跳到主要內容

臺灣博碩士論文加值系統

(18.97.14.86) 您好!臺灣時間:2024/12/06 15:31
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:吳玟憲
研究生(外文):Wen-Hsien Wu
論文名稱:運用分組教學探討同儕壓力與學習成效─以程式設計為例
論文名稱(外文):Exploring Peer Stress and Learning Effectiveness in a Group Setting - An Example of Programming Design Course
指導教授:姜琇森姜琇森引用關係蕭國倫蕭國倫引用關係
學位類別:碩士
校院名稱:國立臺中科技大學
系所名稱:資訊管理系碩士班
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:2020
畢業學年度:108
語文別:中文
論文頁數:46
中文關鍵詞:同儕壓力學習成效腦波程式設計
外文關鍵詞:Peer StressLearning effectivenessElectroencephalographyProgramming
相關次數:
  • 被引用被引用:1
  • 點閱點閱:223
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
在求學過程中,帶給學生影響的不僅只有教師與課程內容,還有鄰座的同學們。這些同學對學生本身而言,往往比遠在講台上的教師更具有影響力,這樣的影響力甚至會影響到學生的學習成效。過去大多都使用較為主觀的問卷進行同儕關係的研究,但同儕之間的影響不容易被明確的描述與評估,因此本研究提供了客觀的評估依據指標。過去與同儕關係相關的研究也多著重在整個群體的影響力,而非個體在群體中所受的影響,因此本研究提出了以個體為單位的實驗方法與結果。
本研究透過受測者的邏輯能力對受測者進行分類,按照分組教學法對受測者進行分組,進行教學相同內容並使其互相影響,讓受測者在彼此比較學習成效時產生同儕壓力。本研究透過腦波訊號評估受測者之間的同儕壓力;以完成測驗所產生的名次評估學習成效。於本研究中,發現了同儕壓力的腦波特徵值,並發現同儕壓力確實會對受測者造成影響,其中(1)高學習力者之間會互相激勵,達到更好的學習成效、(2)低學習力者之間會彼此警惕,保持一定的學習成效、(3)高學習力者會受低學習力者的影響而鬆懈,無法發揮應有的專注度而使學習成效下滑、(4)低學習力者可能會受高學習力者影響而失去信心,產生放棄心理,最終無法獲得該有的學習成效。因此,若要使受測者表現出最佳學習成效,同儕的學習能力不能差異過大且彼此要互相熟悉;若差異過大則會導致其中一方產生認輸的心理,另一方無法產生競爭意識,導致雙方的學習成效都會降低。
In school, not only the teachers and the curriculum influence the students, but also the classmates. These classmates are often more influential to students than teachers who are far away on the stage, it will even affect students’ learning effectiveness. In the past, studies which research peer effect usually used subjective questionnaires to evaluate, but it isn’t easy to be clearly described and evaluated. Therefore, this study provides an objective assessment based on indicators. Most of studies researched the effect between groups. Thence, This study proposes experimental methods and results on an individual basis.
This research divides subjects to two groups based on their logical abilities, according to group teaching method to group setter. Teach the same curriculum and make setter affect each other. The setter generate peer stress by the learning effectiveness between each other. This research explorers peer effect between subjects through Electroencephalography(EEG) and evaluate learning effectiveness between the ranking by programming test.
The research finding the EEG eigenvalues and knowing how to make the subjects show the best learning effectiveness. (1) the students with high learning ability will motivate each other to achieve better learning effectiveness, (2) the students with low learning ability will be alert to each other and maintain a certain learning effectiveness, (3) the student with high learning ability will be slackened by the peer effect of the student with low learning ability, and they will not be able to give full play to their due attention and the learning effectiveness will decline, (4) the student with low learning ability may lose confidence and give up due to the peer effect of the student with high learning ability, then they can’t get the learning effectiveness that should be in the end. Therefore, learning ability cannot be too different with peer, if the difference is too large, the learning effectiveness of both parties will be reduced.
摘要 i
ABSTRACT ii
目次 iv
表目次 vi
圖目次 vii
第一章 緒論 1
第一節 背景與動機 1
第二節 研究目的 2
第二章 文獻探討 3
第一節 同儕效應(Peer Effect) 3
第二節 同儕關係與學習成效 3
第三節 程式語言學習成效之評估 4
第四節 壓力與腦波(Electroencephalography)之關係 5
第五節 過去壓力與腦波之相關研究 7
第三章 研究方法 9
第一節 分組教學法 9
第二節 獨立樣本T檢定(Independent-Samples t -Test) 9
第三節 巴特沃斯濾波器(Butterworth Filter) 9
第四節 快速傅立葉轉換(Fast Fourier Transform) 10
第五節 最小-最大特徵縮放法(Min-Max scaling) 12
第四章 實驗設計 13
第一節 實驗對象 13
第二節 研究工具 13
4-2-1 程式能力評估 14
4-2-2 邏輯能力評估 15
4-2-3 學習成效評估 15
4-2-4 同儕壓力腦波評估 16
第三節 實驗設計 16
4-3-1 學習情境設計 17
4-3-2 實驗流程 18
第四節 實驗結果 21
4-4-1腦波資料與資料處理過程 21
4-4-2腦波資料結果與分析 22
4-4-3學習成效結果與分析 31
第五章 討論 36
第一節 同儕壓力階段特徵 36
第二節 學習意願與學習成效 36
第三節 同儕關係的強弱 37
第四節 同儕關係與學習成效 37
第六章 結論 39
第一節 研究貢獻 39
第二節 研究限制 40
第三節 未來展望 40
參考文獻 41
Allen, A. P., Kennedy, P. J., Cryan, J. F., Dinan, T. G., & Clarke, G. (2014). Biological and psychological markers of stress in humans: focus on the Trier Social Stress Test. Neuroscience & Biobehavioral Reviews, 38, 94-124.
Asif, A., Majid, M., & Anwar, S. M. (2019). Human stress classification using EEG signals in response to music tracks. Comput Biol Med, 107, 182-196.
Barnes, J., Beaver, K. M., Young, J. T., & TenEyck, M. (2014). A behavior genetic analysis of the tendency for youth to associate according to GPA. Social Networks, 38, 41-49.
Brechwald, W. A., & Prinstein, M. J. (2011). Beyond homophily: A decade of advances in understanding peer influence processes. Journal of Research on Adolescence, 21(1), 166-179.
Cheema, A., & Singh, M. (2019). An application of phonocardiography signals for psychological stress detection using non-linear entropy based features in empirical mode decomposition domain. Applied Soft Computing, 77, 24-33.
Chen, W. (2020). Disagreement in peer interaction: Its effect on learner task performance. System, 88, 102179.
Choi, Y., Kim, M., & Chun, C. (2015). Measurement of occupants'' stress based on electroencephalograms (EEG) in twelve combined environments. Building and Environment, 88, 65-72.
Clark, I. A., & Maguire, E. A. (2019). Do questionnaires reflect their purported cognitive functions? BioRxiv, 583690.
Coyle, D. K., Howard, S., Bibbey, A., Gallagher, S., Whittaker, A. C., & Creaven, A.-M. (2019). Personality, cardiovascular, and cortisol reactions to acute psychological stress in the Midlife in the United States (MIDUS) study. International Journal of Psychophysiology.
Creswell, J. D., Pacilio, L. E., Lindsay, E. K., & Brown, K. W. (2014). Brief mindfulness meditation training alters psychological and neuroendocrine responses to social evaluative stress. Psychoneuroendocrinology, 44, 1-12.
Davidson, R. J. (1984). 11 Affect, cognition, and hemispheric specialization. Emotions, cognition, and behavior, 320.
Davis, B. G. (2009). Tools for teaching: John Wiley & Sons.
De Pascalis, V., Varriale, V., & Rotonda, M. “EEG oscillatory activity associated to monetary gain and loss signals in a learning task: effects of attentional impulsivity and learning ability,” International Journal of Psychophysiology, Vol. 85, No. 1, pp. 68-78, 2012.
Deguire, F., Thébault-Dagher, F., Barlaam, F., Knoth, I. S., Lafontaine, M.-P., Lupien, S., & Lippé, S. (2019). The relationship between acute stress and EEG repetition suppression in infants. Psychoneuroendocrinology, 104, 203-209.
Dieterich, S. E. (2015). Coevolution of adolescent friendship networks and school outcomes, The. Colorado State University. Libraries,
Dokuka, S., Valeeva, D., & Yudkevich, M. (2015). The diffusion of academic achievements: social selection and influence in student networks. Higher School of Economics Research Paper No. WP BRP, 65.
Düsing, R., Tops, M., Radtke, E. L., Kuhl, J., & Quirin, M. “Relative frontal brain asymmetry and cortisol release after social stress: The role of action orientation,” Biological psychology, 115, 86-93, 2016.
Flashman, J. (2012). Academic achievement and its impact on friend dynamics. Sociology of education, 85(1), 61-80.
Foster, G. (2005). Making friends: A nonexperimental analysis of social pair formation. Human Relations, 58(11), 1443-1465.
Ghazali, D. A., Darmian-Rafei, I., Nadolny, J., Sosner, P., Ragot, S., & Oriot, D. (2018). Evaluation of stress response using psychological, biological, and electrophysiological markers during immersive simulation of life threatening events in multidisciplinary teams. Australian Critical Care, 31(4), 226-233.
Goodman, R. N., Rietschel, J. C., Lo, L.-C., Costanzo, M. E., & Hatfield, B. D. (2013). Stress, emotion regulation and cognitive performance: The predictive contributions of trait and state relative frontal EEG alpha asymmetry. International Journal of Psychophysiology, 87(2), 115-123.
Ishii, Y., Ogata, H., Takano, H., Ohnishi, H., Mukai, T., & Yagi, T. (2008). Study on mental stress using near-infrared spectroscopy, electroencephalography, and peripheral arterial tonometry. Paper presented at the 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
Jebelli, H., Hwang, S., & Lee, S. (2018). EEG-based workers'' stress recognition at construction sites. Automation in Construction, 93, 315-324.
Kiuru, N., Aunola, K., Nurmi, J.-E., Leskinen, E., & Salmela-Aro, K. (2008). Peer group influence and selection in adolescents'' school burnout: A longitudinal study. Merrill-Palmer Quarterly (1982-), 23-55.
Kordaki, M. (2010). A drawing and multi-representational computer environment for beginners’ learning of programming using C: Design and pilot formative evaluation. Computers & Education, 54(1), 69-87.
Laurenti, R., & Acuña, F. M. B. (2020). Exploring antecedents of behavioural intention and preferences in online peer-to-peer resource sharing: A Swedish university setting. Sustainable Production and Consumption, 21, 47-56.
Lotfan, S., Shahyad, S., Khosrowabadi, R., Mohammadi, A., & Hatef, B. (2019). Support vector machine classification of brain states exposed to social stress test using EEG-based brain network measures. Biocybernetics and Biomedical Engineering, 39(1), 199-213.
Mayer, A., & Puller, S. L. (2008). The old boy (and girl) network: Social network formation on university campuses. Journal of public economics, 92(1-2), 329-347.
Minkley, N., Schröder, T. P., Wolf, O. T., & Kirchner, W. H. (2014). The socially evaluated cold-pressor test (SECPT) for groups: Effects of repeated administration of a combined physiological and psychological stressor. Psychoneuroendocrinology, 45, 119-127.
Monroe, S., & Slavich, G. (2016). Psychological stressors: overview. In Stress: Concepts, cognition, emotion, and behavior (pp. 109-115): Elsevier.
Navarro, M. A., Stalgaitis, C. A., Walker, M. W., & Wagner, D. E. (2019). Youth peer crowds and risk of cigarette use: The effects of dual peer crowd identification among hip hop youth. Addictive behaviors reports, 10, 100204.
O''Connor, P. J., & Brown, C. M. (2016). Sex-linked personality traits and stress: Emotional skills protect feminine women from stress but not feminine men. Personality and individual differences, 99, 28-32.
Ouahbi, I., Kaddari, F., Darhmaoui, H., Elachqar, A., & Lahmine, S. (2015). Learning basic programming concepts by creating games with scratch programming environment. Procedia-Social and Behavioral Sciences, 191, 1479-1482.
Papousek, I., Wimmer, S., Lackner, H. K., Schulter, G., Perchtold, C. M., & Paechter, M. (2019). Trait positive affect and students’ prefrontal EEG alpha asymmetry responses during a simulated exam situation. Biological psychology, 148, 107762.
Patacchini, E., & Zenou, Y. (2011). Neighborhood effects and parental involvement in the intergenerational transmission of education. Journal of Regional Science, 51(5), 987-1013.
Porcelli, A. J., & Delgado, M. R. (2017). Stress and decision making: effects on valuation, learning, and risk-taking. Current opinion in behavioral sciences, 14, 33-39.
Rosen, A., & Reiner, M. “Right frontal gamma and beta band enhancement while solving a spatial puzzle with insight.” International Journal of Psychophysiology, 2016.
Ryan, A. M. (2000). Peer groups as a context for the socialization of adolescents'' motivation, engagement, and achievement in school. Educational Psychologist, 35(2), 101-111.
Ryan, A. M. (2001). The peer group as a context for the development of young adolescent motivation and achievement. Child development, 72(4), 1135-1150.
Sacerdote, B. (2011). Peer effects in education: How might they work, how big are they and how much do we know thus far? In Handbook of the Economics of Education (Vol. 3, pp. 249-277): Elsevier.
Saeed, S. M. U., Anwar, S. M., Majid, M., & Bhatti, A. M. “Psychological stress measurement using low cost single channel EEG headsetm” 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), IEEE, pp. 581-585, 2015.
Seidman, R. H. (1981). The effects of learning a computer programming language on the logical reasoning of school children.
Selye, H. (1956). The stress of life.
Shields, G. S., Sazma, M. A., & Yonelinas, A. P. (2016). The effects of acute stress on core executive functions: A meta-analysis and comparison with cortisol. Neuroscience & Biobehavioral Reviews, 68, 651-668.
Van Ryzin, M. J., & Roseth, C. J. (2019). Cooperative learning effects on peer relations and alcohol use in middle school. Journal of Applied Developmental Psychology, 64, 101059.
Vaquero, L. M., & Cebrian, M. (2013). The rich club phenomenon in the classroom. Scientific reports, 3, 1174.
Winston, G., & Zimmerman, D. (2004). Peer effects in higher education. In College choices: The economics of where to go, when to go, and how to pay for it (pp. 395-424): University of Chicago Press.
Woolf, K., Potts, H. W., Patel, S., & McManus, I. C. (2012). The hidden medical school: a longitudinal study of how social networks form, and how they relate to academic performance. Medical teacher, 34(7), 577-586.
Xie, X., Tao, Y., Liu, A., & Lei, L. (2020). Peer relationship mediates the effect of mobile phone functions on adolescent adaptation. Children and Youth Services Review, 108, 104571.
Yang, T.-C., Chen, S. Y., & Hwang, G.-J. (2015). The influences of a two-tier test strategy on student learning: A lag sequential analysis approach. Computers & Education, 82, 366-377.
Zimmerman, D. J. (2003). Peer effects in academic outcomes: Evidence from a natural experiment. Review of Economics and statistics, 85(1), 9-23.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊