1. NCCU Academic Hub
  2. 學術產出
  3. 理學院
  4. 學位論文
  5. Item

學術產出-學位論文

文章檢視/開啟

書目匯出

Google ScholarTM

政大圖書館

引文資訊

TAIR相關學術產出

題名 情緒對類別學習之影響
The effect of mood on category learning
作者 盧毓文
Lu, Yu Wen
貢獻者 楊立行
Yang, Lee Xieng
盧毓文
Lu, Yu Wen
關鍵詞 情緒
多元分類系統
日期 2011
上傳時間 30-十月-2012 15:21:44 (UTC+8)
摘要 過去研究發現，情緒會影響認知執行作業的表現，而正負向情緒分別有著不一樣的效果，Ashby等人提出的多元分類系統（Competition between verbal and implicit system，COVIS），包含一外顯系統，涉及的是工作記憶與假設檢定，而該系統會因好心情，增加多巴胺濃度並作用在前額葉區，故據COVIS理論，正向情緒會增加認知彈性，使需要投入注意力的外顯作業，學習表現更好，但內隱系統涉及的是不同的腦區活動，故內隱作業歷程不受任何情緒的影響。而從另一觀點，根據認知捷思，正向情緒狀態，會促動認知捷思歷程，因為好心情降低對周遭訊息處理的動機，而多數認知執行作業，需要審慎考慮的分析以及注意力的控制，所以從動機論的觀點，預期正向情緒會損傷認知執行作業的表現，相對的，負向情緒讓個體警覺，進而提升對周遭訊息處理的動機，使人們會更加小心翼翼，採用系統式分析歷程，故在此觀點下，負向情緒可以提升認知作業表現。本研究進一步釐清，探究在正向及負向情緒下，到底哪種情緒會增進分類學習的正確率表現。實驗一、二、三主要的目的，在複製出Nadler（2010）研究結果，即正向情緒助長了外顯系統作業表現，由於實驗一的情緒誘發素材成份過於複雜，無法複製出Nadler（2010）相同的結果，實驗二進而使用更純粹誘發素材，實驗結果支持認知捷思的觀點，即負向情緒，提升了受試者分類學習表現，實驗三進一步確認，情緒激發水準在情緒對分類學習影響下所扮演的角色，研究結果顯示，情緒的激發水準確實調節分類學習表現，尤其在正向情緒下，高激發水準會損傷外顯學習系統作業表現，低激發水準時，則助長外顯作業系統的學習表現，故COVIS理論的預期，正向情緒有比較好的外顯作業學習表現，唯情緒激發水準低時，方能實現。
參考文獻 林和逸（1998）。情緒狀態的覺察與引發來源類別對情緒調適的影響。輔仁大學心理學研究所，碩士論文。
Ashby, F.G., L.A., Alfonso-Reese, Turken, A.U., & Waldron, E.M. (1998). A neuropsychological theory of multiple systems in category learning, Psychological Review,105 (3), 442–481.
Ashby, F.G., & E.Gott, R. (1988). Decision rules in the perception and categorization of multidimensional stimuli. Journal of Experimental Psychology, 14, 33-53.
Ashby, F. G., Noble, S., Filoteo, J. V., Waldron, E. M., & Ell, S. W. (2003). Category
Ashby, F.G., & Maddox, W.T. (1993).Relations between prototype, exemplar, and decision bound models of categorization, Journal of Mathematical Psychology 37 (3), 372–400.
Bartolic, E.I., Basso, M.R., Schefft, B.K., Glauser, T., & Titanic-Schefft, M. (1999). Effects of experimentally-induced emotional states on frontal lobe cognitive task performance. Neuropsychologia, 37, 677-683.
Bless, H., Bohner, G., & Schwarz, N. (1990). Mood and persuasion: A cognitive response analysis. Personality and Social Psychology Bulletin, 16, 331-345.
Bodenhausen, G. V., Sheppard, L. A., & Kramer, G. P. (1994). Negative
affect and social judgment: The differential impact of anger and sadness. European Journal of Social Psychology, 24, 45-62.
Brewer, D., Doughtie, E. B., & Lubin, B. (1980). Induction of mood and mood shift.Journal of Clinical Psychology, 36 215-225.
Clark, L., Iversen, S. D., & Goodwin, G. M. (2001). The influence of positive and negative mood states on risk taking, verbal fluency, and salivary cortisol. Journal of Affective Disorders, 63, 179–187.
Damasio, A. R. (1994). Descartes’ Error: Emotion, reasoning, and human brain. New York:Grosset/Putnam.
Davidson R.J., Ekman P, Saron C.D., Senulis J.A., Friesen W.V.(1990). Approach-withdrawal and cerebral asymmetry: emotional expression and brain physiology.Journal of personality and social psychology,58,330-341.
De Vries, M., Holland, R. W., & Witteman, C. L. M. (2008). In the winning mood: Affect in the Iowa gambling task. Judgment and Decision Making, 3, 42-50.
Dreisbach, G., & Goschke, T. (2004). How positive affect modulates cognitive control: Reduced perseveration at the cost of increased distractibility. Journal of Experimental Psychology: Learning, Memory & Cognition, 30, 343–353.
Evans, J. St. B. T. (1989). Bias in Human Reasoning: Causes and Consequences. Brighton, UK: Erlbaum.
Evans, J. St. B. T. (2006). The heuristic-analytic theory of reasoning: extension and evaluation. Psychonomic Bulletin & Review, 13(3), 378-395.
Evans, J. St. B. T., & Over, D. E. (1996). Rationality and Reasoning. Hove, UK: Psychology Press.
Hammond, K. R. (1996). Human Judgment and Social Policy. New York: Oxford University Press.
Hertel, G., Neuhof, J., Theuer, T., & Kerr, N. L. (2000). Mood effects on cooperation in small groups: Does positive mood simply lead to more cooperation? Cognition and Emotion, 14, 441-472.
Isen, A. M., & Means, B. (1983). The influence of positive affect on decision-making strategy. Social Cognition, 2, 18-31.
Isen, A. M., Rosenzweig, A. S., & Young, M. J. (1991).The influence of positive affect on clinical problem solving. Medical Decision Making, 11, 221-227.
Kruschke, J. K. (1992). ALCOVE: An exemplar-based connectionist model of category learning.Psychological Review, 99, 22-44.
Kruschke, J. K., Johansen, M. K. (1999). A model of probabilistic category learning. Journal of Experimental Psychology: Learning, Memory H Cognition, 25, 1083-1119.
Lang, P. J. (1980). Behavioral treatment and bio-behavioral assessment: Computer applications. In J. M. Schlien （Ed.）, Research in Psychotherapy. 3. 90-103.
Learning Deficits in Parkinson`s Disease.. Neuropsychology, 17, 115-124.
Lewandowsky, S., Yang, L.X., Newell, B.R., & Kalish, M. (in press). Working memory does not dissociate between different perceptual categorization tasks. Journal of Experimental Psychology: Learning, Memory, & Cognition.
Mackie, D. M., Gastardo-Conaco, M. C., & Skelly, J. J. (1992). Knowledge of the advocated position and the processing of in-group and out-group persuasive messages. Personality and Social Psychology Bulletin, 18, 145-151.
Maddox, W. T., Ashby, F. G., & Bohil, C. J. (2003). Delayed Feedback Effects on Rule-Based and Information-Integration Category Learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 650-662.
Markman, A.B., Maddox, W.T., & Worthy, D.A. (2007). Regulatory Fit Effects in a Choice Task. Psychonomic Bulletin and Review, 14, 1125-1132.
Nadler, R. T., Rabi, R., & Minda, J. P. (2010). Better Mood and Better Performance: Learning Rule-Described Categories Is Enhanced by Positive Mood. Psychological Science, 21(12), 1770-1776.
Nomura, E.M & Reber, P.J. (2008). A review of medial temporal lobe and caudate contributions to visual category learning. Neuroscience and Biobehavioral Reviews, 32, 279-291.
Nosofsky, R. M., Palmeri, T. J., & McKinley, S. C. (1994). Rule-plus-exception model of classification learning. Psychological Review, 101, 53-79.
Nosofsky, R. M., Stanton, R. D., & Zaki, S. R. (2005). Procedural interference in perceptual classification: Implicit learning or cognitive complexity? Memory & Cognition, 33, 1256-1271.
Payne, J. W., Bettman, J. R., & Johnson, E. J. (1988). Adaptive strategy selection in decision making. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14, 534-552.
Phillips, L. H., Bull, R., Adams, E., & Fraser, L. (2002). Positive mood and executive function: Evidence from Stroop and fluency tasks. Emotion, 2, 21–22.
Posner, M.I., & Keele, S.W. (1968). On the genesis of abstract ideas. Journal of Experimental Psychology, 77, 353-363.
Reber, A. S. (1993). Implicit Learning and Tacit Knowledge. Oxford, UK: Oxford University Press.
Ross, B. H., & Kennedy, P. T. (1990), Genernalizing from the use of earlier examples in problem solving, Journal of Experimental Psychology: Learning, Memory, and Cognition, 16(1), 42-55.
Schwarz, N. (1990). Feelings as information: Informational and motivational functions of affective states. In T. E. Higgins & R. M. Sorrentino (Eds.), Handbook of motivation and cognition . New York: Guilford.
Schwarz, N., & Bless, H. (1991). Happy and mindless, but sad and smart? The impact of affective states on analytic reasoning. In J. P. Forgas (Eds.), Emotion and social judgments, 55-71.
Stanton, R.D., & Nosofsky, R.M. (2007). Feedback interference and dissociations of classification:Evidence against the multiple learning-systems hypothesis. Memory & Cognition, 35, 1747-1758.
Watson, D., Clark, L., & Tellegen, A.(1998). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063-1070.
Wegener, Duane T. and Richard E. Petty (1994). Mood management across affective states: The hedonic contingency hypothesis, Journal of Personality and Social Psychology, 66 (6), 1034-48.
Wilson, T. D. (2002). Strangers to Ourselves. Cambridge, MA: Belknap.
Phan K.L., Wager T. Taylor S.F., & Liberzon I., (2002). Functional Neuroanatomy of Emotion: A Meta-analysis of Emotion Activation Studies in PET and fMRI. NeuroImage, 16:331-348.
 
描述 碩士
國立政治大學
心理學研究所
99752008
100
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0099752008
資料類型 thesis
dc.contributor.advisor 楊立行zh_TW
dc.contributor.advisor Yang, Lee Xiengen_US
dc.contributor.author (作者) 盧毓文zh_TW
dc.contributor.author (作者) Lu, Yu Wenen_US
dc.creator (作者) 盧毓文zh_TW
dc.creator (作者) Lu, Yu Wenen_US
dc.date (日期) 2011en_US
dc.date.accessioned 30-十月-2012 15:21:44 (UTC+8)-
dc.date.available 30-十月-2012 15:21:44 (UTC+8)-
dc.date.issued (上傳時間) 30-十月-2012 15:21:44 (UTC+8)-
dc.identifier (其他 識別碼) G0099752008en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/55033-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 心理學研究所zh_TW
dc.description (描述) 99752008zh_TW
dc.description (描述) 100zh_TW
dc.description.abstract (摘要) 過去研究發現，情緒會影響認知執行作業的表現，而正負向情緒分別有著不一樣的效果，Ashby等人提出的多元分類系統（Competition between verbal and implicit system，COVIS），包含一外顯系統，涉及的是工作記憶與假設檢定，而該系統會因好心情，增加多巴胺濃度並作用在前額葉區，故據COVIS理論，正向情緒會增加認知彈性，使需要投入注意力的外顯作業，學習表現更好，但內隱系統涉及的是不同的腦區活動，故內隱作業歷程不受任何情緒的影響。而從另一觀點，根據認知捷思，正向情緒狀態，會促動認知捷思歷程，因為好心情降低對周遭訊息處理的動機，而多數認知執行作業，需要審慎考慮的分析以及注意力的控制，所以從動機論的觀點，預期正向情緒會損傷認知執行作業的表現，相對的，負向情緒讓個體警覺，進而提升對周遭訊息處理的動機，使人們會更加小心翼翼，採用系統式分析歷程，故在此觀點下，負向情緒可以提升認知作業表現。本研究進一步釐清，探究在正向及負向情緒下，到底哪種情緒會增進分類學習的正確率表現。實驗一、二、三主要的目的，在複製出Nadler（2010）研究結果，即正向情緒助長了外顯系統作業表現，由於實驗一的情緒誘發素材成份過於複雜，無法複製出Nadler（2010）相同的結果，實驗二進而使用更純粹誘發素材，實驗結果支持認知捷思的觀點，即負向情緒，提升了受試者分類學習表現，實驗三進一步確認，情緒激發水準在情緒對分類學習影響下所扮演的角色，研究結果顯示，情緒的激發水準確實調節分類學習表現，尤其在正向情緒下，高激發水準會損傷外顯學習系統作業表現，低激發水準時，則助長外顯作業系統的學習表現，故COVIS理論的預期，正向情緒有比較好的外顯作業學習表現，唯情緒激發水準低時，方能實現。zh_TW
dc.description.tableofcontents 摘要 1
緒論 1
分類學習派典 1
(一)原型理論 2
(二)範例理論 2
(三)規則理論 4
(四)多元分類學習系統 2
COVIS 模型之神經基礎 4
(一)外顯系統 5
(二)內隱系統 6
(三)腦造影研究 7
(四)對COVIS理論的質疑 7
認知功能受情緒調節影響 9
(一)情緒與認知捷思 9
(二)情緒與決策 10
(三)情緒調節認知功能 11
(四)情緒與創造力 13
實驗一 14
研究方法 14
受試者 14
情緒刺激材料 15
分類學習刺激材料 20
實驗程序 21
實驗結果 22
SAM-Valence 22
SAM-Arousal 23

Category Learning 26
討論 32
實驗二 36
研究方法 36
受試者 36
情緒刺激材料 36
分類學習刺激材料 37
實驗程序 39
實驗結果 40
SAM-Valence 40
SAM-Arousal 41
SAM-Arousal v.s. Dominance 42
情緒前後測分析 43
Category Learning 43
討論 48
實驗三 49
實驗三A 49
研究方法 49
受試者 49
情緒刺激材料 49
分類學習刺激材料 50
實驗程序 51
實驗結果 51
SAM-Valence 52
SAM-Arousal 52
Category Learning 52
實驗三B 58
實驗結果 58
SAM-Valence 59
SAM-Arousal 59
Category Learning 61
各實驗之綜合分析 67
綜合討論 72
本研究可能有的問題與限制 72
與COVIS理論之比對驗證 73
參考文獻 75
附錄 80
附錄一 正負向情感量表 81
附錄二 PANAS中文版 82
附錄三 SAM問卷 83
附錄四 GABOR指導語 84
附錄五 情緒成份問卷 85
附錄六 正向事件回憶問卷 86
附錄七 負向事件回憶問卷 87
附錄八 SAM問卷(自傳式記憶) 89
附錄九 SAM問卷(情緒音樂) 90		zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0099752008en_US
dc.subject (關鍵詞) 情緒zh_TW
dc.subject (關鍵詞) 多元分類系統zh_TW
dc.title (題名) 情緒對類別學習之影響zh_TW
dc.title (題名) The effect of mood on category learningen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 林和逸（1998）。情緒狀態的覺察與引發來源類別對情緒調適的影響。輔仁大學心理學研究所，碩士論文。
Ashby, F.G., L.A., Alfonso-Reese, Turken, A.U., & Waldron, E.M. (1998). A neuropsychological theory of multiple systems in category learning, Psychological Review,105 (3), 442–481.
Ashby, F.G., & E.Gott, R. (1988). Decision rules in the perception and categorization of multidimensional stimuli. Journal of Experimental Psychology, 14, 33-53.
Ashby, F. G., Noble, S., Filoteo, J. V., Waldron, E. M., & Ell, S. W. (2003). Category
Ashby, F.G., & Maddox, W.T. (1993).Relations between prototype, exemplar, and decision bound models of categorization, Journal of Mathematical Psychology 37 (3), 372–400.
Bartolic, E.I., Basso, M.R., Schefft, B.K., Glauser, T., & Titanic-Schefft, M. (1999). Effects of experimentally-induced emotional states on frontal lobe cognitive task performance. Neuropsychologia, 37, 677-683.
Bless, H., Bohner, G., & Schwarz, N. (1990). Mood and persuasion: A cognitive response analysis. Personality and Social Psychology Bulletin, 16, 331-345.
Bodenhausen, G. V., Sheppard, L. A., & Kramer, G. P. (1994). Negative
affect and social judgment: The differential impact of anger and sadness. European Journal of Social Psychology, 24, 45-62.
Brewer, D., Doughtie, E. B., & Lubin, B. (1980). Induction of mood and mood shift.Journal of Clinical Psychology, 36 215-225.
Clark, L., Iversen, S. D., & Goodwin, G. M. (2001). The influence of positive and negative mood states on risk taking, verbal fluency, and salivary cortisol. Journal of Affective Disorders, 63, 179–187.
Damasio, A. R. (1994). Descartes’ Error: Emotion, reasoning, and human brain. New York:Grosset/Putnam.
Davidson R.J., Ekman P, Saron C.D., Senulis J.A., Friesen W.V.(1990). Approach-withdrawal and cerebral asymmetry: emotional expression and brain physiology.Journal of personality and social psychology,58,330-341.
De Vries, M., Holland, R. W., & Witteman, C. L. M. (2008). In the winning mood: Affect in the Iowa gambling task. Judgment and Decision Making, 3, 42-50.
Dreisbach, G., & Goschke, T. (2004). How positive affect modulates cognitive control: Reduced perseveration at the cost of increased distractibility. Journal of Experimental Psychology: Learning, Memory & Cognition, 30, 343–353.
Evans, J. St. B. T. (1989). Bias in Human Reasoning: Causes and Consequences. Brighton, UK: Erlbaum.
Evans, J. St. B. T. (2006). The heuristic-analytic theory of reasoning: extension and evaluation. Psychonomic Bulletin & Review, 13(3), 378-395.
Evans, J. St. B. T., & Over, D. E. (1996). Rationality and Reasoning. Hove, UK: Psychology Press.
Hammond, K. R. (1996). Human Judgment and Social Policy. New York: Oxford University Press.
Hertel, G., Neuhof, J., Theuer, T., & Kerr, N. L. (2000). Mood effects on cooperation in small groups: Does positive mood simply lead to more cooperation? Cognition and Emotion, 14, 441-472.
Isen, A. M., & Means, B. (1983). The influence of positive affect on decision-making strategy. Social Cognition, 2, 18-31.
Isen, A. M., Rosenzweig, A. S., & Young, M. J. (1991).The influence of positive affect on clinical problem solving. Medical Decision Making, 11, 221-227.
Kruschke, J. K. (1992). ALCOVE: An exemplar-based connectionist model of category learning.Psychological Review, 99, 22-44.
Kruschke, J. K., Johansen, M. K. (1999). A model of probabilistic category learning. Journal of Experimental Psychology: Learning, Memory H Cognition, 25, 1083-1119.
Lang, P. J. (1980). Behavioral treatment and bio-behavioral assessment: Computer applications. In J. M. Schlien （Ed.）, Research in Psychotherapy. 3. 90-103.
Learning Deficits in Parkinson`s Disease.. Neuropsychology, 17, 115-124.
Lewandowsky, S., Yang, L.X., Newell, B.R., & Kalish, M. (in press). Working memory does not dissociate between different perceptual categorization tasks. Journal of Experimental Psychology: Learning, Memory, & Cognition.
Mackie, D. M., Gastardo-Conaco, M. C., & Skelly, J. J. (1992). Knowledge of the advocated position and the processing of in-group and out-group persuasive messages. Personality and Social Psychology Bulletin, 18, 145-151.
Maddox, W. T., Ashby, F. G., & Bohil, C. J. (2003). Delayed Feedback Effects on Rule-Based and Information-Integration Category Learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 650-662.
Markman, A.B., Maddox, W.T., & Worthy, D.A. (2007). Regulatory Fit Effects in a Choice Task. Psychonomic Bulletin and Review, 14, 1125-1132.
Nadler, R. T., Rabi, R., & Minda, J. P. (2010). Better Mood and Better Performance: Learning Rule-Described Categories Is Enhanced by Positive Mood. Psychological Science, 21(12), 1770-1776.
Nomura, E.M & Reber, P.J. (2008). A review of medial temporal lobe and caudate contributions to visual category learning. Neuroscience and Biobehavioral Reviews, 32, 279-291.
Nosofsky, R. M., Palmeri, T. J., & McKinley, S. C. (1994). Rule-plus-exception model of classification learning. Psychological Review, 101, 53-79.
Nosofsky, R. M., Stanton, R. D., & Zaki, S. R. (2005). Procedural interference in perceptual classification: Implicit learning or cognitive complexity? Memory & Cognition, 33, 1256-1271.
Payne, J. W., Bettman, J. R., & Johnson, E. J. (1988). Adaptive strategy selection in decision making. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14, 534-552.
Phillips, L. H., Bull, R., Adams, E., & Fraser, L. (2002). Positive mood and executive function: Evidence from Stroop and fluency tasks. Emotion, 2, 21–22.
Posner, M.I., & Keele, S.W. (1968). On the genesis of abstract ideas. Journal of Experimental Psychology, 77, 353-363.
Reber, A. S. (1993). Implicit Learning and Tacit Knowledge. Oxford, UK: Oxford University Press.
Ross, B. H., & Kennedy, P. T. (1990), Genernalizing from the use of earlier examples in problem solving, Journal of Experimental Psychology: Learning, Memory, and Cognition, 16(1), 42-55.
Schwarz, N. (1990). Feelings as information: Informational and motivational functions of affective states. In T. E. Higgins & R. M. Sorrentino (Eds.), Handbook of motivation and cognition . New York: Guilford.
Schwarz, N., & Bless, H. (1991). Happy and mindless, but sad and smart? The impact of affective states on analytic reasoning. In J. P. Forgas (Eds.), Emotion and social judgments, 55-71.
Stanton, R.D., & Nosofsky, R.M. (2007). Feedback interference and dissociations of classification:Evidence against the multiple learning-systems hypothesis. Memory & Cognition, 35, 1747-1758.
Watson, D., Clark, L., & Tellegen, A.(1998). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063-1070.
Wegener, Duane T. and Richard E. Petty (1994). Mood management across affective states: The hedonic contingency hypothesis, Journal of Personality and Social Psychology, 66 (6), 1034-48.
Wilson, T. D. (2002). Strangers to Ourselves. Cambridge, MA: Belknap.
Phan K.L., Wager T. Taylor S.F., & Liberzon I., (2002). Functional Neuroanatomy of Emotion: A Meta-analysis of Emotion Activation Studies in PET and fMRI. NeuroImage, 16:331-348.
 		zh_TW