Measuring Acceptance Level of Learning Zone Among Universiti Utara Malaysia (UUM) Students: A Study of the Role Intention to Use as Mediator in the Relationship of Usefulness and Ease of Use Towards User Satisfaction

Changes in technologies have changed our lives. Education field was not exempted from the current technology changes. Technology now plays an important role to improve accessibility in seeking knowledge and wisdom much faster and easier. The changes of Malaysia’s education system and worldwide gener...

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Main Author: Roslan, Ridzuan
Format: Thesis
Language:eng
eng
Published: 2011
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Online Access:https://etd.uum.edu.my/2869/1/Roslan_Ridzuan.pdf
https://etd.uum.edu.my/2869/2/1.Roslan_Ridzuan.pdf
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id my-uum-etd.2869
record_format uketd_dc
institution Universiti Utara Malaysia
collection UUM ETD
language eng
eng
advisor Ramli, Azahari
topic T Technology (General)
L Education (General)
spellingShingle T Technology (General)
L Education (General)
Roslan, Ridzuan
Measuring Acceptance Level of Learning Zone Among Universiti Utara Malaysia (UUM) Students: A Study of the Role Intention to Use as Mediator in the Relationship of Usefulness and Ease of Use Towards User Satisfaction
description Changes in technologies have changed our lives. Education field was not exempted from the current technology changes. Technology now plays an important role to improve accessibility in seeking knowledge and wisdom much faster and easier. The changes of Malaysia’s education system and worldwide generally have taken steps to lead the field in using trusted online access to benefit the education sector. Public and private institutions in Malaysia have been taking advantage from ease of internet access to provide its students with more secure and reliable information more effectively. Therefore, this study exploits the technology acceptance model established by Davis (1989) to examine the level of acceptance using Learning Zone as a portal that helps learning process. Technology acceptance model (TAM) established by Davis (1989) has three basic instruments of perceived usefulness (PU), perceived ease of use (PEU) and user satisfaction (US). However, intention to Use (IU) had been inserted in this study as a mediator to examine whether perceived usefulness and perceived ease of use will have an impact on the intention to use to achieve satisfaction. Students of Universiti Utara Malaysia (UUM) which have access of using Learning Zone have been selected to participate in the study. A total of 391 usable data provide by the respondents is being used to achieve the objectives of the study. Therefore, correlation and multiple regression analysis were used to examine whether perceived usefulness and perceived ease of use will have the impact on user satisfaction. Generally, the correlation analysis shows that there is a significant and strong positive correlation between variables perceived usefulness towards user satisfaction; perceived ease of use towards user satisfaction; and intention to use towards user satisfaction.
format Thesis
qualification_name masters
qualification_level Master's degree
author Roslan, Ridzuan
author_facet Roslan, Ridzuan
author_sort Roslan, Ridzuan
title Measuring Acceptance Level of Learning Zone Among Universiti Utara Malaysia (UUM) Students: A Study of the Role Intention to Use as Mediator in the Relationship of Usefulness and Ease of Use Towards User Satisfaction
title_short Measuring Acceptance Level of Learning Zone Among Universiti Utara Malaysia (UUM) Students: A Study of the Role Intention to Use as Mediator in the Relationship of Usefulness and Ease of Use Towards User Satisfaction
title_full Measuring Acceptance Level of Learning Zone Among Universiti Utara Malaysia (UUM) Students: A Study of the Role Intention to Use as Mediator in the Relationship of Usefulness and Ease of Use Towards User Satisfaction
title_fullStr Measuring Acceptance Level of Learning Zone Among Universiti Utara Malaysia (UUM) Students: A Study of the Role Intention to Use as Mediator in the Relationship of Usefulness and Ease of Use Towards User Satisfaction
title_full_unstemmed Measuring Acceptance Level of Learning Zone Among Universiti Utara Malaysia (UUM) Students: A Study of the Role Intention to Use as Mediator in the Relationship of Usefulness and Ease of Use Towards User Satisfaction
title_sort measuring acceptance level of learning zone among universiti utara malaysia (uum) students: a study of the role intention to use as mediator in the relationship of usefulness and ease of use towards user satisfaction
granting_institution Universiti Utara Malaysia
granting_department College of Business (COB)
publishDate 2011
url https://etd.uum.edu.my/2869/1/Roslan_Ridzuan.pdf
https://etd.uum.edu.my/2869/2/1.Roslan_Ridzuan.pdf
_version_ 1747827448991449088
spelling my-uum-etd.28692013-07-24T12:18:30Z Measuring Acceptance Level of Learning Zone Among Universiti Utara Malaysia (UUM) Students: A Study of the Role Intention to Use as Mediator in the Relationship of Usefulness and Ease of Use Towards User Satisfaction 2011 Roslan, Ridzuan Ramli, Azahari College of Business (COB) College of Business T Technology (General) L Education (General) Changes in technologies have changed our lives. Education field was not exempted from the current technology changes. Technology now plays an important role to improve accessibility in seeking knowledge and wisdom much faster and easier. The changes of Malaysia’s education system and worldwide generally have taken steps to lead the field in using trusted online access to benefit the education sector. Public and private institutions in Malaysia have been taking advantage from ease of internet access to provide its students with more secure and reliable information more effectively. Therefore, this study exploits the technology acceptance model established by Davis (1989) to examine the level of acceptance using Learning Zone as a portal that helps learning process. Technology acceptance model (TAM) established by Davis (1989) has three basic instruments of perceived usefulness (PU), perceived ease of use (PEU) and user satisfaction (US). However, intention to Use (IU) had been inserted in this study as a mediator to examine whether perceived usefulness and perceived ease of use will have an impact on the intention to use to achieve satisfaction. Students of Universiti Utara Malaysia (UUM) which have access of using Learning Zone have been selected to participate in the study. A total of 391 usable data provide by the respondents is being used to achieve the objectives of the study. Therefore, correlation and multiple regression analysis were used to examine whether perceived usefulness and perceived ease of use will have the impact on user satisfaction. Generally, the correlation analysis shows that there is a significant and strong positive correlation between variables perceived usefulness towards user satisfaction; perceived ease of use towards user satisfaction; and intention to use towards user satisfaction. 2011 Thesis https://etd.uum.edu.my/2869/ https://etd.uum.edu.my/2869/1/Roslan_Ridzuan.pdf application/pdf eng validuser https://etd.uum.edu.my/2869/2/1.Roslan_Ridzuan.pdf application/pdf eng public masters masters Universiti Utara Malaysia Adams, D., Nelson, R. R., Todd, P. A. (1992), Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Quarterly, 16: 227–247. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, New Jersey: Prentice-Hall. Ajzen, I. & Madden, J.T. (1986). Prediction of goal directed behaviour, attitudes, intentions and perceived control. Journal of Experimental Social Psychology. 22, 253-274. Ajzen, I. (2002). Perceived behavioural control, self-efficacy, locus of control and the theory of planned behaviour. Journal of Applied Social Psychology, 32 (4),665- 83. Al-Gahtani (2001). The applicability of TAM outside North America: An empirical test in the United Kingdom. Information Resources Management Journal 14(3): 37-46. Amoako-Gyampah, K., & Salam, A. F (2004). An extension of the technology acceptance model in an ERP implementation environment. Information and Management 41(6): 731-745. Anastasi, A. (1982). Psychological Testing. (5th edition). New York: Macmillan. Anne M Kavanagh, R. J. B., Kate E Mason, Jodie McVernon, Sylvia Petrony, James Fielding and D. M. S. Anthony D LaMontagne6 (2011). Sources, perceived usefulness and understanding of information disseminated to families who entered home quarantine during the H1N1 pandemic in Victoria, Australia: a cross-sectional study. BMC Infectious Diseases, 11: 1471-2334. Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology. 51: 1173-1182. Begum, N. J. a. N. (2008). The role of perceived usefulness, perceived ease of use, security and privacy, and customer attitude to engender customer adaptation in the context of electronic banking. African Journal of Business Management, 2(1): 032-040. Borgmann, A. (2006). Technology and the Character of contemporary Life: A Philosophical inquiry. University of Chicago Press. Bryman, A. (2007). Business Research Methods. Oxford University Press. Burn, A. C. & Bush, R. F. (1998). Marketing Research. (2nd ed.) London. Prentice-Hall. Chan, H.C. and Teo, H.H. (2007). Evaluating the Boundary Conditions of the Technology Acceptance Model: An Exploratory Investigation. ACM Trans. Computer Human Interaction 14(2): 9. Coakes, S. J. & Steed, L. G. (2003). SPSS: Analysis without Anguish. Australia: John Wiley & Sons, Ltd. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/ correlation analysis for the behavioral sciences, 3rd ed. Hillsdale: Erlbaum. Culwin, F. (2007). Learning Beans: Design, Implementation & Evaluation. BCS HCI Group Conference. 2(1). Dasgupta, S., Granger, M. & Mcgarry, N. (2002). User acceptance of e-collaboration technology: an extension of the technology acceptance model, Group Decision and Negotiation, 11, 87-100. Daniel Cruz, M. A. (2007). Application of Data Screening Procedures in Stress Research. The new School Psychology Bulletin, 5(2). 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. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), pp. 318-340. Davis, F.D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioural impacts. International Journal of Man-Machine Studies 38, pp. 475-487. Davis, F.D. and Venkatesh, V. (2004). Toward Preprototype User Acceptance Testing of New Information Systems: Implications for Software Project Management. IEEE Transactions on Engineering Management, 51 (1). Doll, W., Hendrickson, A., Xiandong, D. (1998). Using Davis’s Perceived Usefulness and Ease-of-Use Instruments for Decision Making: A Confirmatory and Multi-Group Invariance Analysis, Decision Sciences, 29(4), 839-869. Elmore, P.E. & Beggs, D.L. (1975). Salience of concepts and commitment to extreme judgements in response pattern of teachers. Education, 95(4), 325 – 334. Fishbein, M. & Ajzen, I. (1975), Belief, attitude, intention and behavior: an introduction to theory and research. Reading, MA: Addison-Wesley. Frennea, V. M. C. (2010). Customer Satisfaction: A Strategic Review and Guidelines for Managers. Marketing Science Institute: 10-701. Gefen, D., Straub, D. (2000). The Relative Importance of Perceived Ease of Use in IS Adoption: A Study of Ecommerce Adoption, Journal of the Association of Information Systems. 1(8). Grunwald, D. and Goldfarb, N. M. (2006). Back Translation for Quality Control of Informed Consent Forms. Journal of Clinical Research Best Practices, 2(2). Hair. J. F., Anderson, R. E., Tatam, R. L., & Beach, W. C. (1998). Multivariate data analysis. (3th Ed). MacMillan Publ. Co. Hair, J. F., Balck, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th Ed). Upper Saddle River, New Jersey: Pearson Education International. Hair, J. F., Money, a. H., Samouel, P., Page, M. (2007). Research methods for business. Chrichester, England: John Wiley & Sons Ltd. Haruna, M. Z. (2010). Software architecture evaluation using Architecture Tradeoff Analysis Method (ATAM): A case study off UUM learning zone system, Universiti Utara Malaysia. Master of Science (information and Communication Technology). Haviland, William A. (2004). Cultural Anthropology: The Human Challenge. The Thomson Corporation. p. 77. Hendricks, J. D., Meyers, T. R., Casteel, J. L., Nixon, J. E., Loveland, P. M., Bailey, G. S. (1984). Rainbow Trout Embryos: Advantages and Limitations for Carcinogenesis Research. Natl Cancer Inst., Monogr 65: 129-137. Hock, C. C. and Hock, H. T. (2007). Evaluating the Boundary Conditions of the Technology Acceptance Model: An Exploratory Investigation. ACM Transactions on Computer-Human Interaction. 14(2). Hu, P.J., Chau, P.Y.K., Sheng, O.R.L., & Tam, K.Y. (1999). Examining the technology acceptance model using physical acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91-112. Julius Adams Stratton and Loretta H. Mannix, Mind and Hand: The Birth of MIT (Cambridge: MIT Press, 2005), 190-92. Karahanna, E. (1993). Evaluative Criteria and User Acceptance of End-User Information Technology: A study of End-User Cognitive and Normative Pre-Adoption Beliefs. Karahanna, E., Straub, D. W., and Chervany, N. L. (1999). Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs. MIS Quaterly 23(2). Kavanagh, A. M. et al. (2011). Sources, Perceived Usefulness and Understanding of information Disseminated to Families Who Entered Home Quarantine During the H1N1 Pandemic in Victoria, Australia: A Cross-Sectional Study. BMC Infectious Diseases, 11(2). Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13 (2), 205-223. Landry, B.J.L., Griffith, R. , & Hartman, S. (2006). Measuring student perceptions of blackboard using the technology acceptance model. Decision Sciences, 4(1), 87-99. Leclerq, A. (2007). The Perceptual Evaluation Information Systems Using the Construct of User Satisfaction: Case Study of a Large French Group. The Database for Adavnces in Information Systems. 38(2): 27-60. Leavitt, H. & Whisler, T. (1958). Management in the 1980’s. Harvard Business Review, November-December, 1958. p.41-48. Lee, P. C. B., Wan, G. (2010). Including Subjective Norm and Technology Trust in the Technology Acceptance Model: A case of e-ticketing in China. The Database for Advances in Information Systems. 41(4). Leech, J.A., Wilby, K., McMullen, E., Laporte, K. (1996). The Canadian Human Activity Pattern Survey: report of methods and population surveyed. Chronic Dis Can 17(3–4):118–123. Leech, N. L. & Onwuegbuzie, A. J. (2005). On Becoming a Pragmatic Researcher: Importance of Combining Quantitative and Qualitative Research Methodologies. International Journal of Social. Research Methodology, 8(5): 375-387 Leidner, D. E. & Jarvenpaa, S. L. (1995). The Use of Information Technology to Enhance Management School Education: A Theoretical View. MIS Quarterly. 19(3): 265. Leidner, D.E. & Jarvenpaa, S.L. (1993). The information age confronts education: case studies on electronic classrooms, Information Systems Research, 4, 24-55. Lipponen, K., Hakkarainen, L., & Jarvela, S. (2002). Epistemology of inquiry and computer-supported collaborative learning. CSCL2: Carrying forward the conversation. pp. 129-156. Lipponen, L. (2002). Exploring Foundations for Computer-Supported Collaborative Learning. CSCL. Pp.72-78. Longley, Dennis, Shain, Michael (1985). Dictionary of Information Technology (2 ed.), Macmillan Press, p. 164. Macek, J. (2007).Defining Cyberculture. Masaryk University Press. pp. 35-65. Maslin, M. (2007). Technology Acceptance Model and E-learning. 12th International Conference on Education, Sultan Hassanal Bolkiah Institute of Education University Brunei Darussalam. Mathieson, K. (1991). Predicting user intentions:comparing the technology acceptance model with theory of planned behavior. Infromation Systems Research, 2(3), 173-191. Menkhoff, T., Thang, T. Y., Chay, Y. W., and Wong, Y. K. (2011). Engaging knowledge management learners through web-based ICT: an empirical study. The Journal of Information and Knowledge Management System. 41(2): 132-151. Money, W., Turner, A. (2004). Application of the Technology Acceptance Model to a Knowledge Management System, Proceedings of the 37th Hawaii International Conference on System Sciences (HICSS'04). Moore, G.C. & Benbasat, I. (1991). Development of an Instrument to Measure Perceptions of Adopting an Information Technology Innovation. Information Systems Research, 2 (3), 192-222. Morris, M.G., & Dillon, A. (1997). The influence of user perceptions on software utilization: application and evaluation of a theoretical model of technology acceptance, IEEE Software, 14(4), 56-75. Mostafa, M. R. (2008). Evaluation of the Implementation, Use and Effect of A Computerized Management Information System In College of Business Utara Malaysia. Nunnally, J.C. (1978). Psychometric Theory, (2nd ed.). New York: McGraw-Hill. Piazza, F. J. (2009). Factor influencing the perceive of usefulness of an information delivery website among the united state residents viewership. Pallant, J. (2001). SPSS Survival Manual: A step by step guide to data analysis using SPSS for windows (Version 10). Illinois, USA: Allen & Unwin. Pallant, J. (2005). SPSS Survival Manual. Milton Keynes: Open University Press. Raafat, G. S., Kira, D. (2007). Mediating the Impact of Technology Usage on Perceived Ease of Use by Anxiety. Computers & Education. 49(4): 1189-1204. Ramayah, T. (2002). Impact of Perceived usefulness, Perceived ease of use and Perceived Enjoyment on Intention to shop online. Rawstorne, P., Jayasuriya, R. and Caputi, P. (1998). An Integrative Model of Information Ststems Use in Mandatory Environments. Proceedings of the nineteenth International Conference on Information Systems. Pp. 325-330. Riedel, R., Fransoo, J.C. and Wiers, V.C.S. (2006). Modelling dynamics in decision support systems. In: R.N. Piekaar, E.A.P. Koningsveld and P.J.M. Settels, Proceedings IEA 2006 Congress. Rivard, S. (1988). Factors for success for end-user computing. Communications of the ACM 31(5): 552-561. Ronen. M., Kohen-Vacs, D., & Raz-Fogel, N. (2006). Structuring, Sharing and Reusing Asynchronous Collaborative Pedagogy. ICLS. Rose, J. and Forgarty, G. (2006). Determinants of Perceived Usefulness and Perceived Ease of Use In The Technology Acceptance model: Senior Consumers’ Adoption of Self-Service Banking Technologies. Academy of World Business, Marketing & Management Development Conference Proceedings, 2(10). Sekaran, U. (2009). Research Methods for Business: A Skills-Building Approach. (6th Ed). New York: John Wiley & Sons, Inc. Stiegler, Bernard (1998). Technics and Time, 1: The Fault of Epimetheus. Stanford University Press. pp. 17, 82. Sun, H. (2005). Causal Relationships between Perceived Enjoyment and Perceived Ease of Use: An Alternative Approach. Journal of the Association for Information System 1:85-87. Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92. Tabachnick, B. G., & Fidell, L.S. (1996). Using multivariate statistics (3rd Ed.). New York: HarperCollins. Tabachnick, B.G., & Fidell, L.S. (2001). Using Multivariate Statistics (4th ed.). Needlam Heights, MA: Allyn and Bacon. Taylor, S., & Todd, P. A. (1995). Assessing IT Usage: The Role of Prior Experience. MIS Quarterly. 19 (4), 561-570. Venkatesh, V. and Davis, F.D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27 (3). Venkatesh, V. and Davis, F.D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46 (2), pp. 186-204.