Effects of user and system characteristics on perceived usefulness and perceived ease of use for the web-based classroom response system

Turkish Online Journal of Educational Technology

Volumn 11, Issue 3, 2012, Pages 128-143

  Sun, Huey Min ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84863682952     PISSN: None     EISSN: 13036521     Source Type: Journal    
DOI: None     Document Type: Article

References (54)

1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
2. Arbuckle, J. L. (1995). Amos 6.0 User's Guide.
3. Arenas-Gaitán, J., Ramírez-Correa, P. E., Rondán-Cataluña, F. J. (2011). Cross cultural analysis of the use and perceptions of web Based learning systems, Computers & Education, 57(2), 1762-1774.
4. Bandura, A. (1997). Self-Efficacy: The Exercise of Control. New York: Freeman and Company.
5. Brancheau, J. C. & Wetherbe, J. C. (1990). The adoption of spreadsheet software: testing innovation diffusion theory in the context of end-user computing. Information Systems Research, 1(2), 115-143.
6. Cawthon, N. & Moere, A. V. (2007). The Effect of Aesthetic on the Usability of Data Visualization. International Conference Information Visualization, 637-648.
7. Chen, H.-R. & Tseng, H.-F. (2012). Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan, Evaluation and Program Planning, 35(3), 398-406.
8. Chittaro, L. & Ranon, R. (2007). Web 3D technologies in learning, education and training: motivations, issues, opportunities. Computers & Education, 49(1), 3-18.
9. Choy, S.O., Ng, S. C., & Tsang, Y. C. (2005). Software Agents to Assist in Distance Learning Environments. EDUCAUSE Quarterly Magazine, 28(2), 34-40.
10. Christopher, D. M. & Hinrich, S. (1999). Foundations of Statistical Natural Language Processing. MIT Press.
11. Chunga, J. & Tan, F. B. (2004). Antecedents of computer playfulness: an exploratory study on user acceptance of general information-searching websites. Information & Management, 41(7), 869-881.
12. Dagiene, V. & Futschek, G. (2008). Bebras International Contest on Informatics and Computer Literacy: Criteria for Good Tasks, Informatics Education-Supporting Computational Thinking. Lecture Notes in Computer Science (Vol.5090, pp.19-30).
13. Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
14. Davis, S. A. & Bostrom, R. P. (1992). An experimental investigation of the roles of the computer interface and individual characteristics in learning of computer systems. International Journal of Human-Computer Interaction, 4, 143-172.
15. Drave, W. A. (2000). Teaching online LERN Books. Wisconsin: River Falls.
16. Ferrington, G. & Loge, K. (1992). Virtual reality: a new learning environment. The Computing Teacher, 19(7), 16-19.
17. Fies, C. & Marshall, J. (2006). Classroom Response Systems: A Review of the Literature. Journal of Science Education and Technology, 15(1), 101-109.
18. Fishbein, M. & Ajzen, I. (1975) Belief Attitude, Intention and Behavior: An Introduction to Theory and Research. MA: Addison-Wesley.
19. Gok, T. (2011). An Evaluation of Student Response Systems from the Viewpoint of Instructors and Students, The Turkish Online Journal of Educational Technology, 10(4), 67-83.
20. Gururajan, R. & Fink, D. (2002). A study of influences of application interfaces on end user training outcomes. Informing Science and IT Education Conference, Cork, Ireland.
21. Ha, L. & James, E. L. (1998). Interactivity reexamined: a baseline analysis of early business web sites. Journal of Broadcasting and Electronic Media, 42(4), 457-474.
22. Hasan, B. (2006). Delineating the effects of general and system-specific computer self-efficacy beliefs on IS acceptance. Information & Management, 43(5), 565-571.
23. Hasan, B. & Ahmed, M. U. (2007). Effects of interface style on user perceptions and behavioral intention to use computer systems. Computers in Human Behavior, 23, 3025-3037.
24. Hoffman, D. L. & Novak, T. P. (1997). A New Marketing Paradigm for Electronic Commerce. The Information Society, 13(1), 43-45.
25. Hair, J., Anderson, R., Tatham, R., & Black, W. (1998). Multivariate Data Analysis 5th ed. Upper Saddle River: Prentice Hall.
26. Holmes, J. (2007). Designing agents to support learning by explaining. Computers & Education, 48(4), 523-547.
27. Kim, J. H., Park, S. T., Lee, H., Yuk, K. C., & Lee, H. (2001). Virtual reality simulations in physics education. Interactive Multimedia Electronic Journal of Computer-Enhanced Learning. Available from http://imej.wfu.edu/articles/2001/2/02/printver.asp
28. 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.
29. Lewis, W., Agarwal, R. & Sambamurthy, V. (2003). Sources of influence on beliefs about information technology use: an empirical study of knowledge workers. MIS Quarterly, 27(4), 657-678.
30. Lin, W.-S. (2012). Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives, International Journal of Human-Computer Studies, Available online 14 February 2012, 10.1016/j. ijhcs.2012.01.006.
31. Liu, I.-F., Chen, M. C., Sun, Y. S., Wible, D., Kuo, C.-H. (2010). Extending the TAM model to explore the factors that affect Intention to Use an Online Learning Community. Computers & Education, 54, 600-610.
32. Liu, S. H., Liao, H. L., & Peng, C.J.(2005). Applying the Technology Acceptance Model and Flow Theory to Online E-Learning Users' Acceptance Behavior. Issues in Information Systems, 6(2), 175-181.
33. Lowery, R. C. (2005). Teaching and Learning with Interactive Student Response Systems: A Comparison of Commercial Products in the Higher-Education Market. Annual meeting of the Southwestern Social Science Association, New Orleans.
34. 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.
35. Ong, S. K. & Mannan, M. A. (2004). Virtual reality simulations and animations in a web-based interactive manufacturing engineering module. Computers & Education, 43(4), 361-382.
36. Park, S. Y. (2009). An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use e-Learning. Educational Technology & Society, 12(3), 150-162.
37. Park, Y., Son, H., Kim, C. (2012). Investigating the determinants of construction professionals' acceptance of web-based training: An extension of the technology acceptance model. Automation in Construction, 22, 377-386.
38. Preece, J. (2000). Online communities: designing usability, supporting sociability. Chichester, UK: John Wiley & Sons.
39. Preszler, R. W., Dawe, A., Shuster, C. B., & Shuster, M. (2007). Assessment of the effects of student response systems on student learning and attitudes over a broad range of biology courses. CBE-Life Sciences Education, 6(1), 29-41.
40. Rogers, E. M. (1995). Diffusion of Innovations. New York: The Free Press.
41. Schepers, J., & Wetzels, M. (2006). Technology acceptance: a meta-analytical view on subjective norm. In Proceedings of the 35th European Marketing Academy Conference, Athens, Greece.
42. Schepers, J. & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44(1), 90-103.
43. Sanchez-Guzman, D. & Cesar Mora, R. G.(2009). Intelligent Agents: A Physics Education Opportunity in Latin-America. Lat. Am. Journal of Phys. Educ. 3(2), 253-258.
44. Seal, K. C. & Przasnyski, Z. H. (2001). Using the World Wide Web for teaching improvement. Computers & Education, 36(1), 33-40.
45. Seletsky, O. B. (2009). Developing an Improved, Web-Based Classroom Response System with Web Services. Dartmouth Computer Science Technical Report TR2009-651
46. Sheremetov, L. & Arenas, A. G. (2002) EVA: an interactive Web-based collaborative learning environment. Computers & Education, 39(2), 161-182.
47. Shyu, S. H.-P. & Huang, J.-H. (2011). Elucidating usage of e-government learning: A perspective of the extended technology acceptance model, Government Information Quarterly, 28(4), 491-502.
48. Siau, K., Sheng, H., & Nah, F. F. (2006). Use of a Classroom Response System to Enhance Classroom Interactivity. IEEE Transactions on education, 49(3), 398-403.
49. Sun, H.-M. & Cheng, W.-L. (2009). The Input-interface of Webcam Applied in 3D Virtual Reality Systems, Computers and Education, 53(4), 1231-1240.
50. Trindade, J., Fiolhais, C., & Gil, V. (1999). Virtual Water, an application of virtual environments as an education tool for physics and chemistry. Proceedings of ICCE 99: international conference on computers in education (vol. 2, pp. 655-658).
51. Tucker, S. P. (2008). E-commerence standard user interface: an E-menu system. Industrial Management & Data systems, 108(8), 1009-1028.
52. Woszczynski, A. B., Roth, P. L. & Segars, A. H. (2002). Exploring the theoretical foundations of playfulness in computer interactions. Computers in Human Behavior, 18(4), 369-388.
53. Yi, M. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management, 43(3), 350-363.
54. 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), 431-449.