STUDIES COURSE: COLLECTIVE EFFICACY, SELF-REGULATORY EFFICACY, FLOW, AND EXTENDED TAM PERSPECTIVE
Abstract
This study was conducted as a case study of a collective composition learning model (CCLM) based on computer assisted collaborative learning framework which was attempted in a university liberal arts convergence studies course in South Korea. CCLM is considered to be an important learning model in the realm of education technology. Accordingly, many educators are currently proposing various research models related to the CCLM based on computer assisted collaborative learning. Although convergence studies curriculum and correlated or relevant curriculum can be learned recently at universities in Korea which regard it as a very important discipline to the extent that it is classified as a learning model, there are still challenges to maximizing learning effect due to characteristics of science and engineering, liberal arts and heterogeneous group courses. In order to solve this problem, we produced the CCLM based on web and applied this to courses. While taking characteristics of each team into consideration, the researchers applied Jigsaw II model and proposed a level of difficulty and learning topics to each team. According to the results of an extended TAM model application measured after one semester was completed, web based CCLM had a positive effect on heterogeneous learning groups. These results show that web based CCLM can be applied effectively to both university education and various forms of heterogeneous group learning model.
Keywords Heterogeneous group learning, Collective composition model, Collective efficacy, Self-regulatory efficacy, Flow, Technology acceptance model
REFERENCES
Agarwal, R., & Karahanna,F. (2000). Time files when you are having fun: cognitive absorption and beliefs about information technology usage, MIS Quarterly, 24(4), 665-694.
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and Human decision Processers, 50 (2), 179-211.
Bandura, A. (1986),Social Foundations of Thought and Action: Asocial Cognitive Theory, Prentice-Hall, Englewood Cliffs, NJ.
Bandura, A. (1997).Self-efficacy: The Exercise of Control. W.H. Freeman and company. New York, NY.
Bandura, A.(2000). Exercise of human agency through collective efficacy. Current Directions in Psychological Science, 9, 75-78.
Barclay ,D., Higgins, C., & Thompson, R. (1995). The partial least squares approach to casual modeling: personal computer adoption and use as an illustration. Technology Studies,2, 285-309.
Bong, M.M.(1997). Self-efficacy and self-regulated learning: the implication of research related in education engineering. Journal of Educational Technology, 14(1), 97-118.
Carl, B., & Marlene, S. (1987). The Psychology of Writtern Composition. Lawrence Erlbaum Association, Publishers Hillscale, New Jersey.
Chen, G., Gully, M. S., & Eden, D. (2001). Validation of a new general self-efficacy scale. Organizational Research Methods, 4(1), 62-83.
Chin, W.W., & Copal, A. (1995). Adoption intention in GSS; Relative importance of belifes. The database for Advances in Information systems, 26 (2-3), 42-64.
Cohen, E.G (1994). Restructuring the Classroom: Conditions for productive small groups, Review of Educational Research, 64(1), 1-35.
Corno. L., & Mandinach, E.B. (1983). The role of congnitive engagement in learning from instruction, Educational Psychogist, 18, 88-108.
Csikszentmihalyi, M. (1991). Flow: The psychology of optimal experience. New York: Harper Perennial.
Davis, F.D. (1989). Perceived usefulness, Perceived ease of use, acceptance of information technology. MIS Quarterly,9, 319-340.
Eccles, J.S., Adler,T.F., Futterman., R et al.(1983). Expectancies, values, and academic behaviors. In J.T.Spence (Ed), Achievement and achievement motion (pp.75-146).San Francisco, CA; W.H. Freeman and Company.
Finneran, C. M., & Zhang, P (2003). A person-artefact-task(PAT) model of flow antecedents in computer-mediated environments. International Journal of Human computer Studies,59, 475-496.
Flower, L., & Hayes, J. R. (1981). "A Cognitive Process Theory of Writing" College Composition and Communication, 32, 4, 365-387.
Flower, L. (1990). “The Role of Task Presentation in Reading-to-Write”, Reading-To-Write; Exploring a Cognitive and Social Process, Oxford University Press.
Fornell, C., & Larker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-50.
Ghani, J.(1995). Flow in human computer interactions: Test of a model. New Jersey:Abix Publishing Corp.
Gibson, C.B., Randel, A.E., & Early, P.C. (2000). Understanding group efficacy, Group and Organization Management, 25(1), 67-97.
Gibson, C.B. (2001). Me and us: Differential relationships among goal-setting training, efficacy and effectiveness at the individual and team level. Journal of Organizational Behavior,22,789-556.
Gist. M. (1989). Effects of self-efficacy and post-training intervention on the acquisition and maintenance of complex interpersonal skills. Personnel Psychology, 44, 837-861.
Hayes .J, (1996). A New Framework for Understanding Cognition and affect in Writing, edited by C. Michel Levy, Sarah Ransdell, The Science of Writing. Lawrence Eraun Associates, Inc.
Igbaria, M. and Iivary, J.(1995), The effects of self-efficacy on computer usage, Omega : International Journal of Management Science, 23(6), 587-605.
Isman, A., Celikli, G. E. (2009). How does student ability and self-efficacy affect the usage of computer technology? The Turkish Online Journal of Educational Technology, 8 (1), 33-38.
Johnson. D. W., & Johnson, R.T. (1992), Positive interdependence: key to effective cooperation. In R. Hertz-Lazarowitz & N. Miller (Eds.), Interaction in cooperative groups. New York: Plenum Press.
Jonassen, D .H.(2006). Modelling with technology: Mind tools for conceptual change. Columbus,OH: Merill Prentice Hall.
Juul, J.(2002). The open and the Closed: Games of Emergence and Games of progression, in Computer games and Digital Cultures conference Proceeding, Tampere University Press, pp.323-329.
Latham, G. P., & Locke, E. A. (1991). Self-regulation through goal setting. Organizational Behavior and Human Decision Processes, 50, 212-247.
Lee, K.C., Kang,I.W., & Kim,J.S.(2007). Exploring the use interface of negotiation support systems from the uder acceptance perspective. Computer in human Behavior, 23, 220-239.
Lee. J. K., & Lee, W.K. (2008). The relationship of e-Leaner’s self regulatory efficacy and perception of e-learning environment al quality, Computer in Human Behavior, 24, 32-47.
Lent, R.W., Schmidt, J., Schmidt.L.(2006).Collective efficacy beliefs in student work teams: Relation to self-efficacy, cohesion, and performance, Journal of Vocational Behavior ,68, 73-84.
Li, D., & Brown, G.J. (2006). The role of need for cognition and mood on online flow experience, Journal of computer Information Systems, 46, 11-17.
Lu, Y., Zhou,T., & Bin W. (2009). Exploring Chinese user’ acceptance of instant messageing using the theory of planned behavior, the technology acceptance model, and the flow theory. Computer in Human Behavior, 23, 29-39.
Mevarech, Z.R. (1999). Effects of metacognitive training embedded in cooperative setting on mathematical proble solving, journal of Education Research, 2(94), 195-205.
Moberly. M.(2008). Composition, Computer Games, and the Absence of Writing, Computer and Composition, 284-299.
Moon, M.K, Jang.S.K, & Kim,T.Y. (2011).A computer-assisted learning model based on the digital game exponential reward system, The Turkish Online Journal of Educational Technology,10 (1), 1-14.
Norvak,T.P., Hofman, D.L.,& Young. Y-F.(2000). Measuring the customer experience in online environment: A structural modeling approach. Marketting Science,19(1), 22-42.
Nunally,J.C.(1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.
Oliver,R.L.(1993). Cognitive, affective, and attribute bases of the consequences of satisfaction. Journal of Applied Psychology, 6(2),179-189.
Prensky, M. (2001).Digital game-based learning, McGraw-Hill, USA.
Printrich,P.R., & Schunk,D.H.(2002). Motivation in education, Theory, research, and application (2nded.). Englewood Cliffs, NJ: Prentice-Hall.
Salomon, G. (1984). Television is "easy" and print is "tough": The differential investment of mental effort in learning as a function of perceptions and attributions. Journal of Educational Psychology, 76, 647-658.
Sanchez-Franco, M.J., Martinez-Lopez, Fco, J., & Martin-Velicia,F.A. (2009). Exploring the impact of individualism and uncertainty avoidance in Web-based electronic learning: An empirical analysis in Europian higher education. Computer & Education, 52(3), 588-598.
Seo, M.G., & Liies, R.(2009). The role of self-efficacy, goal, and affect in dynamic motivational self-regulation. Organizational behavior and Human Decision processes, 109, 120-133.
Vygotsky, L.S. (2007). Thought and language, Cambridge, MA: The MIT press.
Wang, S.H., (2008). The role feedback and self-efficacy on web-based learning: The social cognitive perspective. Computer Education, 51, 1588-1598.
Wang, S. L., & Lin, S.S.J. (2007). The effects of group composition of self-efficacy and collective efficacy on computer-supported collaborative learning, Computer in Human Behavior,23, 2256-2268.
Webb, N.M., & Palincsar A.S.(1996). Group processes in the classroom. In D. C. Berliner & R.C.Calfee (Eds.), Handbook of educational psychology (pp.841-843), New York: Simon & Schuster
Yi, M.Y, & Hwang, J.(2003) Predicting the use of Web-based information system: Self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model, International Journal of Human-Computer Studies, 59(4),431-449.
Zimmerman. B.J. (1990). Self-regulated learning and achievement: an overview, Educational Psychologist, 25(1), 5-17.
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