tojde Turkish Online Journal of Distance Education 1302-6488 Anadolu University 10.17718/tojde.52605 Student Satisfaction Process In Virtual Learning System: 
Considerations Based In Information And Service Quality From Brazil’s Experience Fábio Nazareno MACHADO-DA-SILVA Machado-da-sılva Fábio Nazareno Meırelles Fernando De Souza Fılenga Douglas Fılho Marino Brugnolo 09 01 2014 15 3 122 142 02 27 2015 Copyright © 2000, Turkish Online Journal of Distance Education 2000 Turkish Online Journal of Distance Education

Distance learning has undergone great changes, especially since the advent of the Internet and communication and information technology. Questions have been asked following the growth of this mode of instructional activity. Researchers have investigated methods to assess the benefits of e-learning from a number of perspectives. This survey assesses the associations among the system quality, information quality, and service quality on student satisfaction and use of systems in virtual learning environments using the e-learning success model adapted by Holsapple and Lee-Post from the Delone and McLean (1992, 2003) model as a theoretical basis. The survey was carried out by means of an online program offered to 291 students from public and private institutions from several regions of Brazil. Confirmatory Factor Analysis and Structural Equation Modeling were used for data analysis in order to understand the student satisfaction process in virtual learning system. Findings show that variations in system quality, information quality, and service quality influence the use of the system, and the User Satisfaction construct had 89% of variance explained by Information Quality and Service Quality. Many of the benefits of distance learning programs are related to students’ satisfaction and the intensity with which they make use of the learning system. With awareness of the indicators that are antecedents of these variables, education executives can plan investments that meet the most significant demands and use the information to deal with one of the major problems in distance learning: the dropout rate. Future researches should study this subject longitudinally.

 Distance Education; Student Satisfaction; Quality in e-Learning Byrne, R. (2002). Web-based learning versus traditional management development methods. Singapore Management Review, v. 24, n. 2, p. 59-68. Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perception and behavioral impact. International Journal of Man-Machine-Studies, v. 38, n. 3, p. 475–487. Delone, W. H. and McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, v. 3, n. 1, p. 60–86. Delone, W. H. and McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, v. 19, n. 4, p. 9–30. Demo, P. (1995). Metodologia Científica em Ciências Sociais. São Paulo: Atlas. Dennis, A. R., Wixom, B. H., and Roth, R. M. (2006). Systems analysis and design. Hoboken: John Wiley & Sons. Farias, S. A and Santos, R. C. (2000). Modelagem de Equações Estruturais. RAC, v. 4, n. 3, p. 107-132. Fink, A. (1995a). How to design surveys. The Survey ed. Thousand Oaks: Sage. FINK, A. (1995b). The survey handbook. The Survey ed. Thousand Oaks: Sage. Fornell, C. and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, v. 18, p. 39– Hair, J. F. et al. (1998). Multivariate data analysis. 5. ed. New Jersey: Prentice Hall. Hancock, G. R. and Mueller, R. O. (2006). Structural equation modeling: A second course. Greenwich, CT: Information Age Publishing. Holsapple, C. W. and Lee-Post, A. (2006). Defining, assessing, and promoting e-learning success: An information systems perspective. Decision Sciences Journal of Innovative Education, v. 4, No, p. 18. Jewett, F. (1998). Case studies in evaluating the benefits and costs of mediated and distributed leaning. In: Proceedings Of The 3rd Annual Conference of The Telelearning Network Of Centers of Excellence. Annals. Vancouver, Canada. Jing, I. et al. (2002). Effects of different types of interaction on learning achievement, satisfaction and participation in web-based instruction. Innovations in Education and Teaching International, v. 39(2), p. 153–162. Kavanagh, M. J. and Thite, M. (2009). Human resource information systems: basics, applications, and future directions. Los Angeles: Sage. Kelly, P. (2011). Web 2.0-based e-learning: Applying social informatics for tertiary teaching. Open Learning, v. 26, n. 3, p. 280-283. Kline, R. B. (1998). Principles and practice of structural equation modeling. New York: The Guilford Press. Lawhead, P. B. et al. (1997). The Web and distance learning: What is appropriate and what is not. ITiCSE’97 Working Group Reports and Supplemental Proceedings, p. 27–37. Lemke, C. (2005). Modelos de Equações Estruturais com Ênfase em Análise Fatorial Confirmatória no Software AMOS. Universidade Federal do Rio Grande do Sul - [S.l.]. 200 Lee-Post, A. (2009). E-learning Success Model: an information systems Perspective. Electronic Journal of e-learning, v. 7, n. 1, p. 61-70. Liaw, S. S. et al. (2006). Attitudes toward search engines as a learning assisted tool: approach of Liaw and Huang’s research model. Computers in Human Behavior, v.22, p. 177–190. Liaw and Huang, H. M. (2003). An investigation of user attitudes toward search engines as an information retrieval tool. Computers in Human Behavior, v. 19, p. 751–765. Lin, H. F. (2007). Measuring online learning systems success: applying the updated DeLone and McLean model. Cyber Psychology & Behavior, v. 10, n. 6, p. 817–820. Maroco, J. (2010). Análise de Equações Estruturais: Fundamentos teóricos, software e aplicações. Report Number: Pêro Pinheiro. Marterns, M. P. and Haase, R. F. (2006). Advanced applications of structural equation modeling in counseling psychology research. The Counseling Psychologist, v. 34, n. 6, p. 878–911. Maruyama, G. M. et al. (1998). Basics of Structural Equation Modeling. Sage Publications ed. London: [s.n.]. Mason, R. and Rennie, F. (2006). Elearning: The key concepts. London; New York: Routledge, p. xxxviii, 158 p. McClelland, B. (2001). Digital learning and teaching: Evaluation of developments for students in higher education. European Journal of Engineering Education, v. 26, n. 2, p. 107–115. Motiwallo, L. and Tello, S. (2000). Distance learning on the Internet: An exploratory study. The Internet and Higher Education, v. 2, n. 4, p. 253–264, 2000. Mueller, D. and Strhmeier, S. No Title. (2011). Computers & Education, v. 57, p. 2505– 25 Mueller and Zimmermann, V. (2009). A learner-centered design, implementation, and evaluation approach of learning environments to foster acceptance. International Journal of Advanced Corporate Learning, v. 2, n. 3, p. 50–57. Owston, R. D. and Wideman, H. H. (1998). Teacher factors that contribute to the implementation success in telelearning network. Center for the Study of Computers in Education Technical Report 98-3. Toronto, Canada: Faculty of Education, York University. Ozkan, S. and Kösler, R. (2009). Multi-dimensional students’ evaluation of e-learning systems in the higher education context: an empirical investigation. Computers & Education, v. 53, n. 4, p. 1285–1296. Pinsonneault, A. and Kraemer, K. L. (1993). Survey research in management information systems: An assessment. Journal of Management Information System. Pittinsky, M. and Chase, B. (2000). Quality on the line: Benchmarks for success in Internet-based distance learning. The Institute for Higher Education Policy. Washington, DC: National Education Association: [s.n.]. Poelmans, S. et al. (2012). Usability and acceptance of e-learning in statistics education, based on the compendium platform. In Proceedings of the International Conference of Education, Research and Innovation (p. 1–10), 2008. Available at the following address http://www.wessa.net/download/iceripaper1.pdf Accessed: Nov, 13th. Rosenberg, M. J. (2001). E-learning: Strategies for delivering knowledge in the digital age. New York: McGraw-Hill, p. xxiv, 344. Roca, J. C., Chiu, C. M., and Martinez, F. J. (2006). Understanding e-learning continuance intention: an extension of the technology acceptance model. International Journal of Human-Computer Studies, v. 64, p. 683–696. Savenye, W. C.; Olina, Z., and Niemczyk, M. (2001). So you are going to be an online writing teacher: Issues in designing, developing, and delivering an online course. Computers and Composition, v. 18, n. 1, p. 371–385. Seddon, P. B. A. (1997). respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, v. 8, n. 3, p. 240–253. Shee, D. and WANG, Y. (2008). Multi-criteria evaluation of the web-based e-learning system: a methodology based on learner satisfaction and its applications. Computers & Education, v. 50, n. 3, p. 894-905. Sitzmann, T. et al. (2006). The comparative effectiveness of web-based and classroom instruction: a meta-analysis. Personnel Psychology, v. 59, p. 623-664. Smith, L. J. (2001). Content and delivery: A comparison and contrast of electronic and traditional MBA marketing planning courses. Journal of Marketing Education, v. 23, n. 1, p. 35–44. Sommerville, I. (2007). Engenharia de software. 8. ed. São Paulo: Pearson Addison- Wesley. TEH, G. P. L. (1999). Assessing student perceptions of Internet-based online learning environment. International Journal of Instructional Media, v. 26, n. 4, p. 397-402. Van Aken, J. E. (2005). Management research as a design science: articulating the research products of mode 2 knowledge production in management. British Journal of Management, v. 16, n. 1, p. 19–36. Venkatesh, V.; BALA, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, v. 39, n. 2, p. 273–315. Wang, Y. S. (2003). Assessment of learner satisfaction with asynchronous electronic learning systems. Information & Management, v. 41, p. 75-86. Wang, Wang, H. Y., and Shee, D. Y. (2007). Measuring e-learning systems success in an organizational context: Scale development and validation. Computers in Human Behavior, v. 23, p. 1792–1808. Wang, W. T. and Wang, C. C. (2009). An empirical study of instructor adoption of web- based learning systems. Computers & Education, v. 53, p. 761-774. Wu, J.H., & Wang, Y. M. (2006). Measuring KMS success: a respecification of the DeLone and McLean‟s model. Information & Management, 43(6), 728-739. Yeung, P. and Jordan, E. (2007). The continued usage of business e-learning courses in Hong Kong corporations. Education and Information Technologies, v. 12, n. 3, p. 175-188.