近年來，隨著資訊科技的發展，腦神經科學研究工具也逐漸進步，在認知神經科學領域的相關研究也藉由先進的腦波儀器進行實驗，以更精確地瞭解人們在認知、決策等大腦的心智運作狀態變化。在資訊系統(IS)領域中，有許多比較李克特量表和語意差異量表的研究，但其中鮮少有以認知神經科學的觀點進行量表差異之相關研究，因此本研究將以認知神經科學為出發點，探討不同學科背景（文、理）的大學生，於填答李克特量表和語意差異量表時的認知歷程，以了解受測者受到量表刺激時腦波有何差異。
　　本研究使用實驗法，受測者為四十名大學生(文組20人、理組20人)，並使用腦波儀蒐集受測者填答量表時的腦波訊號，再藉由腦電圖(EEG)進行事件相關電位分析，以腦波成份P300來說明其認知差異。本研究結果發現：一、受測者於填答兩種量表時的腦波確實存在顯著的差異，且李克特量表之P300振幅均大於語意差異量表；二、當文、理組受測者於填答李克特量表時，腦部受到的反應及刺激較不易看出其有所差異；三、文、理組受測者於填答語意差異量表時的腦波確實存在差異，且文組受測者腦部所受到的刺激及反應較理組受測者大。本研究結果，可做為日後量表及腦波相關研究之參考。

With the advance of science and technology, the tools for research in cognitive neuroscience has made a great progress recently. The field of cognitive neuroscience has been utilizing advanced brainwave devices to better understand the changes in the mental functioning of the brain in cognition, emotion, and decision-making, etc. In the field of information systems, there are studies comparing the Likert scale with the Semantic Differential Scale, but few studies explore them from the perspective of cognitive neuroscience by using physiological measurement tools. Thus, the purpose of this study is to explore the cognitive differences in filling in the Likert scale and semantic differential scale by college students.
　　This study is based on an experimental method involving forty college students, 20 students in engineering and 20 students in liberal art. An electroencephalograph is used for brainwave signal collection when the subjects are filling the scale. Then the event-related potential component, P300 is used for statistical analysis. The results of this study show that students’ brain waves are different when they fill in the two scales, and the P300 for Likert scale is higher than that of semantic differential scale. The results also reveal that there are no significant differences between the two groups of subjects in filling in the Likert scale. However, both groups in filling in the semantic differential scale show significant differences, and the liberal art students exhibit higher P300 than those of engineering students, which may indicate that higher cognitive efforts needed in the interpretation of words. The results of this study can be used as a reference for future scale and brain wave related research.

論文提要內容：	II
Abstract：	III
表目錄	VI
圖目錄	VII
第一章 緒論	1
第一節	研究背景與動機	1
第二節	研究目的	2
第三節	研究流程	2
第二章 文獻探討	4
第一節 認知神經科學	4
第二節 科技接受模式	5
第三節 李克特量表	6
第四節 語意差異量表	7
第五節 大腦與腦波	8
第六節 事件相關電位(Event-Related Potentials, ERPs)	10
第七節 P300	12
第三章 研究方法	13
第一節	實驗設計	13
第二節	實驗對象	15
第三節	實驗流程	15
第四節  研究工具	17
第五節 資料蒐集與分析	20
第四章 資料分析	22
第一節	量表腦波分析	22
第二節	文理組於李克特量表之腦波分析	25
第三節	文理組於語意差異量表之腦波分析	29
第五章 結論與建議	32
第一節	研究結論	32
第二節	研究建議	33
參考文獻	34
一、	中文部分	34
二、	英文部分	35
附錄一：實驗量表問項設計	39
附錄二：實驗問卷李克特量表	41
附錄三：實驗問卷語意差異量表	43

表目錄
表2-1 左右腦功能說明	8
表2-2 大腦四大聯合區位置和功能	9
表2-3 腦波頻段說明表	10
表3-1 實驗情境分類	13
表3-2實驗硬體設備	17
表3-3 EPOC腦波訊號頻道對照大腦位置	19
表4-1 不同量表之P300	24
表4-2 量表事件相關電位P300 數據統計資料表	24
表4-3 量表事件相關電位P300數據U檢定表	25
表4-4 文理組學生於李克特量表之P300	27
表4-5 文理組學生於李克特量表事件相關電位P300 數據統計資料表	27
表4-6 李克特量表事件相關電位P300數據U檢定表	28
表4-7 文理組學生於語意差異量表之P300	30
表4-8 文理組學生於語意差異量表事件相關電位P300 數據統計資料表	31
表4-9 語意差異量表事件相關電位P300數據U檢定表	31

圖目錄
圖2-1 科技接受模式	5
圖2-2大腦構造圖	8
圖2-3 事件相關電位萃取技術	11
圖2-4  ERP成分波	11
圖3-1 李克特量表中文問項	14
圖3-2 語意差異量表中文問項	14
圖3-3 實驗流程圖	16
圖3-4 EPOC	18
圖3-5腦波訊號頻道對照圖	18
圖4-1 量表P300比較圖	23
圖4-2 文理組於李克特量表之各頻道腦波比較圖	26
圖4-3 文理組於語意差異量表之各頻道腦波比較圖	30

參考文獻
一、中文部分
1. 余伍洋、楊寬弘、陳明招，1994，聽覺誘發波在精神生理學之臨床意義。
2. 洪蘭，大腦的秘密檔案，2006，台北市：台灣東華。
3. 高木繁治，大腦構造地圖，2011，台北市：三悅出版。
4. 蕭文龍、黃莉君、楊雅雯，2016，神經資訊系統文獻彙整分析，東吳經濟商學學報，第九十二期：37~56頁。
5. 蕭夙婷、張瓊云，2009，從神經生理觀點探討幼兒注意力之表現，幼兒保育論壇，第四期：8~26頁。
6. 魏景漢 ，1995，事件相關電位（ ERP）研究發展，復旦神經生物學講座，第六期：127~134頁。
 
二、英文部分
1.Begleiter, H., Porjesz, B., Chou, C. L., & Aunon, J. I., 1983, “P3 and stimulus incentive value. Psychophysiology,” Vol. 20, No.1, pp. 95-101.
2.Celesia, G. G., & Brigell, M., 1992, “Event-related potentials,” Current Opinion in Neurology, Vol.5, No.5, pp.733-739.
3.Chen, J., Hung, T., Lin, J., Lo, L., Kao, J., Hung, C., Chen, Y., and Lai, Z., , 2005,  “Effects of anxiety on EEG coherence during dart throw,”  The 2005 World Congress of the International Society for Sport Psychology.
4.Chin, W. W., Johnson, N., & Schwarz, A., 2008, “A fast form approach to measuring technology acceptance and other constructs,” MIS Quarterly, pp.687-703. 
5.Courchesne, E., Hillyard, S. A., & Galambos, R., 1975, “Stimulus novelty, task relevance and the visual evoked potential in man”.
6.Davis, F. D., 1989, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,”  MIS quarterly, pp.319-340.
7.Davis, F. D., Bagozzi, R. P., & Warshaw, P. R., 1989,  “User acceptance of computer technology: a comparison of two theoretical models,”  Management science, Vol.35, No.8, pp.982-1003.
8.Eimer, M., 1998,  “Methodological issues in event-related brain potential research. Behavior Research Methods,” Instruments & Computers, Vol.30, No.1, pp.3-7.
9.Ford, J. M., Roth, W. T., & Kopell, B. S., 1976, “Auditory evoked potentials to unpredictable shifts in pitch,” Psychophysiology, Vol.13, No.1, pp.32-39.
10.Fishbein, M., & Ajzen, I., 1977, Belief, attitude, intention, and behavior: An introduction to theory and research, MA: Addison-Wesley.
11.Fitzgerald, P. G., & Picton, T. W., 1983, “Event-related potentials recorded during the discrimination of improbable stimuli,” Biological Psychology, Vol.17, No.4, pp. 241-276.
12.Gazzaniga, M. S., Ivry, R. B. & Mangun, G. R., 2002, “Cognitive Neuroscience: The biology of the mind (2nd ed.),” New York: W.W.Norton.
13.Himmelfarb, S., 1993, “The measurement of attitudes,” The psychology of attitudes, pp.23-87.
14.Kutas, M., McCarthy, G., & Donchin, E., 1977, “Augmenting mental chronometry: the P300 as a measure of stimulus evaluation time,” Science, Vol.197, No.4305, pp. 792-795.
15.Luck, S. J., Woodman, G. F., and Vogel E. K., 2000, “Event-related potential studies of attention,” Trends in Cognitive Sciences, Vol.4,  No.11, pp.432–440.
16.McCarthy, G., & Donchin, E., 1981, “A metric for thought: a comparison of P300 latency and reaction time,” Science, Vol.211, No.4477, pp.77-80.
17.Onton, J., Delorme, A., and Makeig, S., 2005, “Frontal midline EEG dynamics during working memory,” NeuroImage, Vol.27, pp. 341-356.
18.Pfurtscheller, G., and Klimesch, W., 1992, “Functional topography during a visuoverbal judgment task studied with event-related desynchronization mapping,” Journal of Clinical Neurophysiology, Vol.9, No.1, pp.120-131.
19.Preston, C. C., & Colman, A. M., 2000, “Optimal number of response categories in rating scales: reliability, validity, discriminating power, and respondent preferences,” Acta psychologica, Vol.104, No.1, pp.1-15.
20.Sauseng, P., Hoppe, J., Klimesch, W., Gerloff, C., and Hummel, F., 2007, “Dissociation of sustained attention from central executive functions: Local activity and interregional connectivity in the theta range,” European Journal of Neuroscience, Vol.25, pp.587-593.
21.Snyder, E., & Hillyard, S. A., 1976, “Long-latency evoked potentials to irrelevant,” deviant stimuli. Behavioral Biology, Vol.16, No.3, pp.319-331.
22.Squires, N. K., Squires, K. C., & Hillyard, S. A., 1975, “Two varieties of long-latency positive waves evoked by unpredictable auditory stimuli in man,” Electroencephalography and clinical neurophysiology, Vol.38, No.4, pp.387-401.
23.Sutton, S., Braren, M., Zubin, J., & John, E. R., 1965. “Evoked-potential correlates of stimulus uncertainty,” Science, Vol.150, No.3700, pp.1187-1188.
24.Verhagen, T., van Den Hooff, B., & Meents, S., 2015, “Toward a Better Use of the Semantic Differential in IS Research: An Integrative Framework of Suggested Action,” Journal of the Association for Information Systems, Vol.16, No.2, pp.108.