Innovation attributes and pedagogical quality: A concretization of joint theories on course management systems acceptance

Quality and Quantity

Volumn 47, Issue 4, 2013, Pages 2309-2317

  Lin, Shinyi ^a   Chen, Shueh Fen ^b,c  

^a NATIONAL TAICHUNG UNIVERSITY OF EDUCATION   (Taiwan)

^b CHING KUO INSTITUTE OF MANAGEMENT AND HEALTH   (Taiwan)

^c NATIONAL TAIWAN NORMAL UNIVERSITY   (Taiwan)

Author keywords

Course management systems; Innovation Diffusion Theory; Pedagogical quality; Self efficacy; Technology Acceptance Model

Indexed keywords

EID: 84874987680     PISSN: 00335177     EISSN: 15737845     Source Type: Journal    
DOI: 10.1007/s11135-011-9657-0     Document Type: Article

References (45)

1. Akers, E. J.: A study of the adoption of digital government technology as public policy in the American states. Ph. D. Dissertation, Auburn University Montgomery, Montgomery, Alabama (2006).
2. Bagozzi R. P., Davis F. D., Warshaw P. R.: Development and test of a theory of technological learning and usage. Hum. Relat. 45(7), 660-686 (1992). doi: 10. 1177/001872679204500702.
3. Barley S.: What can we learn from the history of technology?. J. Eng. Technol. Manag. 15, 237-255 (1998).
4. Braak V. J.: Factors influencing the use of computer mediated communication by teachers in secondary schools. Comput. Educ. 36(1), 41-57 (2001).
5. Braak V. J., Tearle P.: The computer attributes for learning scale (CALS) among university students: scale development and relationship with actual computer use for learning. Comput. Hum. Behav. 23(6), 2966-2982 (2007).
6. Brown S.: From VLEs to learning webs: the implications of Web 2. 0 for learning and teaching. Interact. Learn. Environ. 18(1), 1-10 (2010). doi: 10. 1080/10494820802158983.
7. Compeau D., Higgins C. A., Huff S.: Social cognitive theory and individual reactions to computing technology: a longitudinal study. MIS Q. 23(2), 145-158 (1999).
8. Dalsgaard, C.: Pedagogical quality in e-learning-designing e-learning from a learning theoretical approach. e-Learn. Educ. 1(1) (2005). http://eleed. campussource. de/archive/1/78/. Accessed 14 March 2011.
9. Davis F. D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319-340 (1989).
10. Davis F. D., Bagozzi R. P., Warshaw P. R.: User acceptance of computer technology: a comparison of two theoretical models. Manag. Sci. 35, 982-1003 (1989).
11. Dishaw M. T., Strong D. M.: Extending the technology acceptance model with task-technology fit constructs. Inf. Manag. 36(1), 9-21 (1999).
12. Fulk J., Gould J. J.: Features and contexts in technology research: a modest proposal for research and reporting. J. Comput. Mediat. Commun. 14(3), 764-770 (2009). doi: 10. 1111/j. 1083-6101. 2009. 01469. x.
13. Gray V.: Competition, Emulation, and Policy Innovation. CQ Press, Washington, DC (1994).
14. Hamuy E., Galaz M.: Information versus communication in course management system participation. Comput. Educ. 54(1), 169-177 (2010). doi: 10. 1016/j. compedu. 2009. 08. 001.
15. Hong J.-C., Hwang M.-Y., Hsu H.-F., Wong W.-T., Chen M.-Y.: Applying the technology acceptance model in a study of the factors affecting usage of the Taiwan digital archives system. Comput. Educ. 57(3), 2086-2094 (2011). doi: 10. 1016/j. compedu. 2011. 04. 011.
16. Igbaria M., Iivari J.: The effects of self-efficacy on computer usage. Omega 23(6), 587-605 (1995).
17. Jacobsen, D. M.: Examining technology adoption patterns by faculty in higher education. Paper presented at the proceedings of ACEC2000: learning technologies, teaching and the future of schools, Melbourne, Australia, 6-9 July 2000.
18. Lau S.-H., Woods P. C.: Understanding learner acceptance of learning objects: the role of learning object characteristics and individual differences. Br. J. Educ. Technol. 40(6), 1059-1075 (2009).
19. Liu I. F., Chen M. C., Sun Y. S., Wible D., Kuo C.-H.: Extending the TAM model to explore the factors that affect intention to use an online learning community. Comput. Educ. 54(2), 600-610 (2010). doi: 10. 1016/j. compedu. 2009. 09. 009.
20. Ma Q., Liu L.: The technology acceptance model: a meta-analysis of empirical findings. J. Organ. End User Comput. 16(1), 59-72 (2004).
21. Malikowski S. R., Thompson M. E., Theis J. G.: External factors associated with adopting a CMS in resident college courses. Internet High. Educ. 9(3), 163-174 (2006). doi: 10. 1016/j. iheduc. 2006. 06. 006.
22. Malikowski S. R., Thompson M. E., Theis J. G.: A model for research into course management systems: bridging technology and learning theory. J. Educ. Comput. Res. 36(2), 149-173 (2007).
23. Martín-Blas T., Serrano-Fernández A.: The role of new technologies in the learning process: Moodle as a teaching tool in physics. Comput. Educ. 52(1), 35-44 (2009). doi: 10. 1016/j. compedu. 2008. 06. 005.
24. Mintrom M.: Policy entrepreneurs and the diffusion of innovation. Am. J. Political Sci. 41(3), 738-770 (1997).
25. Morgan, G.: Faculty Use of Course Management Systems (vol. 2). EDUCAUSE Center for Applied Research, Boulder (May 20, 2003).
26. Nass C., Mason L.: On the Study of Technology and Task: A Variable-Based Approach. Sage, Newbury Park (1990).
27. Naveh G., Tubin D., Pliskin N.: Student LMS use and satisfaction in academic institutions: the organizational perspective. Internet High. Educ. 13(3), 127-133 (2010). doi: 10. 1016/j. iheduc. 2010. 02. 004.
28. Oh S., Ahn J., Kim B.: Adoption of broadband Internet in Korea: the role of experience in building attitudes. J. Inf. Technol. 18(4), 267-280 (2003).
29. Park, N., Lee, K. M., Cheong, P. H.: University instructors' acceptance of electronic courseware: an application of the technology acceptance model. J. Comput. Mediat. Commun. 13(1), article 9 (2007).
30. Picciano A.: Beyond student perceptions: issues of interaction, presence, and performance in an online course. J. Asynchronous Learn. Netw. 6(1), 21-40 (2002).
31. Pintrich P. R., De Groot E.: Motivational and self-regulated learning components of classroom academic performance. J. Educ. Psychol. 82, 33-40 (1990).
32. Rogers E. M.: Diffusion of Innovations, 4th edn. Free Press, New York (1995).
33. Romero C., Ventura S., García E.: Data mining in course management systems: Moodle case study and tutorial. Comput. Educ. 51(1), 368-384 (2008). doi: 10. 1016/j. compedu. 2007. 05. 016.
34. Sánchez R. A., Hueros A. D.: Motivational factors that influence the acceptance of Moodle using TAM. Comput. Hum. Behav. 26(6), 1632-1640 (2010). doi: 10. 1016/j. chb. 2010. 06. 011.
35. Sanchez-Franco M. J.: WebCT-the quasimoderating effect of perceived affective quality on an extending technology acceptance model. Comput. Educ. 54(1), 37-46 (2010). doi: 10. 1016/j. compedu. 2009. 07. 005.
36. Selim H. M.: An empirical investigation of student acceptance of course websites. Comput. Educ. 40(4), 343-360 (2003).
37. Shea P., Bidjerano T.: Learning presence: towards a theory of self-efficacy, self-regulation, and the development of a communities of inquiry in online and blended learning environments. Comput. Educ. 55(4), 1721-1731 (2010). doi: 10. 1016/j. compedu. 2010. 07. 017.
38. Snelbecker G. E.: Some thoughts about theories, perfection, and instruction. In: Reigeluth, C. M. (ed.) Instructional-Design Theories and Models. A New Paradigm of Instructional Theory, vol. II, pp. 31-47. Lawrence Erlbaum Associates, Mahwah (1999).
39. Straub E. T.: Understanding technology adoption: theory and future directions for informal learning. Rev. Educ. Res. 79(2), 625-649 (2009). doi: 10. 3102/0034654308325896.
40. Sungur S., Tekkaya C.: Effects of problem-based learning and traditional instruction on self-regulated learning. J. Educ. Res. 99(5), 307-317 (2006).
41. Tabata L. N., Johnsrud L. K.: The impact of faculty attitudes toward technology, distance education, and innovation. Res. High. Educ. 49(7), 625-646 (2008). doi: 10. 1007/s11162-008-9094-7.
42. Teo T.: A path analysis of pre-service teachers' attitudes to computer use: applying and extending the technology acceptance model in an educational context. Interact. Learn. Environ. 18(1), 65-79 (2010). doi: 10. 1080/10494820802231327.
43. Terzis V., Economides A. A.: The acceptance and use of computer based assessment. Comput. Educ. 56(4), 1032-1044 (2011). doi: 10. 1016/j. compedu. 2010. 11. 017.
44. Trotter, A.: Blackboard vs. Moodle. Education Week's Digital Directions, 21 (2008).
45. Wadsworth L. M., Husman J., Duggan M. A., Pennington M. N.: Online mathematics achievement: effects of learning strategies and self-efficacy. J. Dev. Educ. 30(3), 6-14 (2007).