臺灣博碩士論文加值系統

資訊科技對於大多數的學生能夠促進學習過程。而許多學生對於Lego NXT很感興趣，針對大學生已經有許多相關的研究，但是卻沒有小學生群的科技接受模式之研究。這篇研究的目的是在於此研究中評估學生Lego NXT的接受度來預測其意向、提出解釋以及改善TAM的運用模式。研究者試著從樂高NXT的自我效能、主觀規範、並促進條件的三個因素下，討論TAM的模型。然而，小學生在主觀規範及知覺易用性與知覺有用性之間的相關性的結果顯示為不顯著，故可以被認為對於小學生易用性較有用性更為重要。此份研究之貢獻則在於TAM的理論有效以及在教育上能確實被接受。

Information technology can promote the learning process for most students. Many students have interested in Lego NXTs. For Undergraduates already have a number of related research. But there was not studied the acceptance of the technology by the elementary school student populations. The purpose of the study is to evaluate students’ acceptance of Lego NXT as a intention to forecast, explain, and improve application patterns of TAM in surveys. The researcher attempt from three factors of the Lego NXT Self Efficacy, Subjective Norm, and Facilitating Conditions, to discussion the TAM model. However, students in the subjective norms, and perceived ease of use and perceived usefulness of the correlation between the results as not significant, it can be considered more useful for students ease of use is more important. The study contributes to TAM’s theoretical effective and indeed available in education.

Contents
Publications
Ackowledgements
中文摘要 I
Abstract II
Contents III
List of Figures V
List of Tables VI
CHAPTER 1: INTRODUCTION 1
Research Questions 2
Significance of the Study 2
CHAPTER 2: LITERATURE REVIEW 4
Lego NXT System 5
The Adoption of Technological Innovations 5
About the History of Technology Acceptance Models 6
The Technology Acceptance Model 8
CHAPTER 3: RESEARCH DESIGN 11
Related Valuables 12
Lego NXT Self Efficacy (SE) 13
Subjective Norm(SN) 13
Facilitating Conditions(FC) 13
Perceived usefulness(PU) and perceived ease of use(PEOU) 14
Attitude toward using (ATU) 14
Behavioral Intention to Use (BITU) 14
Sample Size 14
Survey Questions 15
CHAPTER 4: DATA ANALYSIS 17
Data Validation 17
PLS analysis 25
Measurement model reliability analysis 17
Validity of measurement model 20
The overall model fitness and verification 22
Hypothesis testing Conclusion 25
CHAPTER 5: DISSCUSSION & CONCLUSIONS 26
Discussion 26
Conclusions 30
REFERENCES 33

1. Bih-Yaw Shih (2006). The Research of the Development of an On-line English Reading Environment and Acceptance Evaluation. Journal of National Pingtung University of Education, Volume24, 521-554 (date accessed 4/12/2005)
2.LeJOS, (2009), Java for LEGO Mindstorms, http://lejos.sourceforge.net/ (date accessed 14/01/2010).
3.Blue, J, (2009), BlueJ – The interactive Java environment, http://www.bluej.org/ (date accessed 14/01/2010).
4.Mohammad Chuttur,(2009), Overview of the Technology Acceptance Model: Origins, Developments and Future Directions.
5.Gerardo Oliveira1, Ricardo Silva1, Tiago Lira1, Luis Paulo Reis (July 2009), “Environment Mapping using the Lego Mindstorms NXT and leJOS NXJ”,
6.Michael W. Lew, Thomas B. Horton, Mark S. Sherriff,(2009), Using LEGO MINDSTORMS NXT and LEJOS in an Advanced Software Engineering Course.
7.Adam Pilat, Andrew J. Kornecki, Jean-Marc Thiriet, Wojciech Grega1, Ondrej Rysavy,(2009), Inter-university Project Based on LEGO NXT.
8. Andreas Nüchter, “3D Robotic Mapping: The Simultaneous Localization and Mapping Problem with Six Degrees of Freedom”, Springer, 1st edition, 2009 January 22
9.Wojciech Grega et. Al.,(2008), Real-time Control Teaching Using LEGO® MINDSTORMS® NXT Robot.
10.Sung Youl Park,(2009), An Analysis of the Technology Acceptance Model in Understanding University Students’ Behavioral Intention to Use e-Learning.
11.Juan Antonio Breña Moral,(2008) “Develop leJOS Programs Step by Step”, Version 0.4, July 2008
12.Jen-Her Wu, Wen-Shen Shen, Li-min Lin, Roberta. Greenes and David w. Bates,(2008), Testing the technology acceptance modelfor evaluating healthcare professionals’ intention to use an adverse event reporting system, International Journal for Quality in Health Care 2008; Volume 20, Number 2: pp. 123–129
13.Leila Halawi, Richard McCarthy,(2008), measuring students perceptions of blackboard using the technology acceptance model: a pls approach.
14. Olusegun Folorunso and Shawn Oluwafemi Ogunseye,(2008), applying an enhanced technology acceptance model to knowledge management in agricultural extension services, Data Science Journal, Volume 7, 22 March 2008.
15.Klassner, F., and Continanza, C. (2007). without robotics: an alternative to simulations in systems courses. Paper presented at the proceedings of the 38th SIGCSE Technical Symposium on Computer Science Education, March 7-1-, in Covington, KY, USA.
16.Burhans, D. (2007). A robotics introduction to computer science. Paper presented at the AAAI spring symposium, March 26-28, in Stanford, California, USA.
17.Cliburn, D. (2006). Experiences with the Lego TM through the undergraduate computer science curriculum. Paper presented at the 36th ASEE/IEEE Frontiers in Education conference, October 28-31, 2006, in San Diego, California, USA.
18.Bagnall, Brian. (2007), Maximum Lego NXT. Winnipeg, Manitoba: Variant Press.
19.Anderson, J. E., and Schwager, P. H. (2006). The Tablet PC: Applying the UTAUT Model, 20.Paper presented at the American Conference on Information Systems, Acapulco, Mexico.
Apple Newton. (2006). Retrieved February 9, 2006, from http://en/wikipedia.org/wiki/
Apple Newton
21.Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.
22.Bandura A. (1977) Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall.
23.Bandura A. (1986) Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice Hall.
24.Bandura, A. (2002). Social Cognitive Theory in Cultural Context: An International Review. Journal of Applied Psychology, 51, 269-290.
25.Carlsson, C., Carlsson, J., Hyvönen, K., Puhakainen, J., & Walden, P. (2006). Adoption of Mobile Devices/Services — Searching for Answers with the UTAUT. Paper presented at the 39th Annual Hawaii International Conference on System Sciences (HICSS''06).
26.Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study. Information Systems Research, 14(2), 189 - 217.
27. Straub, D. W., Boudreau, M., & Gefen, D.(2004). Validation guidelines for IS positivist research. Communications of the Association for Information Systems, 14, 380-426.
28.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.
29.Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
30. Straub, D. W., Boudreau, M., & Gefen, D. (2004). Validation guidelines for IS positivist research. Communications of the Association for Information Systems, 14, 380-426.
31.Fornell, C., and Bookstein, F. L. “Two Structural Equation Models: LISREL and PLS Applied to Consumer Exit-Voice Theory.” Journal of Marketing Research, Volume 19, 1982, pp. 440-452.
32.Gall, M. D., Gall, J. P., & Borg, W. R. (2003). Educational research: An introduction (7th ed.). Boston: Pearson Education, Inc.
33.Garfield, M. J. (2005). Acceptance of Ubiquitous Computing. Information Systems Management, 22(4), 24-31.
34.Garrison, G. (2005). A Model of Factors Impacting an Organizations Propensity to be an Early Adopter of Disruptive Technology. Doctoral Dissertation, University of Mississippi. (UMI No. 3190561).
35.Gefen, D., & Straub, D. (2005). A Practical Guide to Factorial Validity Using PLS-Graph: Tutorial and Annotated Example. Communications of the Association for Information Systems, 16, 91-109.
36.Groves, M. M., & Zemel, P. C. (2000). Instructional Technology Adoption in Higher Education: An Action Research Case Study. International Journal of Instructional Media, 27(1), 57-65.
37.Haenlein, M., & Kaplan, A. (2004). A Beginners Guide to Partial Least Squares Analysis. Understanding Statistics, 3(4), 283-297.
38.Henderson, T., Kotz, D., & Abyzov, I. (2004). The Changing Usage of a Mature Campus-wide Wireless Network. Paper presented at the ACM MobiCom 2004, Philadelphia, PA.
39.Hoffman, B. (2006). Web Survey Design. Retrieved May 23, 2006, from http://coe.sdsu.edu/eet/articles/websurvey/
40.Jarvis, C. B., MacKenzie, S. B., & Podsakoff, P. M. (2003). A Critical Review of 41.Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research. Journal of Consumer Research, 30, 199-218.
42.Legris, P., Ingham, J., & Collerette, P. (2003). Why do People Use Information Technology? Critical Review of the Technology Acceptance Model. Information and Management, 40, 191-204.
43. Gerardo Oliveira, Ricardo Silva, Tiago Lira, Luis Paulo Reis (2009). Environment Mapping using the Lego Mindstorms NXT and leJOS NXJ.
44. Michael W. Lew, Thomas B. Horton, Mark S. Sherriff (2009). Using LEGO MINDSTORMS NXT and LEJOS in an Advanced Software Engineering Course.
45. Elizabeth A. Gandy (2010). the use of lego mindstorms nxt robots in the teaching of introductory java programming to undergraduate students.
46.Pijpers, G. (2001). Executives'' Use of Information Technology: An Examination of Factors Influencing Managerial Beliefs, Attitude and Use of Information Technology. Information and Software Technology, 43(15), 959-971.
47.Plouffe, C. R., Hulland, J. S., & Vandenbosch, M. (2001). Research Report: Richness Versus Parsimony in Modeling Technology Adoption Decisions -- Understanding Merchant Adoption of a Smart Card-Based Payment Systems. Information Systems Research, 12(2), 208-222.
48.Ray, J. (2002). SAGE Cold-War Forerunner to the Information Age. Retrieved February 11, 2006, from http://www.eskimo.com/~wow-ray/sage28.html
49.Rawstorne, P., Jayasuriya, R., & Caputi, P. (2000). An Integrative Model of Information Systems use in Mandatory Environments. Paper presented at the Proceedings of the twenty first international conference on Information systems.
50.Schmidt, J. (2000). DSU Ranks Again, Third Year In A Row. Retrieved March 19, 2006, from http://www.departments.dsu.edu/news/spotlight/00/dsu_ranks_again.htm
51.Shandish, W., Cook, T., & Campbell, D. (2002). Experimental and Quasi-Experimental Design for Generalized Causal Inference. Boston, MA: Houghton Mifflin.
52Singleton, R. A., & Straits, B. C. (2004). Approaches to Social Research (Fourth ed.). Oxford, England: Oxford University Press.
53.Straub, D. (1989). Validating Instruments in MIS Research. MIS Quarterly, 13(2), 146-169.
54.Straub, D., Boudreau, M.-C., & Gefen, D. (2004). Validation Guidelines for IS Positivist Research. Communications of the Association for Information Systems, 13, 380-247.
55.Singletary, L., Akbulut, A., & Houston, A. (2002, August 9-11). Innovative Software Use After Mandatory Adoption. Paper presented at the Proceedings of the Americas Conference on Information Systems (AMCIS), Dallas Texas.
56.Taylor, S., & Todd, P. (2001). Understanding Information Technology Usage: A Test of Competing Models. Information Research, 6(2), 144-176.
57.Vallerand, R. J. (1997). Toward a Hierarchical Model of Intrinsic and Extrinsic Motivation. New York: Academic Press.
58.Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204.
59.Venkatesh, V., & Morris, M. (2000). Why Don''t Men Ever Stop to Ask For Directions? Gender Social Influence, and Their Role in Technology Acceptance and Usage Behavior. MIS Quarterly, 24(2), 115-139.
60.Venkatesh, V., Morris, M., Davis, G., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478.
61. Elizabeth A. Gandy,(2010), The use of LEGO MINDSTORMS NXT robots in the teaching of introductory JAVA programming to undergraduate students.
62.Zhang, P., Li, N., & Sun, H. (2006, January). Affective Quality and Cognitive Absorption: Extending Technology Acceptance Research. Paper presented at the Hawaii International Conference on System Sciences, Kauai, Hawaii.
63.Bagnall, Brian. Maximum Lego NXT. Winnipeg, Manitoba: Variant Press, (2007).
64.Burhans, D. (2007). A robotics introduction to computer science. Paper presented at the AAAI spring symposium, March 26-28, in Stanford, California, USA.
65.Burhans, D., Meyer, R., VanVerth, P., Puehn, D., Steck, V., & Wiejaczka, J. (2006). Introductory computer science with robots. Paper presented at the proceedings of the 21st National Conference on Artificial Intelligence, July 16-20, in Boston,Massachusetts, USA.
66.Danyluk, A. (2004). Using robotics to motivate learning in an AI course for non-majors. Paper presented at the AAAI springsymposium, March 22-24, in Stanford, California, USA.
67.Imberman, S. (2003). Teaching neural networks using Lego-Handyboard robots in an artificial intelligence course. Paper presented at the proceedings of the 34th SIGCSE technical symposium on computer science education, February 19-23, in Reno, Nevada, USA.
68.Lee Wan-I and Bih-Yaw Shih, (2001). A case study of motivation theory on the web-based learning. In Proceedings of the 31st ASEE/IEEE Frontiers in Education Conference,. http://fie.engrng.pitt.edu/fie2001/papers/1442.pdf [Accessed 12 May 2006].
69.Ormrod, J. E. 2006. Educational Psychology: Developing Learners (5th ed.), "glossary". N.J., Merrill: Upper Saddle River (companion website)
70.Banduras, A.(1977) , Self-efficacy: Toward a Unifying Theory of Behavioral Change, Psychological Review , Vol. 84, No. 2, 191-215
71. Linda H. Bertland, (1986),An overview of research in metacognition：Implications for information skills instruction, School library media quarterly l5, ：96-99
72. Li-Fong Chen, (2003)The Information Seeking Skills of Children and Metacognition, Shuyuan Quarterly 45, 68-80