An Adoption of the TAM Model to Determine Factors Affecting Students' Acceptance of e-Learning in Institutions of Higher Education in Saudi Arabia

An Adoption of the TAM Model to Determine Factors Affecting Students' Acceptance of e-Learning in Institutions of Higher Education in Saudi Arabia

The purpose of this study was to investigate the influence of psychological, social, technical, cultural and institutional factors on the students' acceptance of E-learning in institutions of higher education in Saudi Arabia. Data was collected from 480 students at five universities in Saudi Ar...

Full description

Saved in:
Bibliographic Details
Main Author: Alenezi, Abdulhameed Rakan
Format: Thesis
Language:eng
eng
Published: 2011
Subjects:
T Technology (General)
LB2300 Higher Education
Online Access:https://etd.uum.edu.my/2971/1/Abdulhameed_Rakan_Alenezi.pdf
https://etd.uum.edu.my/2971/2/1.Abdulhameed_Rakan_Alenezi.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-uum-etd.2971
record_format uketd_dc
institution Universiti Utara Malaysia
collection UUM ETD
language eng
eng
advisor Abdul Karim, Abdul Malek
Veloo, Arsaythamby
topic T Technology (General)
LB2300 Higher Education
spellingShingle T Technology (General)
LB2300 Higher Education
Alenezi, Abdulhameed Rakan
An Adoption of the TAM Model to Determine Factors Affecting Students' Acceptance of e-Learning in Institutions of Higher Education in Saudi Arabia
description The purpose of this study was to investigate the influence of psychological, social, technical, cultural and institutional factors on the students' acceptance of E-learning in institutions of higher education in Saudi Arabia. Data was collected from 480 students at five universities in Saudi Arabia by using multi stage stratified random sampling. The questionnaire for this study was adapted from Pituch and Lee (2006), Curtis and Payne (2008), and IVgai, Poon and Chan (2007). Several statistical techniques were used including t-tests, one-way ANOVA, bivariate correlation, and multiple regression analyses. The t-test results showed statistically significant differences in students' E-learning acceptance based on their major and internet experience while students' gender, computer and E-learning experience did not indicate any significant differences. The correlation analysis indicated that the relationships between the psychological, social, technological, cultural and institutional factors were significant. The simple linear regression revealed that, technological, social and psychological factors significantly contributed to the students' acceptance of E-learning while the cultural factor did not. The results of the stepwise regression showed that the variables related to the psychological factor all significantly contributed to the students' E-learning acceptance. As for the social factors, only image and self-identity significantly contributed to students' E-learning acceptance. With regards to the technological factor, three variables namely system response, system functionality and system interactivity significantly contributed to students' E-learning acceptance while system performance did not. Finally, all the institutional factor variables significantly contributed to students' E-learning acceptance. Hierarchical regression results indicated that attitude significantly mediated the relationship between the TAM main constructs and the students' Elearning acceptance. Based on the findings, it is suggested that, among others, higher educational institutions should take into consideration the influence of technological, institutional, social and psychological factors in the process of implementing Elearning.
format Thesis
qualification_name Ph.D.
qualification_level Doctorate
author Alenezi, Abdulhameed Rakan
author_facet Alenezi, Abdulhameed Rakan
author_sort Alenezi, Abdulhameed Rakan
title An Adoption of the TAM Model to Determine Factors Affecting Students' Acceptance of e-Learning in Institutions of Higher Education in Saudi Arabia
title_short An Adoption of the TAM Model to Determine Factors Affecting Students' Acceptance of e-Learning in Institutions of Higher Education in Saudi Arabia
title_full An Adoption of the TAM Model to Determine Factors Affecting Students' Acceptance of e-Learning in Institutions of Higher Education in Saudi Arabia
title_fullStr An Adoption of the TAM Model to Determine Factors Affecting Students' Acceptance of e-Learning in Institutions of Higher Education in Saudi Arabia
title_full_unstemmed An Adoption of the TAM Model to Determine Factors Affecting Students' Acceptance of e-Learning in Institutions of Higher Education in Saudi Arabia
title_sort adoption of the tam model to determine factors affecting students' acceptance of e-learning in institutions of higher education in saudi arabia
granting_institution Universiti Utara Malaysia
granting_department Awang Had Salleh Graduate School of Arts & Sciences
publishDate 2011
url https://etd.uum.edu.my/2971/1/Abdulhameed_Rakan_Alenezi.pdf
https://etd.uum.edu.my/2971/2/1.Abdulhameed_Rakan_Alenezi.pdf
_version_ 1747827474233819136
spelling my-uum-etd.29712022-04-11T06:30:23Z An Adoption of the TAM Model to Determine Factors Affecting Students' Acceptance of e-Learning in Institutions of Higher Education in Saudi Arabia 2011 Alenezi, Abdulhameed Rakan Abdul Karim, Abdul Malek Veloo, Arsaythamby Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Sciences T Technology (General) LB2300 Higher Education The purpose of this study was to investigate the influence of psychological, social, technical, cultural and institutional factors on the students' acceptance of E-learning in institutions of higher education in Saudi Arabia. Data was collected from 480 students at five universities in Saudi Arabia by using multi stage stratified random sampling. The questionnaire for this study was adapted from Pituch and Lee (2006), Curtis and Payne (2008), and IVgai, Poon and Chan (2007). Several statistical techniques were used including t-tests, one-way ANOVA, bivariate correlation, and multiple regression analyses. The t-test results showed statistically significant differences in students' E-learning acceptance based on their major and internet experience while students' gender, computer and E-learning experience did not indicate any significant differences. The correlation analysis indicated that the relationships between the psychological, social, technological, cultural and institutional factors were significant. The simple linear regression revealed that, technological, social and psychological factors significantly contributed to the students' acceptance of E-learning while the cultural factor did not. The results of the stepwise regression showed that the variables related to the psychological factor all significantly contributed to the students' E-learning acceptance. As for the social factors, only image and self-identity significantly contributed to students' E-learning acceptance. With regards to the technological factor, three variables namely system response, system functionality and system interactivity significantly contributed to students' E-learning acceptance while system performance did not. Finally, all the institutional factor variables significantly contributed to students' E-learning acceptance. Hierarchical regression results indicated that attitude significantly mediated the relationship between the TAM main constructs and the students' Elearning acceptance. Based on the findings, it is suggested that, among others, higher educational institutions should take into consideration the influence of technological, institutional, social and psychological factors in the process of implementing Elearning. 2011 Thesis https://etd.uum.edu.my/2971/ https://etd.uum.edu.my/2971/1/Abdulhameed_Rakan_Alenezi.pdf text eng public https://etd.uum.edu.my/2971/2/1.Abdulhameed_Rakan_Alenezi.pdf text eng public Ph.D. doctoral Universiti Utara Malaysia Adams, D. A., Nelson R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: A replication. MIS quarterly, 16(2), 227-247. doi: 10.23071249577. Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies. journal of Decision sciences and innovative education, 28(3), 557-582. doi: 10.1 1 1 l/j. 1540-591 5.1999.tbO 614.x. Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS quarterly, 24(4), 665-694. Reterived from http://www.business.auburn.edu/Corleij /plsqaq/misq-24 -04- 66 5- a garwal.pdf. Ajzen, I., & Fishbein, M. (1 980). Understanding attitudes and predicting social behaviour. Englewood Cliffs, NJ: Prentice-Hall. Ajzen, I. (1988). Attitudes, personality, and behavior. Milton-Keynes, England: Open University Press & Chicago, IL: Dorsey Press. Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-2 1 1. doi: 10.10 1610749-5978(91)900 20-T. Albalawi, S. (2007). Critical factors related to the implementation of web based instruction by higher education faculty at three universities in the Kingdom of Saudi Arabia (Doctoral dissertation, University of West Florida). Retrieved from http://etd.fcla.edu/WF/WFE0000095/Albalawi~Mohammed - Saleh-200708 - EdD.pdf. Alenezi, A. R., Abdul Karim, A. M., & Veloo, A. (2010). An Empirical investigation into the role of enjoyment, computer anxiety, computer self-efficacy and internet experience in influencing the students' intention to use e-learning: A case study from Saudi Arabian government universities. The Turkish Online Journal of Educational Technology, 9(4), 22-34. Retrieved from http://www.toiet.netlarticles/943 .pdf. Alexander, S., & Golja, T. (2007). Using students' experiences to derive quality in an e-Learning system: An institution's perspective. Subscription Prices and Ordering Information, 10(2), 17-33. Retrieved from http://www.ifets.info/ journals/lO - 2lets - 10 - 2.pdf. Al-Gahtani, S. S., Hubona, G. S., & Wang, J. (2007). Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT. Information & Management, 44(8), 68 1-691. doi: 10.1 108/09590550010337292. Al-Ghatanni, S., & King, M. (1999). Attitudes, satisfaction, and usage factors contributing to each of the acceptance of information technology. Behavioral & Information Technology, 18(4), 277- 297. doi: 10.1 080/0144929991 19020. Ali, S. H., Sait, S. M., & Al-Tawil, K. M. (2003, April). Perceptions about elearning in Saudi Arabia. Paper presented at the ICASE World Conference on Science & Technology Education, Penang, Malaysia. Al-Jarf, R. (2004, June). Intercultural Communication: Saudi, Ukrainian and Russian Students online. Paper presented at the 37th National Educational Computing Conference (NECC). New Orleans, Louisiana, USA. Al-Jarf, R. (2005, November). Connecting students across universities in Saudi Arabia. Paper presented at the 4th Asia CALL Conference. Korea. Al-Jarf, R. (2007, March). Cultural issues in online collaborative learning in EFL. Paper presented at the 3rd International Online Conference on Second and Foreign Language Teaching and Research. Al-Khaldi, M. A., & Olusegun R.S. (1999). The influence of attitudes on personal computer utilization among knowledge workers: The case of Saudi Arabia. Information and Management, 36(4), 185-204. doi: 10.1 01 6lS0378-7206(99) 0001 7-8. Alshare, K., Grandon, E., & Miller, D. (2004). Antecedents of computer technology usage: Considerations of the Technology Acceptance Model in the academic environment. Journal of Computing Sciences in Colleges, 20(1), 323-33 1. Amoako, G. K., & Salam, A. F. (2004). An extension of the Technology Acceptance Model in an ERP implementation environment. Information & Management, 41(6), 73 1-745. Anandarajan, M., Igbaria, M., & Anakwe, U. P. (2002). IT acceptance in a less developed country: A motivational factor perspective. International Journal of Information Management Science, 22(1), 47-65. doi: 10.1016/S0268- 4012(01)00040-8. Atkinson, M. A., & Kydd, C. (1997). Individual characteristics associated with World Wide Web use: An empirical study of playfulness and motivation. The Database for Advances in Information System, 28(2), 53-62.doi: 10.1 1451264 70 1.264705. Babbie, E. (1990). Survey research methods. Belmont, CA: Wadsworth. Babenko, M. Y., Andrunsyszyn, M.A. & Goldenberg, D. (2004). Effects of computer-based clinical conferencing on nursing students' self-efficacy. Journal of Nursing Education, 43(4), 149- 156. Bagchi, K., Cerveny, R., Hart, P., & Peterson, M. (2003). The influence of national culture in information technology product adoption. In Proceedings of the Ninth Americas Conference on Information Systems.(pp. 957-965).USA. Behl, D., Fitzgerald, J. & Vrazalic, L. (2007). Barriers to e-learning for students in the United Arab Emirates and Oman. In Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. (pp.2334-2338). Chesapeake, VA: AACE. Retrieved from http://www.editlib.ordp/26707. Bhattachejee, A. (2000). Acceptance of Internet applications services: The case of electronic brokerages. IEEE Transactions on systems, Man, and Cybernetics Part A: Systems and Humans, 30(4), 41 1420. Bleimann, U. (2004). Atlantis university: A new pedagogical approach beyond elearning. Campus-wide Information Systems Research, 21 (5), 19 l - 195. doi: 10.1 108/10650740410567536. Bless, C., & Higson-Smith, S. (1995). Fundamentals of social research methods: an Africanprospective (2nd ed.). Cape Town: Juta & Co Ltd, Credapress. Bloom, M. (2003, April). E-learning in Canada: Findings from 2003 e-survey. Paper presented at the Conference Board of Canada, Ottawa, Canada. Bock, G. W., Kim Y. G. (2002). Breaking the myths of rewards: An exploratory study of attitudes about knowledge sharing. Informs & Korms, 15(2), 14-21. doi: 10.1 10811 4637 1509 10949470. Bose, K. (2003). An e-learning experience: A written analysis based on my experience with primary school teachers in an e-learning pilot project. Campus-Wide Information Systems, 20(5), 193-203. doi: 10.1 1081 1065074 03 10507399. Brown, I. T. J. (2002). Individual and technological factors affecting peou and webbased learning technologies in a developing country. Electronic Journal in Information System in Developing Countries, 9(5), 1 - 15. Burns, N., & Grove, S. K. (1993). Practice of nursing research: conduct, critique, and utilization (2nd ed.). Philadelphia: W.B. Saunders Company. Calantone, R. J., Griffith, D. A., & Yalcinkaya, G. (2006). An empirical examination of a technology adoption model for the context of China. Journal of International Marketing, 14(4), 1-27. doi: 10.1509/jimk. 14.4.1. Culture definitions (2009). In Cambridge Advanced Learner's Dictionary. Retrieved January, 12,2009, fiom http://dictionary.cambridge.org/define.asp? key= 1 8 8 8 8 &dict=CALD. Chaffey, D. & Wood, S. (2005). Business information management: Improving performance using information systems. United Kingdom: Pearson Education Limited. Chang, P. V. C. (2004). The validity of an extended Technology Acceptance Model (TAM) for predicting the Intranet / Portal usage. (Master's thesis). Retrieved fiom http:/kdl.handle.net 11 90 1/78. Charbaji, A., Al-Hajhouj, H. R., & Beyruti, N. (2006, July). The influence of type of university culture on faculty usage of WebCT in Lebanon and Saudi Arabia. Paper presented at the Second IASTED international conference on education and technology ICET. Calgary, Canada. Chau, P. Y. K. (1996). An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13(2), 185- 204. Reterived from http://www.jstor.org/pss/4039822 1. Chau, P. Y. K., & Hu, P. J. H. (2001). Information technology acceptance by individual professionals: A model comparison approach. Decision Sciences Journal of Innovative Education, 32(4), 699-719. doi: 10.1 1 1 1/j. 1540- 591 5.2001.tb00978.x. Chen, J. L. 201 1. The effects of education compatibility and technological expectancy on e-learning acceptance. Computers & Education, 57(2), 1501- 151 1. Clark, R. E. (2000). Evaluating distance education: Strategies and cautions. The Quarterly Journal of Distance Education, 1(1), 3- 16. Coakes, S. J., Steed, L., G. & Dzidic, P. (2006). SPSS version 13.0 for windows: Analysis without anguish. Australia: John Wiley and Sons. Coakes, S. J., & Steed, L. G. (2003). SPSS analysis without anguish version 11 for Windows. Australia: John Wiley and Sons. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. NJ: Lawrence Erlbaum. Comfrey, A. L., & Lee, H. B. (1992). Afirst course in factor analysis. Hillsdale, NJ: Lawrence Erlbaum Associates. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-2 1 1. doi: 10.2307124968 Cooper, D. R., & Schindler, P.S. (2003). Business research methods (8th ed.). New Delhi: Tata McGraw Hill Publishing. Curtis, M. B., & Payne, E. A. (2008). An examination of contextual factors and individual characteristics affecting technology implementation decisions in auditing. International Journal of Accounting Information Systems, 9(2), 104-121. doi: 10.101 6/j.accinf.2007.10.002. Davis, F. (1986). A Technology Acceptance Model for empirically testing new enduser information systems: Theory and results. (Unpublished Doctoral dissertation). Massachusetts Institute of Technology, Massachusetts, USA. Davis, F. D. (1 989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 3 19-339. doi: 10.23 071249 008. 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. doi: 10.1287/mnsc.35.8.982. Definitions of Acceptance (2009). In Word web Online. Retrieved February, 4,2009, from http://www.wordwe bonline. com/search.pl?w=acceptance. Dillon, A., & Moms, M. G. (1996). User acceptance of information technology: Theories and models. Annual Review of Information Science and Technology, 31(1), 3-32. Downey, S., Wentling, R. M., Wentling, T., & Wadsworth, A. (2005). The relationship between national culture and the usability of an e-learning system. Human Resource Development International, 8(1), 47-64. doi: 10.1080/1367886042000338245. Elasmar, M. G., & Carter, M. E. (1996). Use of e-mail by college students and implications for curriculum. Journalism and Mass Communication Education, 51 (2), 46-54. Ely, D. P. (1999). Conditions that facilitate the implementation of educational technology innovations. Educational Technology & Society, 39(3), 23-27. Fishbein, M., & Ajzen, I. (1975). BelieJ; attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley. Frankola, K. (2001). Why online learners drop out. Workjiorce Management, 80 (lo), 53-59. Retrieved from http://www.workforce.com/ Furneaux, B. (2005a). Unified theory of acceptance and use of technology [Electronic Version]. Appalachian State University. Retrieved June 22, 2008 from http://www.istheory.yorku.ca/LTTAUT.htm . Furneaux, B. (2005b). Diffusion of innovations [Electronic Version]. Appalachian State University. Retrieved June, 29, 2008 from http://www.istheo ry.yorku. cddiffbsionofinnovations.htm. Furneaux, B. (2006). Technology acceptance model. [Electronic Version]. Appalachian State University. Retrieved July, 5, 2008 from http://www.ist heory .yorku.cdTechnologyacceptancemodel.htm. Fusilier, M., & Durlabhji, S. (2005). An exploration of student internet use in India: The Technology Acceptance Model and the theory of planned behaviour. Campus Wide In formation Systems, 22(4), 23 3 -246. Gall, M. D., Borg, W. R., & Gall, J. P. (1996). Educational research: An introduction (6th ed.). New York: Longman. Galletta, D. F., Ahuja, M., Hartman, A., Teo, T., & Peace, A. G. (1995). Social influence and end-user training. Communications of the ACM, 38(7), 70-79. Gazette. (2008, April). Business: Kingdom's e-learning industry to reach $125 million this year. Saudi Gazette online, Retrieved from http:l/ www.saudigazette.com.sdindex.cfm?method=home.regcon& content ID=200804244097. Gefen, D., & Straub, D.W. (1997). Gender difference in the perception and use of email: An extension to the technology acceptance mode. MIS Quarterly, 21(4), 389-400. doi: 10.2307/249720. 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 Systems, 8(1), 1-28. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Inexperience and experience with online stores: The importance of TAM and trust. IEEE Transactions on Engineering Management, 50(3), 307-321. doi: 10.1 109/TEM.2003.8 17277. Giddens, A. (1991). Modernity and self-identity: Selfand society in the late modern age. New York: Basic Books. Gotschall, M. (2000). E-learning strategies for executive education and corporate training. Fortune, 141 (1 O), 5 - 59. Granberg, D., & Holmberg, S. (1990). The intention-behavior relationship among U.S. and Swedish voters. Social Psychology Quarterly, 53(1), 44-54. doi: 10.2307/2786868. Greenagel, F.L. (2002). The illusion of e-learning: why we're missing out on the promise of technology, retrieved June 3,2009 from http://www.guidedlearninn.com/illusions.pdf. Guttman, L. (1954). Some necessary conditions for common factor analysis. Psychometrika, 19(2), 149- 162. doi: 10.1007/BF02289162. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis. NJ: Prentice hall Upper Saddle River. Hair, J. F., Money, A. H., Samouel, P., & Page, M. (2006). Research methods for business. Chichester: John Wiley and Sons Ltd. Harrison, D., Newman, D.A., & Roth, P.L. (2006). How important is job attitude? Meta-analytic comparisons of integrative behavioral outcomes and time sequences. Academy of Management Journal of Distance Education, 49(2), 305-325. Retrieved from www.business.unr.edu/faculty/simmonsb/mgt486 /amjjobattitudes.pdf. Hasan, B., & Ali, J. M. (2004). An empirical examination of a model of computer learning performance. Journal of Computer Information Systems, 44(4), 27- 34. Hasan, H., & Ditsa, G. (1999). The impact of culture on the adoption of IT: An interpretive study. Journal of Global Information Management Science, 7(1), 5- 16. doi: 10.40181jgim.1999010101. Hayashi, A., Chen, C., Ryan, T. & Wu, J. (2004). The role of social presence and moderating role of computer self-efficacy in predicting the continuance usage of e-learning systems. Journal of Information Systems Education, 15(2), 139- 154. Heijden, V. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695-704. Henryson, S. Analysis and using data on test items. In Thorndike R. (Eds.), Educational measurement (2nd ed.) (pp. 124- 153). Washington, D.C: America Council on Education. Hiemstra, R. (1997, September). Working with the self-directed learner. Paper presented at the First World Conference on Self-Directed Learning, Montreal, Canada. Hofstede, G. (2001). Culture's consequences: Comparing values, behaviors, institutions, and organizations across nations (2nd ed.). CA: Thousand Oaks. Hoskins, S. L., & Hooff, J. C. (2005). Motivation and ability: Which students use online learning and what influence does it have on their achievement. British Journal of Educational Technology, 36(2), 177-1 92. doi: 10.1 1 1 11 j. 1467-8535.2005.0045 1 .x. 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. doi:10.1016/j.im.2003.08.014. Ibrahim, D. Z., Abu Daud S., & Abu Samah B. (2002, February). Readiness and attitude towards online learning among virtual students. Paper presented at the meeting of the Asian Association of Open Universities, New Delhi. Igbaria, M. (1990). End-user computing effectiveness: A structural equation model. Omega International Journal of Management Science, 18(6), 637-652. doi: lo. 101 610305-0483(90)90055-E. Igbaria, M., Iivari, J., Maragahh, H. (1995). Why do individuals use computer technology? A Finnish case study. Information & Management Science, 29(5), 227-238. doi: 10.1016/0378-7206(95)0003 1-0. Igbaria, M., Parasuraman, S., & Baroudi, J. (1996). A motivational model of microcomputer usage. Journal of Management Information Systems, 13(1), 127-143. Igbaria, M., Zinatelli, N., Cragg, P., & Cavaye, A. M. (1997). Personal computing acceptance factors in small firms: A structural equation model. MIS Quarterly, 21(3), 279-305. doi: 10.23071249498. Israel, G. D. (1992). Determining sample size: The Program Evaluation and Organizational Development. Retrieved from http://edis.ifas.ufl.edu /pdffiles/PD/PD00600.pdf. Jack, Z., & Curt, U. (2001). Why blended will win. Training and Development, 55(8), 54-60. Jackson, L. A,, Ervin, K. S., Gardner, P. D., & Schrnitt, N. (2001). Gender and the Internet. Women communicating and men searching, 44(5), 363-379. doi: 10.1016/j.chb.2010.08.001. JISCinfonet. (2008). Exploring Tangible Benefits of e-Learning: Does investment yield interest? [Electronic Version]. Northumbria University. Retrieved May 3 1, 2008 from http://www.jiscinfonet.ac.uk~publications/camel-tangiblebenefits. pdf. Jobber, D. (1 989). An examination of the effects of questionnaire factors on response to an industrial mail survey. International Journal of Research in Marketing, 6(2), 129-1 40. doi: 10.101 610 167-8 1 16(89)90006-2. Kaiser, H. F. (1960). The application of electronic computer to factor analysis. Educational and Psychological Measurement, 20, 14 1 - 15 1. Doi: 10.1 177100 1 316447403400115. Karahanna, E., Straub, D.W., & Chervany, N.L. (1999). Information technology adoption across time: A cross-sectional comparison of pre- adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183-21 3. doi: 10.2307124975 1. Kerka, S. (1999). Distance learning, the Internet, and the World Wide Web. ERIC Digest [Electronic Version]. Retrieved March, 23, 2009 from http://www.ed.gov/database/ ERIC-Digests/ ed3952 14.html Kinnear, P. R., & Gray, C. D. (1994). SPSS for windows made simple. Hove, East Essex, UK: Lawrence Erlbaum Associates. Klein, H. K., Hirschheim R., & Nissen H.E. (1991). A Pluralist Perspective of the Information Systems Research Arena. Elsevier, Amsterdam: Contemporary Approaches and Emergent Traditions Information Systems Research. Kleinman, J., & Entin, E. B. (2002). Comparison of in-class and distancelearning students' performance and attitudes in an introductory computer science course. The Journal of Computing in Small Colleges, 17(6), 206- 21 9. Koohang, A. (2004). Students' perceptions toward the use of the digital library in weekly web-based distance learning assignments portion of a hybrid programme. British Journal of Educational Technology, 35(5), 6 17-626. doi:10.1111/j.0007-1013.2004.00418.x. Kovacic, Z. J. (2005). The impact of national culture on worldwide egovernment readiness. Informing Science Journal, 8, 143- 1 59. Krejcie, R., & Morgan, D. (1970). Determining sample size for research activities Educational and Psychological Measurement, 30,607-6 10. Lai, J. Y., & Ong, C. H. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 81 6 829. doi: 10.1 01 6/j.chb.2004.03.006 . Landry, B. J. L., Rodger G., & Hartman S. (2006). Measuring student perceptions of blackboard using the technology acceptance mode. Decision Sciences Journal of Innovative Education 4(1), 87-99. Lee, J. S., Cho, H., Gay, G., Davidson, B., & Ingraffea, A. (2003). Technology acceptance and social networking in distance learning. Educational Technology & Society, 6(2), 50-61. Retrieved from http://www.ifets.info /journals/6-216.htrnl. Lee, M. K. O., Cheung, C. M. K., & Chen, Z. (2005). Acceptance of internet-based learning medium: The role of extrinsic and intrinsic motivation. Information & Management, 42(8), 1095-1 104. doi:10.1016/j.im.2003.10.007. Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003). The technology acceptance model: Past, present, and future. Communications of the AIS, 12(50), 752-780. Retrieved from http://infosvs.coba.usf.edu/bs/Lee03-TAMcritique.pdf. Lee, Y., Lee, J., & Lee, Z. (2006). Social influence on technology acceptance behavior: Identity theory perspective. Information Systems, 3 7 (2&3), 60-75. Lee, Y. C. (2006). An empirical investigation into factors influencing the adoption of e-learning system. QIR, 30(5), 5 17-541. doi: 10.1 10811468452061 0706406. Lewin, K. (1997). Resolving social confIicts and field theory in social science: Washington, DC: American Psychological Association. Liaw, S. S., & Huang, H. M. (2003). An investigation of user attitudes toward search engines as an information retrival tool. Computers in Human Behavior, 19(6), 75 1-765. doi: 10.10 16lS0747-5632(03)00009-8. Lim, C. K. (2000). Computer self-efficacy, academic self-concept, and other predictors of satisfaction and future participation of adult distance learners. The American Journal of Distance Education, 15(2), 4 1 -5 1. doi: 10.1 0801089236401 09527083. Lin, C., Hu, P. J. H., & Chen, H. (2003). Technology implementation management in law enforcement: System usability and user acceptance evaluations [Electronic Version]. Retrieved January, 12,2009 from http:llwww.diggov.org/dgrcldgo2003/cdromlPAPERSci usabilitvllin copli nk.pdf. Liu, L., & Ma, Q. (2006). Perceived system performance: A test of an extended technology acceptance model. Data Bases, 3 7(2-3), 5 1-59. doi: 10.1 145 I1 161345.1 161354. Madorin, S., & Iwasiw, C. (1999). The effects of computer-assisted instruction on the self-efficacy of baccalaureate nursing students. Journal of Nursing Education, 38,282-295. Mahinda, E., & Whitworth, B. (2005, August). The Web of System Performance: Extending the TAM Model, Information Systems Evaluation track. Paper presented at the Americas Conference on Information Systems, Omaha, Nebraska, USA. Mao, E., Srite M., Thatcher, J.B., & Yaprak, 0. (2005). A research model for mobile phone service behaviors: empirical validation in the U.S. and Turkey. Journal of Global Information Technology Management, 5(4), 7-28. Mao, E. & Palvia, P. (2006). Testing an Extended Model of IT Acceptance in the Chinese Cultural Context. DATA BASE for Advances in Information Systems, 37 (2&3), 20-32. Masrom, M. (2007). Technology Acceptance Model and E-learning. Paper presented at the 12th International Conference on Education. Universiti Brunei Darussalam. Brunei. Mathieson, K. (1 99 1). Predicting user intentions: Comparing the Technology Acceptance Model with the theory of planned behavior. Information Systems Research, 2(3), 173-191. doi: 10.1287/isre.2.3.173. McCoy, S., Everard, A., & Jones, B. M. (2005). An examination of the Technology Acceptance Model in Uruguay and the US: A focus on culture. Journal of Global Information Technology Management, 8(2), 27-45. Milis, K., Wessa, P., Poelmans, S., Doom, C., & Bloemen, E. (2008). The impact of gender on the acceptance of virtual learning environments. Paper presented at the International Conference of Education, Research and Innovation, International Association of Technology, Education and Development, Madrid, Spain. Miller, M., Rainer, R. K., & Corley, J. K. (2003). Predictors of engagement and participation in an on-line Course. Online Journal of Distance Learning Administration, 6(1), 1-1 3. Ministry of Education. (2008). National report on education development in the Kingdom of Saudi Arabia. Paper presented at the Education International Conference, Geneva. Ministry of higher education. (2007). higher education and universities achievement report (No. 1): Ministry of higher education. [Electronic Version]. Retrieved April, 24,2009 from http://www.mohe.edu.sa. Money, W., & Turner A. (2005). Assessing knowledge management system user acceptance with the technology acceptance model. International Journal of Knowledge Management 1(1), 8-26. doi: 10.401 8/jkm.2005010101. Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a world-wide-web context,. Info. & Mgt., 38,217-230. doi: 10.101 6lS0378-7206(00)00061-6. 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. Doi: lO.l287/isre.2.3.192. Myers, M. D., & Tan, F. B. (1997). Beyond models of national culture in information systems research. Journal of Global Information Management, 10(1), 24-32. Naqvi, S. J., & Ajiz, M. A. (2006). Attitudes toward WebCT and Learning: An Omani perspective. The Journal of Issues in Informing Science & Information Technology 1 (3), 435-445. Nasution, M. (2007, March). Investigating social influence on acceptance of executive information systems: Autaut framework approach. Paper presented at the Southern Association for information System Conference: Jacksonville, Florida, USA. Ndubisi, N. 0 . (2004, July). Factors influencing e-learning adoption intention: Examining the determinant structure of the decomposed theory of planned behaviour constructs. Paper presented at the HERDSA Conference, Sarawak, Malaysia. Neuman, W. L. (2003). Social research methods: Qualitative and quantitative approaches (5th ed.). Boston: Allyn and Bacon. Ngai, E. W. T., Poon, J. K. L., & Chan, Y. H. C. (2007). Empirical Examination of the Adoption of WebCT Using TAM. Computers & Education, 48(2), 250- 267. doi: 10.101 6/j.compedu.2004.11.007. Nichols, M. (2003). A theory for e-learning. Educational Technology & Society,6(2), 1 - 1 0. Retrieved from http://www.ifets.info/journals/6_2/ 1 .html Nunnaly, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill. Ong, C. S., Lai, J. Y., & Wang, Y. S. (2004). Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies. Information & Management, 41 (6), 795-804. doi: 10.1 016/j.im.2003.08.012. Oppenheim, C. (1998). The correlation between citation counts and the 1992 research assessment exercise ratings for British research in genetics, anatomy and archaeology. Journal of Documentation, 53(2), 477-487. doi: 10.1 1 081 EUM0000000007207. Pallant, J. (2001). SPSS survival manual: a step by step guide to data analysis using SPSS for windows (version 10 and 1 I). Buckingham: Open University Press. Palloff, R. M., & Pratt, K. (1999). Building learning communities in cyberspace: Effective strategies for the online classroom. San Francisco, CA: Jossey-Bass Publishers. Pan, C. S., Sivo, S., & Brophy, B. (2003, August). The use of a course management system in the light of the technology acceptance model: A student perspective. Paper presented at the 8th Annual Teaching in the Community Colleges Online Conference, Honolulu, HI. Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the Theory of Planned Behavior. MIS Quarterly, 30(1), 115-134. Payne, D. A., & McMonis, R. F. (1967). Educational and psychological measurement. Waltham,Mass: Blaisdell Publication Company. Payne, E. A., & Curtis, M. B. (2008.). Can the unified theory of acceptance and use of technology help us understand the adoption of computer-aided audit techniques by auditors? [Working Paper], University of Louisville, USA. Pituch, K. A., & Lee, Y. K. (2006). The influence of system characteristics on elearning use. Computers & Education, 2 7(2), 222-244. doi: 10.10 16/j. compedu.2004.10.007. Polit, D. F., & Hungler, B. P. (1 993). Essentials of nursing research: Methods, appraisal, and utilization (3rd ed.): Philadelphia: J. B. Lippincott Company. Rabak, L., & Innes, M. (2006). Acceptance and resistance to corporate e-learning: A case from the retail sector. Journal of Distance Education, 2(2 I), 1 15-1 34. Ramayah, T. (2004). Course website usage among distance learning business students: The role of prior experience. International Journal of Learning, 11(1), 1507-1518. Ramayah, T. (2006). Course website usage does prior experience matter. WSEAS Transactions on Information Science & Applications., 3(2), 299-306. Retrieved from http://eprints.usm.my/18 1711 /Course-Wbsite-Usage-Does Prior - Experience - Matter.pdf. Rezaei, M., Mohammadi, H.M., Asadi, A., & Kalantary, K. (2008). Predicting elearning application in agricultural higher education using technology acceptance model. Turkish Online Journal of Distance Education, 9 (I), 85- 95. Retrieved from http:lltojde.anadolu.edu.tr/tojde29/pdfNe9 Number 1 .pdf. Robson, C. (1993). Real world research a resource for Social Scientists and Practitioner-Researchers. Oxford: Blackwell. Roca, J. C., Chiu C. M. & Martinez, F. J. (2006). Understanding e-learning continuance intention: An extension of the technology acceptance model. International Journal of human-computer studies 64(8), 683-696. doi: 10.10 16/j.ijhcs.2006.01.003. Rogers, E. (1995). Dzfusion oflnnovations (4th ed.). New York: Free Press. Romiszowski, A. (2004). How's the e-learning baby? factors leading to success or failure of an educational technology innovation. Educational Technology, 44(1), 5-27. Retrieved from http://asianvu.com/digital-librarylelearning/ elearning - failure - study-romiszowsky.pdf. Rosenberg, M. J. (2001). E-Learning: Strategies for delivering knowledge in the digital age. NY: McGraw Hill. Royal Embassy of Saudi Arabia,. (2009). Saudi Arabia: Facts & Figures. [Electronic Version]. Retrieved April 9,2009 from http://www.saudiembassy.net /Country/Facts.asp. Ruth, C. J. (2000). Applying a modified Technology Acceptance Model to determine factors affecting behavioralintentions to adopt electronic shopping on the World Wide Web: a structural equation modeling approach. (Doctoral dissertation). Avaliable from Abstracts International (UMI No. 9966 196). SaadC, R. B. B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: An extension of the technology acceptance model. Info. & Mgt., 42(2), 3 17-327. doi: 10.1016/j.im.2003.12.0 13. SaadC, R. G., & Galloway, I. (2005). Understanding intention to use multimedia information systems for learning. The Journal of Issues in Informing Science and Information Technology 2(1), 287-296. Saadk, R. G., & Kira, D. (2006). The emotional state of technology acceptance. Issues in Informing Science & Information Technology, 3, 529-540. Retrieved from http://infomingscience.org/proceedings/InSITE2006/IISIT Saad 145 .pdf. Saadk, R., Tan, W., & Nebebe, F. (2008). Impact of motivation on intentions in online learning: Canada vs. China. In proceedings of Issues in Informing Sciences and informationtechnology, 5,13 71 47. Retrieved from http://proceeding.infomingscience.org/insite2008/iisitv5~137- 147saade463 .pdf. Sahab, S. (2003). Initiating distance education programs in Saudi Arabia using networked learning Technology. [Electronic Version]. Retrieved June, 1, 2008 from http://www.odlaa.org/publications/2003Proceedings /pdfs/sahab.pdf . SAMIRAD. (2009). Formal foundation of the kingdom. [Electronic Version]. Retrieved April 10,2009 from http://www.saudinf.com/main/b4.htm. Saunders, M., Lewis, P., & Thornhill, A (2003). Research methods for business students: Edinburgh: Prentice Hall. Schifter, C. C. (2000). Faculty participation in asynchronous learning networks: A case study of motivating and inhibiting factors. Journal of Asynchronous Learning Networks, 4(1), 15-22. Retrieved from http:Nsloanconsortium.org /sites/default/files/v4n1- s chifter- 1 . pdf. Seels, B., & Glasgow, Z. (1998). Making instructional design decisions. Columbus, Ohio: Menill Publishing Company. Segars, A. H., & Grover, V. (1993). Reexamining perceived ease of use and usefulness: A confirmatory factor analysis. MIS Quarterly, 17(3), 5 17-525. doi: 10.2307/249590. Sekaran, U. (1 992). Research methods for business. NY: Wiley Sekaran, U. (2000). Research methods for business: A skill building approach. NY: John Wiley & Sons, Inc. Sekaran , U. (2003). Research methods for business: A skill building approach. New York: John Wiley & Sons. Selim, H. M. (2003). An Empirical Investigation of Student Acceptance of Course Websites. Computers & Education, 40(4), 343-360. doi: doi: 10.101 61S0360 - 13 15(02)00 142-2. Shankaranarayanan, N. K., Jiang, Z., & Mishra, P. (2001). User-perceived performance of web browsing and interactive data in HFC cable access networks. IEEE International Journal on Communications, 4(1), 1264- 1268. doi: 10.1 109/ICC.2001.936895. Shannon, S., & Doube, L. (2004). Valuing and using web supported teaching: A staff development role in closing the gaps. Australasian Journal of Educational Technoloay, 20(1), 1 14-1 36. Retrieved from http://hdl.handle.net/2440/749. Shen, D., Laffey, J., Lin, Y., & Huang, X. (2006). Social influence for perceived usefulness and ease-of-use of course delivery systems. Journal of Interactive Online Learning, 5(3), 270-282. Retrieved from http://www.ncolr.org/jioll issues/getfile.cfm?volID=5&IssueID= 1 8&ArticleID=9 1 . Simonson, M. R., Maurer, M., Montag-Torardi, M., & Whitaker, M. (1987). Development of a standardized test of computer literacy and a computer anxiety index. Journal of Educational Computing Research, 3(2), 23 1-247. Sjazna, B. (1994). Software evaluation and choice predictive validation of the technology acceptance instrument. MIS Quarterly, 18(3), 3 19-324. doi: 10.2307124962 1. Slavin, R. E. (1992). Research methods in education (2nd ed.). Boston: Allyn & Bacon. Sparks, P., Shepherd, R., & Frewer, L. J. (1995). Assessing and structuring attitudes toward the use of gene technology in food production: The role of perceived ethical obligation. Basic and Applied Social Psychology, 16(3), 267-285. Doi: 10.1207/s15324834basp1603~1. Srite, M. (2006). Culture as an explanation of technology acceptance differences: an empirical investigation of Chinese and US users. Australasian Journal of Information Systems, 14(1), 5-26. Srite, M. (2000). The Influence of National Culture on the Acceptance and Use of Information Technologies: An Empirical Study (Doctoral Dissertation). The Florida State University. US. Stoel, L., & Lee, K. H. (2003). Modeling the effect of experience on student acceptance of web-based courseware. Internet Research: Electronic Networking Applications and Policy, 13(5), 364-374. doi: 10.1 10811 0662240 3 1050 1649. Straub, D., Keil, M. , & Brenner, W. (1997). Testing the Technology Acceptance Model across cultures: A three country study. Information & Management, 33(1), 1-1 1. doi: 10.101 6lS0378-7206(97)00026-8. Succi, C. (2007). Corporate eLearning Acceptance: the role of Context and Communication (PhD dissertation).Retrieved from http://doc.rero.ch/lm.php? url=l000,40,6,20070730172734-RW/2007COM007.pdf. Suh, C. K., & Lee, T. H. (2007). User acceptance of e-learning for voluntary studies. In Proceedings of the annual Conference on International Conference on Computer Engineering and Applications. (pp.538-544). Gold Coast, Queensland, Australia http://www.wseas.us/e-library/conferences/2007 australia/papers/550- 1 83 .pdf. Sun, H., & Zhang, P. (2005). An empirical study on causal relationships between perceived enjoyment and perceived ease of use. Paper presented on the Fourth Annual Workshop on HCI Research in MIS, Las Vegas, NV. Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives a successful elearning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1 183- 1202. doi: 10.1 01 6/j.compedu.2006.11.007. Sundqvist, S., Frank, L., & Puumaliainen, K. (2005). The effects of country characteristics, cultural similarity and adoption timing on the diffusion of wireless communications. Journal of Business Research, 58, 107-1 10. doi: 10.101 6lSO148-2963(02)00480-0. Szajna, B. (1 996). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92. doi: 10.1287/mnsc.42.1.85. Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144- 176. Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS quarterly, 19(4), 561 -570. doi: 10.23071249633. Teo, H. H., Chan, H. C., Wei, K. K., & Zhang, Z. (2003). Evaluating information accessibility and community adaptivity features for sustaining virtual learning communities. International Journal of Human-Computer Studies 59(9), 671 -697. doi: 10.101 61S107 1-58 19(03)00087-9. Teo, T. S. H., Tan, M., & Wong, K. B. (1998). A contingency model of Internet adoption in Singapore. International Journal of Electronic Commerce, 2(2), 95-1 18. Teo, T. S. H. (2001). Demographic and motivational variables associated with Internet usage activities. Internet Research: Electronic Networking Applications and Policy, 11(2), 125-137. doi: 10.1108/10662240110695089. Terry, D. J., Hogg, M. A., & White, K. M. (1999). The Theory of Planned Behavior: self-identity, social identity, and group norms. British Journal of Social Psychology, 38 (2), 225-244. doi: 10.1348/014466699164 149. Ministry of Foreign Affairs. (2006). The kingdom: Site and geographical position. Retrieved April 10, 2009, from http://www.mofa.gov.sal Detail.asp?InSectionID=25 l&InNewsItem ID=46466. Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124- 143. doi: 10.23071249443. Tolhurst, D., & Debus, R. L. ( 2002). Influence of prior knowledge, attitudes, ability, and activity structure on students' learning and use of software. Journal of Educational Computing Research, 27(3), 275-3 13. Triandis, H. C. (1971). Attitude and attitude change, NY: John Wiley and Sons. Trombley, K. B., & Lee, D. (2002). Web-based learning in corporations: Who is using it and why, who is not and why not? Journal of Educational Media, 27(3), 137-146. doi:10.1080/1358165022000081396. Tung, F. C., & Chang, S. C. (2008). An empirical investigation of students' behavioral intentions to use the online learning course websites. British Journal of Educational Technology, 39(1), 71 -83. Tung, L. L., & Quaddus, M. A. (2002). Cultural differences explaining the differences in results in GSS: Implications for the next decade. Decision Support Systems, 33(2), 177- 199. doi: 10.101 6lSO167-9236(01)00 143-9. Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences Journal of Innovative Education, 27(3), 45 1-482. doi: 10.1 1 1 1/j. 1540-591 5.1996.tb00860.x. Venkatesh, V. (2000). Determinants of perceived ease of use: integrating perceived behavioral control, computer anxiety and enjoyment into the technology acceptance model. Information Systems Research, 11(4), 342-365. doi: 10.1287lisre. 1 1.4.342.1 1872. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-205. doi: 10.1287/mnsc.46.2.186.11926. Venkatesh, V., & Morris M. G. (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(1), 1 15-1 39. doi: 10.2307/325098 1. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. Wagner, N., Hassanein, K., & Head, M. (2008). Who is responsible for E-Learning Success in Higher Education? A stakeholders' analysis. Educational Technology & Society, 11(3), 26-36. Reterived from http://www.ifets.info/ journals/l 1-313 .pdf. Webster, J., & Hackley, P. (1997). Teaching effectiveness in technology-mediated distance learning. Academy of Management Journal, 40(6), 1282-1 309. doi: 10.2307/257034. Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85- 102. doi: 10.1287/isre. 1050.0042. Wolk, R. M. (2007). Using the Technology Acceptance Model for outcomes assessment in higher education.In Proceedings of the Information Systems Education Conference. (PP. 1 - 16). (Pittsburgh). Retrieved from http://proc.isecon.or9/2007/35 121. Wolski, S. & Jackson, S. (1999). Technological Diffusion within Educational Institutions: Applying the Technology Acceptance Model. Proceedings of Society for Information Technology and Teacher Education International Conference 1999 (pp. 171 8-1 723). Chesapeake, VA: AACE. Retrieved from http://www.editlib.org/p/26707. World wide learn. (2008). New Dimensions in Education Benefits of E-Learning [Electronic Version]. Retrieved April 9,2009, from http://www.worldwidelearn.com/elearninn-essentials/elearninn-benefits.htm. Yayla, A. and Hu, Q. (2007, June). User acceptance of e-commerce technology: A metaanalytic comparison of competing models. In Proceedings of the 13th European. (pp. 179-1 90). Switzerland. Yi, M. Y., Davis F. D. (2001). Improving computer training effectiveness for decision technologies: behavior modeling and retention enhancement. Decision Sciences Journal of Innovative Education, 32(3), 521-544. doi: 10.1 1 1 llj. 1540-59 15.2001 .tb00970.x. Yi, M. Y., & Hwang, Y. (2003). Predicting the use of web-based information systems: Self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. International Journal of Human-Computer Studies, 59(4), 43 1-449. doi: 10.101 6lS1071-58 19(03)00114-9. Yi, M. Y., & Im, K.S. (2004). Predicting computer task performance: personal goal and self-efficacy. Journal of Organizational and End-user Computing, 16(2), 20-38. doi: 10.401 8/joeuc.2004040102. Yi-Cheng, C., Chun-Yu, C., Yi-Chen, L., & Ron-Chen, Y. (2007, July). Predicting college student' use of e-learning systems: An attempt to extend Technology Acceptance Model. Proceedings of Pacific Asia Conference on Information Systems. (1 72-1 83). Auckland, New Zealand. Yin, R. K. (2003). Case Study Research: Design and Methods (3rd ed.).Thousand Oaks: Sage Publication. Yousafzai, S. Y., Foxall G. R., & Pallister J. G. (2007). A meta-analysis of Technology Acceptance Model. Journal of Modelling in Management, 2(3), 25 1-280. Yuen, H. K., & Ma, W. K. (2002). Gender differences in teacher computer acceptance. Journal of Technology and Teacher Education, 10(3), 365-3 82. Retrieved from http://www.editlib.org!p/l5 142. Zander, U., & Kogut, B. (1995). Knowledge and the speed of the transfer and imitation of organizational capabilities: An empirical test. Organization Science, 6(1), 76-92. doi: 10.1287/orsc.6.1.76. Zikmund, W. G. (2003). Business research methods (7th ed.). Toronto: Dryden Press.

Similar Items