(3.238.186.43) 您好!臺灣時間:2021/03/02 10:45
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:鍾文耀
研究生(外文):Wen-Yaw Chung
論文名稱:國小教師使用Lego NXT機器人於教學之意象探討-以高雄縣及屏東縣國小教師為例
論文名稱(外文):The Exploration of Teachers’ Intention of Using Lego NXT in Elementary School-An Example of Kaohsiung and Pingtung County
指導教授:施弼耀施弼耀引用關係
指導教授(外文):Bih-Yaw Shih
學位類別:碩士
校院名稱:國立屏東教育大學
系所名稱:數位學習教學碩士學位學程
學門:教育學門
學類:教育科技學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:英文
論文頁數:31
中文關鍵詞:自我效能科技接受模式樂高 NXT真實教師意圖
外文關鍵詞:AuthenticSelf-efficiencyTeachers’ intentionLEGO NXTTechnology Acceptance Model
相關次數:
  • 被引用被引用:1
  • 點閱點閱:520
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:36
  • 收藏至我的研究室書目清單書目收藏:1
著名的樂高NXT的是一種低成本的機器人,可以很輕鬆地通過圖形用戶界面來組合製作,在台灣已成為一種流行的教學和學習工具而且被廣泛用於機器人教學。越來越多的樂高NXTs適用於不同的課程結合起來,為設計多媒體的教材。因此,了解影響教師在學校使用樂高NXT的意圖一直是渴望知道的研究課題,這是介以促進真實機器人學習材料和環境。
本研究是探討國小教師使用樂高NXT在傳統教學中作為輔助學習工具的意圖。研究者以科技接受模式(TAM),以及系統的特點和研究文獻所提到有關參與者提到的建議為基礎。研究者設計一假設模組。然後,收集47位來自高雄縣與屏東縣的國小教師。並以結構方程模式(SEM)為測試假設之工具。
The well-known LEGO NXT is a low-cost robot which can be easily programmed via graphical user interface and it is widely used for robotics education and has become a popular tool for teaching and learning in Taiwan. Eventually, more and more LEGO NXTs are applied to combine with different courses for designing multimedia instructional materials. Therefore, understanding the factors affecting teachers’ intention of using Lego NXT in school has been an eager research issue for the promotion of authentic robotic learning materials and environment.
The purpose of the current research is the exploration of teachers’ intention of using Lego NXT in elementary school where the system is used as a complementary learning tool within a traditional class. A model combining factors from Technology Acceptance Model (TAM) as well as system and participant characteristics cited in the research literature is proposed. Meanwhile, the operation of the LEGO NXT system is demonstrated first. Then, data were collected from forty seven elementary school teachers in Kaohsiung and Pingtung county. Structural Equation Modeling(SEM) is used to test the hypothesis.
Table of contents
Acknowledgements II
Abstract III
1. Introduction 1
2. Theoretical model 2
2.1. TRA and TAM 2
2.2. External variables 3
2.2.1. System characteristics 3
2.2.2. User characteristics 3
2.3. Usefulness constructs 4
2.4. Outcomes 4
3. Research model 5
4. Study 7
4.1. Data analysis methods and tools 7
4.2. PLS statistical methods are as follows: 8
4.3. Partial least squares method (Partial Least Squares, PLS) Overview 8
4.4. The results of data analysis and discussion 9
4. Study 7
5. Discussion 17
6. Conclusion 19
.Appendix A. List of items by construct 24
References
[1] Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies?. Decision Sciences, 30, 361–391.
[2] Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.
[3] Alavi, M. (1994). Computer-mediated collaborative learning: an empirical evaluation. MIS Quarterly, 18, 159. Anderson, C., Dankens, A., & Julian, E. H. (2000). Worldwide and US corporate IT education and training services: forecast and analysis 1999-2004 (International Data Corporation Report No. W22154), 2000, Abstract retrieved October 30, 2001. Available from: www.itresearch.com/alfatst4.nsf/UNITABSX/W22154?OpenDocument.
[4] Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: a review and recommended two step approach. Psychological Bulletin, 103, 411–423.
[5] Bailey, J. E., & Pearson, S. W. (1983). Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29, 530–545.
[6] Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological Review, 84, 191–215.
[7] Bollen, B. M. (1989). Structural equations with latent variables. New York, NY: Wiley–Interscience.
[8] Byrne, K. A. (1998). Structural equations modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications,and programming. Mahwah, NJ: Lawrence Erlbaum Associates.
[9] Carswell, A. D., & Venkatesh, V. (2002). Learner outcomes in an asynchronous distance education environment. International Journal of Human–Computer Studies, 56, 475–494.
[10] Chau, P. Y. K. (1996). An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13, 185–204.
[11] Chen, L. D., Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: an extended technology acceptance perspective. Information and Management, 39, 705–719.
[12] Chin, W. W., & Todd, P. A. (1995). On the use, usefulness, and ease of use of structural equation modeling in MIS research. MIS Quarterly, 19, 237–246.
[13] Compeau, D. R., & Higgins, C. A. (1995a). Application of social cognitive theory to training for computer skills. Information Systems Research, 6, 118–143.
[14] Compeau, D. R., & Higgins, C. A. (1995b). Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19, 189–211.
[15] Compeau, D. R., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: a longitudinal study. MIS Quarterly, 23, 145–158.
[16] Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13, 319–339.
[17] Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man–Machine Studies, 38, 475–487.
[18] Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35, 982–1003.
[19] Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
[20] Fornell, C. R., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50.
[21] Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption:
a study of E-Commerce adoption. Journal of the Association for Information System, 1 (8). Retrieved March 10, 2001. Available from: www.jais.aisnet.org/articles/default.asp?vol=1&art=8.
[22] Gefen, D., Straub, D. W., & Boudreau, M. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4 (7). Retrieved March 10, 2001. Available from www.cais.aisnet.org/articles/default.asp?vol=4&art=7.
[23] Gubernick, L., & Ebeling, A. (1997). I got my degree through e-mail. Forbes, June 16.
Heinich, R., Molenda, M., Russell, J. D., & Smaldino, S. E. (1996). Instructional media and technologies for learning (5th ed.). Englewood Cliffs, NJ: Prentice-Hall.
[24] Igbaria, M., Guimaraes, T., & Davis, G. B. (1995). Testing the determinants of microcomputer usage via a structural equation model. Journal of Management Information Systems, 11(4), 87–114.
[25] Igbaria, M., & Zinatelli, N. (1997). Personal computing acceptance factors in small firms: a structural equation model. MIS Quarterly, 2, 279–306.
[24] Jackson, C. M., Chow, S., & Leitch, R. A. (1997). Toward an understanding of the behavioral intention to use an information system. Decision Sciences, 2, 357–389.
[25] Joreskog, K. G., & Sorbom, D. (1993). LISREL8: Structural equation modeling with the SIMPLIS command language. Hillsdale, NJ: Erlbaum.
[26] Kelloway, E. K. (1998). Using LISREL for structural equation modeling: A researcher s guide. Thousand Oaks, CA:Sage.
[27] Kerka, S. (1999). Distance learning, the Internet, and the World Wide Web. ERIC Digest. (ERIC Document Reproduction Service No. ED 395214).
[28] Kline, R. B. (1998). Principles and practice of structural equation modeling. New York, NY: The Guilford Press.
[29] Lim, C. K. (2000). Computer self-efficacy, academic self-concept and other factors as predictors of satisfaction and future participation of adult learners in Web-based distance education. Dissertation Abstracts International, 61, 02A (UMI No. 9962612).
[30] Lucas, H. C., & Spitler, V. K. (1999). Technology use and performance: a field study of broker workstations. Decision Sciences, 30, 291–311.
[31] MacCallum, R. C. (1986). Specification searches in covariance structure modelling. Psychological Bulletin, 101,107–120.
[32] Mathieson, K. (1991). Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2, 173–191.
[33] Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2, 192–222.
[34] Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York, NY: McGraw-Hill. Palloff, R. M., & Pratt, K. (1999). Building learning communities in cyberspace: Effective strategies for the online classroom. San Francisco, CA: Jossey-Bass Publishers.
[35] Ruth, C. J. (2000). Applying a modified technology acceptance model to determine factors affecting behavioral Intentions to adopt electronic shopping on the World Wide Web: a structural equation modeling approach. Dissertation Abstracts International, 61, 03A. (UMI No. 9966196).
[36] Seels, B., & Glasgow, Z. (1998). Making instructional design decisions. Englewood Cliffs, NJ: Educational Technology Publications.
[37] Segars, A. H. (1997). Assessing the unidimensionality of measurement: a paradigm and illustration within the context of information systems research. Omega, 25, 107–121.
[38] Segars, A. H., & Grover, V. (1993). Re-examining perceived ease of use and usefulness: a confirmatory factor analysis. MIS Quarterly, 17, 517–525.
[39] Selim, H. M. (2003). An empirical investigation of student acceptance of course websites. Computers and Education, 40,343–360.
[40] Spooner, F., Jordan, L., Algozzine, B., & Spooner, M. (1999). Student ratings of instruction in distance learning and on-campus classes. Journal of Educational Research, 92, 132–140.
[41] Storck, J., & Sproull, L. (1995). Through a glass darkly: what do people learn in videoconferences?. Human Communication Research, 22, 197–219.
[42] Subramanian, G. H. (1994). A replication of perceived usefulness and perceived ease-of-use measurement. Decision Sciences, 25, 863–874.
[43] Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42, 85–92.
[44] Tan, M., & Teo, T. S. H. (2000). Factors influencing the adoption of Internet banking. Journal of the Association for Information System, 1 (5). Retrieved March 10, 2001. Available from: www.jais.aisnet.org/articles/default.asp?vol=1&art=5.
[45] Tate, R. (1998). An introduction to modeling outcomes in the behavioral and social sciences (2nd ed.). Edina, MN:Burgess.
[46] Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: a test of competing models. Information Systems Research, 6, 144–176. The survey of distance learning programs in higher education. (1999). New York: Primary Research Group, Inc.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔