Abstract
The purpose of this study was to examine the relationships between students’ computer self-efficacy, intrinsic motivation, attitude, and satisfaction in blended learning environments. The participants were 239 college students enrolled at Hubei University in China. A survey including four existing instruments was used for data collection. The results of structural equation modeling analysis suggested students’ attitudes toward online and face-to-face classes were the most influential toward to satisfaction in blended learning environments. Higher levels of intrinsic motivation were seen to be influential toward satisfaction in blended learning environments. Computer self-efficacy was seen to influence intrinsic motivation and attitudes, but not found to influence satisfaction in blended learning environments.
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References
Garrison, D.R., Kanuka, H.: Blended learning: Uncovering its transformative potential in higher education. Internet High. Educ. 2, 95–105 (2004)
Singh, H.: Building effective blended learning programs. Educ. Technol. 43(6), 51–54 (2003)
Osguthorpe, R.T., Graham, C.R.: Blending learning environments: definitions and directions. Q. Rev. Distance Educ. 3, 227–233 (2003)
Yang, H., Wang, S.: Cases on Online Learning Communities and Beyond: Investigations and Applications. Information Science Reference/IGI Global, Hershey (2012)
Yang, H., Wang, S.: Cases on e-Learning Management: Development and Implementation. Information Science Reference/IGI Global, Hershey (2012)
So, H.J., Brush, T.A.: Student perceptions of collaborative learning, social presence and satisfaction in a blended learning environment: relationships and critical factors. Comput. Educ. 51, 318–336 (2008)
Abrantes, J.L., Seabra, C., Lages, L.F.: Pedagogical affect, student interest, and learning performance. J. Bus. Res. 60, 960–964 (2007)
Wu, J.H., Tennyson, R.D., Hsia, T.L.: A study of student satisfaction in a blended e-learning system environment. Comput. Educ. 1, 155–164 (2010)
Deci, E.L., Ryan, R.M.: Intrinsic Motivation and Self-determination in Human Behavior. Plenum, New York (1985)
Ryan, R.M., Deci, E.L.: Self-determination theory and facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 55, 68–78 (2000)
Ryan, R.M., Deci, E.L.: Intrinsic and extrinsic motivations: classic definitions and new directions. Contemp. Educ. Psych. 25, 54–67 (2000)
Chao, C.Y., Chen, Y.T., Chuang, K.Y.: Exploring students’ learning attitude and achievement in flipped learning supported computer aided design curriculum: a study in high school engineering education. Comput. Appl. Eng. Educ. 4, 514–526 (2015)
Compeau, D.R., Higgins, C.A.: Computer self-efficacy: development of a measure and initial test. MIS Q. 19, 189–211 (1995)
Lim, C.K.: Computer self-efficacy, academic self-concept, and other predictors of satisfaction and future participation of adult distance learners. Am. J. Distance Educ. 2, 41–51 (2001)
Holley, D., Oliver, M.: Student engagement and blended learning: portraits of risk. Comput. Educ. 3, 693–700 (2010)
Ajzen, I., Fishbein, M.: Understanding Attitudes and Predicting Social Behavior. Prentice Hall, New Jersey (1980)
Lu, Y., Zhou, T., Wang, B.: Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Comput. Hum. Behav. 1, 29–39 (2009)
Teo, T.: Assessing the computer attitudes of students: an Asian perspective. Comput. Hum. Behav. 4, 1634–1642 (2008)
Mitchell, A., Honore, S.: Criteria for successful blended learning. Indust. Commer. Train. 3, 143–149 (2007)
Dahalan, N., Hassan, H., Atan, H.: Student engagement in online learning: learners attitude toward e-mentoring. Procedia-Soc. Behav. Sci. 67, 464–475 (2012)
Pintrich, P.R., De Groot, E.V.: Motivational and self-regulated learning components of classroom academic performance. J. Educ. Psych. 1, 33–40 (1990)
Akkoyunlu, B., Yılmaz-Soylu, M.: Development of a scale on learners’ views on blended learning and its implementation process. Internet High. Educ. 1, 26–32 (2008)
Bentler, P.M., Chou, C.P.: Practical issues in structural modeling. Sociol. Methods Res. 16(1), 78–117 (1987)
Gefen, D., Straub, D.W.: A practical guide to factorial validity using PLS-graph: tutorial and annotated example. Commun. Infor. Syst. 5, 91–109 (2005)
Chin, W.W.: The partial least squares approach to structural equation modeling. In: Marcoulides, G.A. (ed.) Modern Methods for Business Research, pp. 298–336. Erlbaum, New Jersey (1998)
Shevlin, M., Miles, J.N.: Effects of sample size, model specification and factor loadings on the GFI in confirmatory factor analysis. Pers. Indiv. Differ. 1, 85–90 (1998)
Fornell, C.D., Larcker, F.: Evaluating structural equation models with unobservable variables and measurement errors. J. Marketing Res. 2, 39–50 (1981)
Chatterjee, S., Hadi, A.S.: Regression Analysis by Example. Wiley, New York (2000)
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The work was supported by the Key Project of Philosophy and Social Science Research, Ministry of Education of China (14JZD044).
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Li, Y., Yang, H.H., Cai, J., MacLeod, J. (2017). College Students’ Computer Self-efficacy, Intrinsic Motivation, Attitude, and Satisfaction in Blended Learning Environments. In: Cheung, S., Kwok, Lf., Ma, W., Lee, LK., Yang, H. (eds) Blended Learning. New Challenges and Innovative Practices. ICBL 2017. Lecture Notes in Computer Science(), vol 10309. Springer, Cham. https://doi.org/10.1007/978-3-319-59360-9_6
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