
2.1動機與成就測驗 4
2.2 腦波與注意力及學習成效 5
2.3 腦波與認知負荷及學習成效 5
2.4 腦波與正向情緒及學習成效 7
第三章、研究方法 8
3.1 研究流程 8
3.2 研究對象 9
3.3 實驗設計 9
3.4 實驗步驟 11
3.5 腦波工具 11
3.6 心律變異分析 (HRVAS) / poincare plot analysis 13
3.7 腦波分析 15
3.8統計分析 16
第四章、實驗結果 17
4.1 前後測成績比較 17
4.1.1組別前測成績之獨立樣本t檢定 17
4.1.2後測成績共變數分析 17
4.1.3實驗組別與高低分組前後測與進步分數整理 19
4.2 腦波數值分析 20
4.2.1組別前測腦波獨立樣本t檢定 20
4.2.2組別後測腦波獨立樣本t檢定 21
4.3 控制組前後腦波比較 23
4.4 實驗組前後腦波比較 24
第五章、討論 25
5.1 激勵策略對於動機與成績的影響 25
5.2 激勵策略對於腦波的影響 26
5.3 不同組別腦波前後的變化 26
5.3.1 控制組前後測腦波 26
5.3.2 實驗組前後測腦波 27
5.3.3 高低分組前後測腦波 28
第六章、結論與未來研究建議 29
第七章、參考文獻 31
中文文獻
1. 曾文志(2010)。走過正向心理學的第一個十年。師友月刊,513期,62-66。
2. 楊智先(2010)。正向心理學脈絡下的創造力教育實踐:從希望理論談起。北縣教育,70期, 56-59。
3. 黃絢質,「青少年正向思考、正向情緒與學習動機」,臺灣師範大學,碩士,2010。
英文文獻
1. Asseburg, Regine, and Andreas Frey. "Too hard, too easy, or just right? The relationship between effort or boredom and ability-difficulty fit." Psychological Test and Assessment Modeling, Vol. 55, Issue 1, pp.92-104, 2013.
2. Barry, Robert J., et al. "Resting-state EEG gamma activity in children with Attention-Deficit/Hyperactivity Disorder." Clinical neurophysiology, Vol. 121, Issue 11, pp.1871-1877, 2010.
3. Bental, B., & Tirosh, E. (2007). The relationship between attention, executive functions and readingdomain abilities in attention deficit hyperactivity disorder and reading disorder: A comparativestudy. Journal of Child Psychology and Psychiatry, Vol. 48, Issue 5, pp.455-463.
4. Brennan M, Palaniswami M, Kamen P: Do existing measures of poincare plot geometry reflect nonlinear features of heart rate variability. IEEE Trans on Biomed Engg, Vol. 48, Issue 11, pp.1342-1347, 2001.
5. Fan, J., McCandliss, B. D., Sommer, T., Raz, M., & Posner, M. I. Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, Vol. 14, Issue 3, pp. 340-347, 2002.
6. Gevensleben, Holger, et al. "Distinct EEG effects related to neurofeedback training in children with ADHD: a randomized controlled trial." International Journal of Psychophysiology,Vol. 74, Issue 2, pp.149-157, 2009.
7. Gola, Mateusz, et al. "EEG beta band activity is related to attention and attentional deficits in the visual performance of elderly subjects." International Journal of Psychophysiology, Vol . 89, Issue 3, pp.334-341, 2013.
8. Linden, M., Habib, T., Radojevic, V.: A controlled study of the effects of EEG biofeedback on cognition and behavior of children with attention deficit disorder and learning disabilities. Applied Psychophysiology and Biofeedback, Vol. 21, Issue 1, pp.35-49, 1996.
9. Pass, F. G. W. & Van Merrienboer, J. J. G. "Variability of worked examples and transfer of geometrical problem solving : A cognitive load approach." Journal of Educational Psyhology, Vol. 86, Issue 1, pp.122-130, 1994.
10. Pintrich, Paul R., and Elisabeth V. De Groot. "Motivational and self-regulated learning components of classroom academic performance." Journal of Educational Psychology, Vol. 82, Issue 1, pp.28-50, 1990.
11. Roderer, Thomas, and Claudia M. Roebers. "Children's Performance Estimation in Mathematics and Science Tests over a School Year: A Pilot Study."Electronic Journal of Research in Educational Psychology, Vol. 11, Issue 1, pp.5-24, 2013.
12. Savage, R., Cornish, K., Manly, T., & Hollis, C.. Cognitive processes in children's reading and attention: The role of working memory, divided attention, and response inhibition. British Journal of Psychology, Vol. 97, Issue 3, pp.365-385, 2006.
13. Sona, D., Veeramachaneni, S., Olivetti, E., Avesani, P.: Inferring cognition from fMRI brain images. In: de S?, J.M., Alexandre, L.A., Duch, W., Mandic, D.P. (eds.) ICANN 2007. LNCS, Vol. 4669, Issue 2, pp. 869-878, 2007.
14. Sundre, D. L., & Kitsantas, A. An exploration of the psychology of the examinee: Can examinee self-regulation and test-taking motivation predict consequential and nonconsequential test performance? Contemporary Educational Psychology, Vol. 29, Issue 1, pp.6-26, 2004.
15. Sutton, S., Tueting, P., Zubin, J., and John, E. R., "Information delivery and the sensory evoked potential." Science, Vol. 155, Issue 3768, pp.1436-1439, 1967.
16. Sweller, J.,"Cognitive load during problem solving." Effects on learing Cognitive Science, Vol. 12, Issue 2, pp.257-285, 1988.
17. Tongkun Shi , Xia Li , Jia Song , Na Zhao , Caihong Sun , Wei Xia ,Lijie Wua,Akemi Tomoda :EEG characteristics and visual cognitive function of childrenwith attention deficit hyperactivity disorder (ADHD) Brain & Development, Vol. 34, Issue 10, pp.806-811, 2012.
18. Tulppo MP, Makikallio TH, Takala TES, Seppanen T, V HH: Quantitative beat-to-beat analysis of heart rate dynamics during exercise. Am J Physiol, Vol. 271, Issue 1, pp.244-252, 1996.
19. Wise, S. L., & DeMars, C. E. Examinee noneffort and the validity of program assessment results. Educational Assessment, Vol. 15, Issue 1, pp.27-41, 2010.
20. Woo, M. A., Stevenson, W. G., Moser, D. K., Trelease, R. B., & Harper, R. M. Patterns of beat-to-beat heart rate variability in advanced heart failure.American heart journal, Vol. 123, Issue 3, pp.704-710, 1992.
21. Yoshida, Kouji, et al. "Trial of a distance learning system using a brain wave sensor." Knowledge-Based and Intelligent Information and Engineering Systems. Springer Berlin Heidelberg, Vol. 6883, Issue 3, pp.86-95, 2011.
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