研究生: |
洪久琇 Hung, Chiu-Hsiu |
---|---|
論文名稱: |
以整合性科技接受模式探討員工使用微課程進行教育訓練之行為研究 A Study on the Behavior of Employees under Microlecture Training Using the UTAUT Model |
指導教授: |
林坤誼
Lin, Kuen-Yi 蕭顯勝 Hsiao, Hsien-Sheng |
學位類別: |
碩士 Master |
系所名稱: |
科技應用與人力資源發展學系 Department of Technology Application and Human Resource Development |
論文出版年: | 2017 |
畢業學年度: | 105 |
語文別: | 中文 |
論文頁數: | 111 |
中文關鍵詞: | 整合性科技接受模式 、結構方程模型 、微課程 |
英文關鍵詞: | UTAUT, SEM, microlecture |
DOI URL: | https://doi.org/10.6345/NTNU202202914 |
論文種類: | 學術論文 |
相關次數: | 點閱:250 下載:22 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
「知識經濟」時代的來臨,企業須隨時掌握新知,培育人才,方能因應急遽變化的環境與挑戰,在高度激烈競爭的市場中立於不敗之地。個案公司運用通訊網路設備及雲端運算技術,透過整合通訊平台線上會議功能進行授課互動,規劃出一種創新的教學模式—微課程,期能跨越實體課程與數位學習平台的限制,激發同仁自主而有效率地學習,在影響工作最小的情況下,快速獲取新知。本研究旨在以整合性科技接受模式的研究架構為理論基礎,探討績效期望、努力期望、社會影響及促成條件等構面對個案公司員工參加微課程之行為意圖及使用行為之影響。本研究透過立意抽樣方式,採問卷調查法,以個案公司參加「資訊類」微課程的學員為研究對象,問卷共發放508份,回收有效問卷224份,並以SPSS軟體進行描述性統計分析、項目分析、因素分析、信度分析、獨立樣本t檢定及變異數分析,另以AMOS軟體進行結構方程模型 (SEM)分析。研究結論:(1)員工參加微課程的行為意圖會受到績效期望與努力期望的顯著影響;(2)員工參加微課程的使用行為不會受到促成條件及行為意圖的顯著影響;(3)績效期望與社會影響對行為意圖的影響力,皆會因年齡及職務的不同而有差異。
With the era of knowledge economy coming, enterprises must keep abreast of new knowledge and develop talents to meet the rapidly changing environment in order to keep the leading position in a highly competitive market. The company in this case study uses network equipment and cloud computing technology to conduct interactive teaching through the online conferencing function of the Unified Communications (UC). They created an innovative teaching model - microlecture, which breaks the limitation of both physical and digital learning (E-Learning) platforms, and stimulates employees to learn independently and efficiently. With the aid of microlecture, employees can acquire new knowledge with a minimal impact on their regular jobs. This study is based on the research framework of Unified Theory of Acceptance and Use of Technology (UTAUT). The goal is to investigate how the factors of "performance expectancy (PE)", "effort expectancy (EE)", "social impact (SI)", and "facilitation conditions (FC)" influence the employees' participation in microlectures, focusing on the aspects of employees’ "behavior intention (BI)" and "use behavior". Purposive sampling method was used in questionnaire survey. A total of 508 questionnaires were distributed to the students participated in the information related microlectures, and 224 valid questionnaires were collected. SPSS was used to conduct descriptive statistics analysis, item analysis, factor analysis, reliability analysis, Independent-Samples t Test, and Analysis of variance. The structural equation modeling (SEM) analysis was carried out by AMOS. The results show that: (1) Both Performance Expectancy and Effort Expectancy have significant influences on employees’ Behavior Intention to participate in the microlecture; (2) Neither Facilitating Conditions nor Behavior Intention has a significant influence on employees’ Use Behavior to participate in the microlecture; (3) Both the effects of "Performance Expectancy on the Behavior Intention" and "Social Influence on the Behavior Intention" vary by ages and job positions.
一、中文部份
吳明隆(2010)。結構方程模式:AMOS 的操作與運用。台北:五南。
吳明隆(2013)。SPSS 統計應用學習實務:問卷分析與應用統計(3 版)。新北市:易習圖書。
林光龍(2015)。遇見微課程教學創新應用。未出版之原始資料。
邱成欽、林弘昌(2010)。影響企業員工使用數位學習意願之相關因素探討。生活科技教育,43(5),9-26。
邱皓政(2000)。量化研究與統計分析-SPSS中文視窗版資料分析範例解析。台北市:五南。
邱竣麟(2008)。以UTAUT探討數位學習系統使用行為之研究(未出版之碩士論文)。大葉大學資訊管理學系,彰化縣。
施學琦、陳怡蓁(2010年5月)。以UTAUT架構探討社群網站使用者的使用行為。「第11屆電子化企業經營管理理論暨實務研討會」發表之論文,彰化縣大葉大學。
孫思源、羅月秀、趙珮如、吳章瑤(2008)。人力資源招募網站使用意向影響因素之探討。人力資源管理學報,8(3),1-23。
高瑜璟(2006)。數位學習-學習的新趨勢。網路社會學通訊期刊,57。取自http://www.nhu.edu.tw/~society/e-j/57/57-22.htm
張偉豪(2011)。SEM 論文寫作不求人。台北:鼎茂。
張偉豪、鄭時宜(2013)。與結構方程模型共舞:曙光乍現。台北:前程。
梁定澎(2012)。資訊管理理論。 新北市 : 前程文化出版總經銷。
梁樂明、曹俏俏、張寶輝(2013)。微课程设计模式研究——基于国内外微课程的对比分析。開放教育研究,19(1),65-73。
陳寬裕、王正華(2010)。論文統計實務SPSS 與 AMOS的運用。台北:五南。
粟四維、莊友豪(2009)。Wiki使用者與使用行為之研究。電子商務學報,11(1),185-212。
黃仁男(2013)。以整合性科技接受模式探討警察人員學科常訓導入數位學習使用意圖之研究-以雲林縣警察局為例(未出版之碩士論文)。南華大學文化創意事業管理學系,嘉義縣。
游光昭、李大偉(2003)。網路化教育訓練概論。台北:師大書苑。
榮泰生(2011)。AMOS與研究方法。台北:五南。
廖珮妏(2011)。企業導入數位學習之創新擴散通用模型與整合型科技接受模式的多層次分析(未出版之博士論文)。國立臺灣師範大學科技應用與人力資源發展學系,台北市。
廖珮妏、余鑑、于俊傑(2012)。應用整合型科技接受模式與創新擴散通用模型於企業導入數位學習之多層次分析。電子商務學報, 14(4),657-687。
葉千華(2016)。應用整合性科技接受使用模式探討行車紀錄器使用行為之研究(未出版之博士論文)。國立高雄應用科技大學,高雄市。
蔡明月、張淑娟(2015)。電子書閱讀器借閱服務之使用研究:以交通大學圖書館為例。大學圖書館,19(2),1-21。
鍾秀英(2015)。公務人員使用政府數位學習意向的影響因素之探討(未出版之博士論文)。國立臺灣科技大學管理研究所,台北市。
謝琪文(2013)。以整合性科技接受模式探討教師利用網路社群進行教師專業發展之研究(未出版之博士論文)。臺北市立大學,臺北市。
蕭文龍、李逸婕、曾子珊(2012)。整合性科技接受模式之彙總分析:以教育為例。第八屆知識社群國際研討會論文集(952-961頁)。台北市。
蘇照雅、陳怡穎(2005)。數位學習導入企業組織之探討。生活科技教育,38(7),26-36。
二、外文部份
AbuShanab, E., & Pearson, J. M. (2007). Internet banking in Jordan: The unified theory of acceptance and use of technology (UTAUT) perspective. Journal of Systems and Information Technology, 9(1), 78-97.
Ajzen, I. (1985). From intention to actions: A theory of planned behavior. In J. Kuhl and J. Bechmann (Eds.), Action-control: From cognition to behavior (pp. 11-39). Heidelberg: Springer.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179 -211.
Anderson J.C., & Gerbing, D.W. (1988). Structural equation modeling in practice: a review and recommended two-step approach, Psychological Bulletin. 103, 453-460.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
Barua, M. (2012). E-governance adoption in government organization of India. International Journal of Managing Public Sector Information and Communication Technologies, 3(1), 1-20.
Bollen, K.A. (1989). Structural equations with latent variables. New York: Wiley.
Byrne, B. B. (2010). Structural equation modeling using AMOS. Basic concepts, applications, and programming (2nd Ed). New York: Routledge.
Castaeda, J. A., MuozLeiva, F., & Luque, T. (2007). Web acceptance model (WAM): Moderating effects of user experience. Information & Management, 44(4), 384-396.
Chiemeke, S. C., & Evwiekpaefe, A. E. (2011). A conceptual framework of a modified unified theory of acceptance and use of technology (UTAUT) Model with Nigerian factors in E-commerce adoption. Educational Research, 2(12), 1719-1726.
Chiu, C. M., & Wang, E. T. (2008). Understanding web-based learning continuance intention: The role of subjective task value. Information & Management, 45(3), 194-201.
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), 982-1003.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.
DeVellis, R. F. (1991). Scale development theory and applications. London: SAGE.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Boston, MA: Addison-Wesiey.
Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate data analysis. NJ:Person Prentice Hall.
Hair, J. F. Jr., R. E. Anderson, R, L. Tatham, & W. C. Black (2009). Multivariate data analysis. 7th ed., Englewood Cliffs, NJ:Prentice Hall.
Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate data analysis:A global perspective. NJ:Person Prentice Hall.
Hartwick, J., & Barki, H. (1994), "Explaining the role of user participation in information system use." Management Science, 40(4), 440-465.
Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853-868.
Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36.
Kelley, T. L.(1939).The selection of upper and lower groups for the validation of test item, Educational Psychology, 30, 17-24
Kenny, D.A. (2006). Series editor’s note. In T. A. Brown (Ed.), Confirmatory factor analysis for applied research. New York: Guilford. Ix-x.
Kline, R. B. (2005). Principles and Practice of Structural Equation Modeling (2nd ed.). New York, NY: Guilford Press.
Krejcie, R.V., & Morgan, D.W. (1970) Determining sample size for research activities. Educational and Psychological Measurements, 30, 607-610.
Kuo, Y. F., & Yen, S. N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior, 25(1), 103-110.
Mardia, K. V. (1985). Mardia’s test of multinormality. Encyclopedia of statistical sciences, New York: Wiley, 217-221
Moore. G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.
Nicholas, D., Rowlands, I., Clark, D., Huntington, P., Jamali, H. R., & Ollé, C. (2008). UK scholarly e-book usage: A landmark survey. Aslib Proceedings, 60(4), 311-334. doi: 10.1108/00012530810887962
Rogers, E. (1983). Diffusion of innovations. New York: Free Press.
Santos-Feliscuzo, L. T., & Himang, C. M. (2011). Library periodical indexing software evaluation using Unified Theory of Acceptance and Use of Technology. Procedia Social and Behavioral Sciences, 25(2011), 104-114. doi: 10.1016/j.sbspro.2011.10.532
Schumacker, Randall E., & Lomax, Richard G. (2004). A beginner’s guide to structural equation modeling(2nd ed.). Mahwah, NJ:Lawrence Erlbaum Associate
SPSS. (2008). SPSS 17. Brief Guide. Chicago: Author.
Taylor, S., & Todd, P. A. (1995a). Decomposition and cross effects in the theory of planned behavior: A study of consumer adoptios.n intentions. International Journal of Research in Marketing, 12(2), 137-155.
Taylor, S., & Todd, P. A. (1995b). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124-143.
Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications. Washington, DC:American Psychological Association.
Van Dijk, J. A., Peters, O., & Ebbers, W. (2008). Explaining the acceptance and use of government Internet services: A multivariate analysis of 2006 survey data in the Netherlands. Government Information Quarterly, 25(3), 379-399.
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., Morris, M. G., Gordon, B. D., & Davis F. D. (2003). “User acceptance of information technology: Toward a unified view.” MIS Quarterly, 27(3), 425-478.
Wang, C. H., Liu, W. L., Tseng, M. C., & Tsai, H. S. (2010). A study of taiwanese college teachers' acceptance of distance learning. International Journal of Organizational Innovation (Online), 3(2), 243-261.
Wang, Y. S., Wu, M. C., & Wang, H. Y. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology, 40(1), 92-118.
Zhao, F., & Khan, M. S. (2013). An empirical study of e-government service adoption: culture and behavioral intention. International Journal of Public Administration, 36(10), 710-722.