本研究藉由科技接受模式(technology acceptance model, TAM)來了解公部門數位學習網站，提出十六項假設，重新檢視數位學習平台的網站品質對公務人員是否影響其學習效果。本研究採用立意取樣方式進行問卷調查，請國家文官學院、地方行政研習中心中心與公務人力發展中心三個單位的負責人以推薦學員名單進行問卷填寫，樣本以最近在實體上課的學員，協助填答。問卷總共發放930份問卷，經回收樣本進行篩選後有效回收樣本，總計共計575份，有效回收率達62％。經由統計分析得到以下的結論，在結構方程模式(SEM)檢定假設部分，結果驗證軟體內容設計、軟體介面設計與專注力三個變數都會影響TAM模式，則認知易用性對認知有用性會受到公務人員是否有選擇與工作有關的課程，選擇有關工作的課程對於認知有用性就會愈高。在敘述性統計分析得知，公務人員對於軟體內容設計是重視「使用者控制」、「考慮學習者接受程度」、「學習動機引起好奇心」、「自主學習」、「目標性」與「多媒體影音」這幾個構面，而軟體介面設計則在意「系統穩定性」、「豐富的教材」、「多媒體影音」、「詞句需具有親和力」、「使用者控制」與「介面設計」這幾個要素，因此，政府未來可更用心於這幾個項目，讓公務人事行政體系所開發的數位學習網站愈來愈好。

Through TAM (technology acceptance model), this study is aimed to explore digital learning websites of publics sectors with 16 assumptions, in order to re-examine whether learning platforms affect the employees’ learning outcomes. It is a questionnaire-survey study adopting the judgement sampling method at the beginning, while inviting National Academy of Civil Service, Regional Civil Service Development Institute, and Civil Service Development Institute as the targets fulfilling the questionnaires. The return rate was 62% with 575 valid shares out of 930. The results showed that Software Content Design, Software Interface Design, and Concentration variables had influences on the TAM, whilst Perceived Ease of Use (PEU) were interacted with Perceived Usefulness (PU) based on the relevance between jobs and the courses they choose; and generally, selecting courses more related to their jobs resulting in higher PU values. Judging from the Descriptive Statistics analysis, public sector employees focused more on aspects such as user control, acceptance, motivation, self-learning, target, and media while considering Software Content Design, but being more concerned about system stability, context, media, clear & user-friendly tone and language, user control, and user interface while facing Software Interface Design issues. In sum, it is suggested by the results that paying more attention to items mentioned above might benefit the governmental policies, enabling digital learning platforms developed by the administrative departments of public sectors become more and more progressed in the current future.

一、中文文獻
E學中心(n.d.)。電子化政府線上數位學習應用現況前言。行政院人事行政局，2010年3月16日，取自http://elearning.rad.gov.tw/files/16-1000-285.php
旭聯科技(2002)。線上學習人口大有潛力，但滿意度仍有成長空間。旭連科技網站新聞稿，2009年11月29日，取自http://www.sun.net.tw/sn1.php?atype=3&no=136
行政院國科會(2002)。數位學習國家型科技計畫總體規劃書。數位學習國家型科技計畫網站。
余民寧(2002)。教育測驗與評量-成就測驗與教學評量。台北：心理出版社。
余泰魁、李能慧、吳桂森(2005)。金門觀光客旅遊行為意向實驗研究－線性結構模式之交叉效度驗證。觀光研究學報，11 (4)，355-384。
吳明隆、涂金堂(2008)。SPSS與統計應用分析。台北市：五南圖書出版股份有限公司。
李進寶(2005)。數位學習的發展與應用。資策會，2009年11月25日，取自http://140.111.130.21/scweb/stufile/files/0625李進寶投影片.ppt
李羅權(2008)。公部門數位學習發展策略與應用趨勢國際研討會。行政院人事行政局，2009年11月29日，取自http://www.cpa.gov.tw/ct.asp?xItem=2058&ctNode=233&mp=1
沈旭豐(2008)。以科技接受模式探討數位學習之學習滿意及購滿意意願。國立東華大學企業管理學系碩士在職專班碩士論文。
城忠志(2008)。公部門數位學習發展策略與應用趨勢國際研討會。行政院人事行政局，2009年11月29日，取自http://www.cpa.gov.tw/ct.asp?xItem=2058&ctNode=233&mp=1
施欣怡(2004)。消費者採用行動資訊服務行為之研究。台北大學企業管理所碩士論文。
原正彬(2004)。視覺障礙學生網路學習態度調查研究。雲林科技大學資訊管理系碩士班論文。
孫駿庭(2007)。數位閱讀較適呈現模式-以15至29歲為例。大同大學資訊經營研究所碩士論文。
財團法人資訊工業策進會(2006)。2005-2006數位學習。行政院國家科學委員會，數位學習國家型科技計畫辦公室，經濟部工業局。
財團法人資訊工業策進會(2008)。2008數位學習白皮書。行政院國家科學委員會，數位學習國家型科技計畫辦公室，經濟部工業局。
高翊群(2007)。行動導覽服務使用者接受模式分析-創新擴散之觀點。大同大學資訊經營研究所碩士論文。
莊雅茹(1993)。台灣學生電腦焦慮之探討。教育研究資訊，1(5)，114-127。
許靜月(2005)。訓練的利器—企業e-learning發展的隱憂與解決之道。游於藝雙月刊，54(5)。2009年11月29日，取自http://epaper.hrd.gov.tw/09_DEVELOP/09_05_monthly/number54/5.ASP?version=54
郭達沂(2003)。以科技接受模型探討失業勞工對公共職業訓練採用線上學習的使用意願。國立中正大學資訊管理研究所碩士論文。
陳怡真(2009)。科技接受模型應用於再購意願之研究。國立交通大學碩士在職專班經營管理組碩士論文。
陳明溥(1992)。CAI之發展趨勢：多媒體電腦輔助教學。資訊與教育，28，5-11。
陳彥勳(2008)。以科技接受模型探討影響企業員工使用數位學習系統之研究。國立中央大學企業管理研究所碩士論文。
陳清秀(2008)。公部門數位學習發展策略與應用趨勢國際研討會。行政院人事行政局，2009年11月29日，取自http://www.cpa.gov.tw/ct.asp?xItem=2058&ctNode=233&mp=1
湯惠誠(1994)。高雄市高中學生電腦態度及其相關因素之研究。國立高雄師範大學工業科技教育研究所碩士論文。
黃竹韻(2009)。公部門員工網路學習參與意願與障礙之研究-以台北市政府為例。生活科技教育月刊，42(1)，67-95。
數位教育研究所(n.d.)。數位學習中心。資訊工業策進會，2009年11月29日，取自http://60.199.205.230/elearning/
蔡佩珊(2001)。E-learning成長不如預期，企業投資趨緩。ZDNet，2009月11月11日。取自http://www.zdnet.com.tw/news/hardware/0,2000085676,11014691,00.htm
薛義誠(2008)。公部門數位學習發展策略與應用趨勢國際研討會。行政院人事行政局，2009年11月29日，取自http://www.cpa.gov.tw/ct.asp?xItem=2058&ctNode=233&mp=1

二、英文文獻
Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361-391.
Ajzen, I. (1985). From intention to actions: A theory of planned behavior. NY: Springer Verlag, 11-39.
Ajzen, I. (1988). Attitudes, personality and behavior. Chicago: Dorsey Press. 112-150.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.
ASTD. (2001). E-learning glossary. Retrieved November 20, 2009, from http://www.learningcircuits.org/glossary.html
ASTD. (2005). Usability in E-Learning. Retrieved November 20, 2009, from http://www.astd.org/LC/2005
ASTD. (2007). Learning circuits glossary. Retrieved November 20, 2009, from http://www.learningcircuits.org/glossary
Bagozzi, R. P., & Yi, Y. (1988). On the Evaluation of Structural Equation Models, Academy of Marking Science, 16, 76-94.
Belisle, M. J. (2007). Temporal behavior of Taylor-Couette flow sinusoidally modulated about a zero mean. Paper presented at the AIAA Region VI Student Conference, Seattle, Washington.
Bersin & Associates. (2003). Blended learning: what works TM. Retrieved November 25, 2009, from http://www.tjtaylor.net/Research/Blended%20Learning%20-%20What%20works.pdf
Brandon Hall Research. (2001). Learning context management systems. Retrieved November 20, 2009, from http://www.brandon-hall.com.
Brvan, N., Kirakowski, J., & Maisse, J. (1991) What is usability , Proceedings of the 4th International Conference on HCI, Stuttgart.
Campbell, N. J., & Perry, K. M. (1988). Sex and ethnic group differences in high school students' computer attitudes and computer attributions. San Francisco: ERIC. 1-20.
Colly, A. M. (1994). Effects of gender role identity and experience on computer attitude componetos. Journal of Educational Computing Research, 10(2), 129-137.
Connolly, T., Stansfield, M., & Hainey, T. (2009). Towards the development of a games-based learning evaluation framework.. NY: IGI Global, 251-273.
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information system: Theory and results. Ph.D. Dissertation, MIT Sloan School of management, Cambrige, MA.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1002.
Delcourt, M. A., & Kinzie, M. B. (1993). Computer technologies in teacher education: The measurement of attitudes and self-efficacy. Journal of research & Development, 27(1), 35-41.
Drago, W., & Wagner, R. (2004). VARK preferred learning styles and online education. J Management Research News, 27(7), 1-13.
Elena, K., & Detmar, W. S. (1999). The psychological origins of perceived usefulness and ease-of-use. Information & Management, 35, 237-250.
ESA. (n.d.). Digital economy. Retrieved November 29, 2009, from http://www.esa.doc.gov/reports.cfm
Fang, X., Chan, S., Brzezinski, J., & Xu, S. (2006). Moderating effects of task type on　wireless technology acceptance. Journal of Management Information Systems, 22(3), 123-157.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Journal of Leisure research, 27(1), 61-84.
Fox, G. (1998). The internet: Making it work in the ESL classroom. The Internet TESL Journal, 4 (9). Retrieved November 27, 2009, from http://www.aitech.ac/jp/~iteslj/Articles/Fox-Internet.html
Gaide, S. (2005). Serving the post-modern student: personalization is central. Distance Education, 9(12), 1-6.
Ha, I., Yoon, Y., & Choi, M. (2008). Determinants of adoption of mobile games under mobile broadband wireless access environment. Information & Management, 44(3), 276-286.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate Data Analysis (5th Ed.). NY: Prentice Hall International.
Hasan, B. (2006). Delineating the effects of general and system-specific computer self-efficacy beliefs on IS acceptance. Information & Management, 43(5), 565-571.
Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695-704.
Huang, M. H. (2005). Web performance scale. Information & Management, 42(6), 841-852.
Hung, S. Y., Ku, C. Y., & Chang, C. M. (2003). Critical factors of WAP services adoption: An empirical study. Electronic Commerce Research and Applications, 2(1), 46-60.
Igbaria, M., Iivari, J., & Maragahh, H. (1995). Why do individuals use computer technology? A Finnish case study. Information and Management, 29(5), 227-238.
Johnson, R. D., Hornik, S., & Salas, E. (2008). An empirical examination of factors contributing to the creation of successful e-learning environments. Human-Computer Studies, 66, 356-369.
Katz, Y. J., & Yablon, Y. B. (2002). Who is afraid of university internet courses? Educational Media International, 39(1), 69-73.
Khalifa, M., & Cheng, S. (2002). Adoption of mobile commerce: Role of exposure. Proceedings of the 35th Hawaii InternationalConference on System Sciences, Institute of Electrical and Electronics engineers, Hawaii.
Khan, B. H. (2001). A Framework for E-learning, Retrieved November 20, 2009, from http://www.bookstoread.com/framework/
Kim, B. G., Soon, C. P., & Lee, K. J. (2007). A structural equation modeling of the internet acceptance in korea. Electronic Commerce Research and Applications, 6(4), 425-432.
Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behaviour. Information Systems Research, 13(2), 205-223.
Lederer, A. L., Maupin, D., Sena, M. P., & Zhuang, Y. (2000). The technology acceptance model and the World Wide Web. Decision Support System, 29(3), 269-285.
Lee, D., & Huang, N. (2004). The effect and efficiency of digital content format in elearning. Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2004, 797-803.
Lee, J. (2007). Transfer effect in national price levels. NY: Springer Verlag, 534-556.
Lern(Learning Resources Network)(1998). Online education: Growing presence and growing pains, Life long Learning Today, 6(1), 6-7.
Li, H., Kuo, C., & Russell, M. G. (1999). The impact of perceived channel utilities, shopping orientations, and demographics on the consumer's online buying behavior. Journal of Computer-Mediated Communication, 5(2), 1-20.
Li, W. C. (2007). The effect of motion analysis model in computer assist instruction(CAI) for teachers of special education classes in teaching orientation and mobility skills for blind and visually impaired students. Paper presented at the 2007 International Conference on ICT in Teaching and Learning, Hong Kong, China.
Liao, Y. C. (1998). Effects of hypermedia versus traditional instruction on students’ attitude on achievement: A meta-analysis. Journal of Research on Computing in Education, 30 (4), 341-359.
Liaw, S. S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers & Education, 51, 864-873.
Lin, J., & Lu, H. P. (2000). Towards an understanding of the behavioural intention to use a websit. International Journal of Information Management, 20(3), 197-208.
Liu, S. H., Liao, H. L., & Pratt, J. A. (2009). Impact of media richness and flow on e-learning technology acceptance. Computers & Education, 52, 599-607.
Loyd, B. C., & Gressard, C. (1984). Reliability and factorial validity of computer attitude scale. Educational and Psychological Measurement, 44(2), 501-505.
Lu, J., Yu, C. S., & Liu, C. (2003). Learning style, learning patterns, and learning performances in WebCT-based MIS course. Information & Management, 40(6), 497-507.
Luo, W., & Strong, D. (2000). Perceived critical mass effect on groupware acceptance. European Journal of Information System, 9(2), 91-103.
Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a world-wide-web context. Information & Management, 38(4), 217-230.
Moore, M. G., Cookson, P., & Donaldson, J. (1990). Contemporary issues in american distance education. NY: Pregamom Press, 163-171.
Nielsen, J. (1993). Usability engineering. San Diego, Academic Press.
Patrick, Y. K. (1996). An Empirical Assessment of a Modified Technology Acceptance Model. Journal of Management Information Systems, 13(2), 185-204.
Powell, T. A.(2000). Web Design: The Complete Reference. McGraw-Hill, Berkeley, C. A.
Priest. G. (2002). Learn fast, go fast. Retrieved November 20, 2009, from http://www.internettime.com/itimegroup/more.htm
Reisetter, M., Lapointe, L., & Korcuska, J. (2007). The impact of altered realities: Implications of online delivery for learners’interactions, expectations, and learning skills. International Journal on E-Learning, 6(1), 55-80.
Robey, D. (1979). User Attitudes and Management Information System Use. Academy of Management Journal, 22(3), 527-538.
Roca, J. C., & Gagne, M. (2007). Understanding e-learning continuance intention in the workplace: A self-determination theory perspective. Computers in Human Behavior, 24, 1585-1604.
Rosenberg, M. J. (2001). E-learning: Strategies for delivering knowledge in the digital age. NY: McGraw-Hill.
Seng, L. C., & Al-Hawamdeh, S. (2001). New mode of course delivery for virtual classroom. Aslib Proceedings: New Information Perspectives, 53(6), 238-242.
Seyal, A. H., Rahman, M. N., & Rahim, M. M. (2002). Determinants of academic use of the internet: A structural equation model. Behaviour and Information Technology, 21(1), 71-86.
Shashaani, L. (1994). Gender differences in computer experience and its influence on computer attitudes. Jorunal of Educaional Computing Research, 11(4), 347-367.
Sun, P. C., & Cheng, H. K. (2005). The design of instructional multimedia in e-learning: A media richness theory-based approach. Computers & Education, 49(3), 662-676.
Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92.
Taylor, S., & Todd, P. (1995a). Understanding information technolgy: a test of competing models. Information Systems Research, 6(2), 44-176.
Varank, I. (2007). Effectiveness of quantitative skill, qualitative skills, and gender in determining computer skills and attitudes: A causal analysis. The clearing House, 81(2), 71-80.
Venkatesh, V., & Davis, F. D. (1996). A critical assessment of potential measurement biases in the TAM: Three experiments. Human-Computer Studies 45(1), 19-45.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision Sciences, 33(2), 297-316.
Wan, Z., Wang. Y., & Haggerty, N. (2008). Why people benefit from e-learning differently: The effects of psychological processes on e-learning outcomes. Information & Management, 45, 513-521.
Woodrow, J. E. (1994). A comparison of four computer attitudes scale. Journal of Educational computing Research, 1(5), 114-127.
WR Hambrecht +Co. (2000). Corporate e-learning: Exploring a new frontier. Retrieved October 25, 2009, from http://www.astd.org/NR/rdonlyres/hambrecht.pdf
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? an empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719-729.
Yu, J., Ha, I., Chio, M., & Rho, J. (2005). Extending the TAM for t-commerce. Information & Management, 42(7), 965-976.
Yuen, A. H. K., & Ma, W. W. K. (2008). Exploring teacher acceptance of e-learning technology. Asia-Pacific Journal of Teacher Education, 36(3), 229-243.