Abstract
Colleges and universities have focused on increasing the number of online courses and programs offered to remove the obstacles in terms of time and space. Partial Least Squares Structural Equation Modeling (SEM) is used to explore the relationships among the parameters. The results of this study indicate a positive relationship between perceived online learning environment and university students’ learning performance mediated by students’ engagement. Therefore, educators should develop online student engagement strategies in order to increase online student engagement. Furthermore, for improving online students’ learning performance, educators should invest their resources to develop a good online learning environment.
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References
Asunka, S.: Online learning in higher education in Sub-Saharan Africa: Ghanaian university students’ experiences and perceptions. Int. Rev. Res. Open Distrib. Learn. 9(3), 1–23 (2008)
Barnard-Brak, L., Paton, V.O., Lan, W.Y.: Profiles in self-regulated learning in the online learning environment. Int. Rev. Res. Open Distrib. Learn. 11(1), 61–80 (2010)
Bartsch, R.A., Cobern, K.M.: Effectiveness of PowerPoint presentations in lectures. Comput. Educ. 41(1), 77–86 (2003)
Boekarts, M., Pintrich, P.R., Zeidner, M. (eds.): Handbook of Self-Regulation: Theory, Research and Applications. Academic, San Diego (2000)
Brock, L.L., Nishida, T.K., Chiong, C., Grimm, K.J., Rimm-Kaufman, S.E.: Children’s perceptions of the classroom environment and social and academic performance: a longitudinal analysis of the contribution of the Responsive Classroom approach. J. Sch. Psychol. 46(2), 129–149 (2008)
Busato, V.V., Prins, F.J., Elshout, J.J., Hamaker, C.: Learning styles: a cross-sectional and longitudinal study in higher education. Br. J. Educ. Psychol. 68(3), 427–441 (1998)
Cangur, S., Ercan, I.: Comparison of model fit indices used in structural equation modeling under multivariate normality. J. Modern Appl. Stat. Methods 14(1), 14 (2015)
Carliner, S., Shank, P. (eds.): The E-Learning Handbook: Past Promises, Present Challenges. Wiley, Hoboken (2016)
Chauhan, A.: Massive open online courses (MOOCS): emerging trends in assessment and accreditation. Digit. Educ. Rev. 25, 7–17 (2014)
Cheong, I.A.: Educating pre-service teachers for a sustainable environment. Asia-Pacific J. Teach. Educ. 33(1), 97–110 (2005)
Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989)
Delen, E., Liew, J., Willson, V.: Effects of interactivity and instructional scaffolding on learning: self-regulation in online video-based environments. Comput. Educ. 78, 312–320 (2014)
Frederick, H.R.L.K.S.: Cracking the paradox of Chinese learners: looking into the mathematics classrooms in Hong Kong and Shanghai. How Chin. Learn Math.: Perspect. Insiders 1, 348 (2004)
Gan, C.L., Balakrishnan, V.: Enhancing classroom interaction via IMMAP–an interactive mobile messaging app. Telematics Inform. 34(1), 230–243 (2017)
Greene, T.G., Marti, C.N., McClenney, K.: The effort—outcome gap: differences for African American and hispanic community college students in student engagement and academic achievement. J. High. Educ. 79(5), 513–539 (2008)
Hair Jr., J.F., Hult, G.T.M., Ringle, C., Sarstedt, M.: A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications, Thousand Oaks (2016)
Hair, J.F., Sarstedt, M., Ringle, C.M., Mena, J.A.: An assessment of the use of partial least squares structural equation modeling in marketing research. J. Acad. Market. Sci. 40(3), 414–433 (2012)
Hu, L.T., Bentler, P.M.: Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Model.: Multidisciplinary J. 6(1), 1–55 (1999)
Järvelä, S., Veermans, M., Leinonen, P.: Investigating student engagement in computer-supported inquiry: a process-oriented analysis. Soc. Psychol. Educ. 11(3), 299–322 (2008)
Kahu, E.R.: Framing student engagement in higher education. Stud. High. Educ. 38(5), 758–773 (2013)
Klein, K.J., Knight, A.P., Ziegert, J.C., Lim, B.C., Saltz, J.L.: When team members’ values differ: the moderating role of team leadership. Organ. Behav. Hum. Decis. Process. 114(1), 25–36 (2011)
Kuh, G.D.: Assessing what really matters to student learning inside the national survey of student engagement. Change: Mag. High. Learn. 33(3), 10–17 (2001)
Lin, W.S.: Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. Int. J. Hum.-Comput. Stud. 70(7), 498–507 (2012)
Marino, S., Hogue, I.B., Ray, C.J., Kirschner, D.E.: A methodology for performing global uncertainty and sensitivity analysis in systems biology. J. Theoret. Biol. 254(1), 178–196 (2008)
Mayer, R.E., Heiser, J., Lonn, S.: Cognitive constraints on multimedia learning: when presenting more material results in less understanding. J. Educ. Psychol. 93(1), 187 (2001)
Meyer, K.A.: The influence of online teaching on faculty productivity. Innovat. High. Educ. 37(1), 37–52 (2012)
Moore, M.G., Kearsley, G.: Distance Education: A Systems View of Online Learning. Cengage Learning, Boston (2011)
Nouh, T., Anil, S., Alanazi, A., Al-Shehri, W., Alfaisal, N., Alfaris, B., Alamer, E.: Assessing correlation between students’ perception of the learning environment and their academic performance. JPMA 66(12), 1616–1620 (2016)
Park, J.H., Choi, H.J.: Factors influencing adult learners’ decision to drop out or persist in online learning. J. Educ. Technol. Soc. 12(4), 207–217 (2009)
Peng, W.: Research on model of student engagement in online learning. EURASIA J. Math. Sci. Tech. Educ. 13(7), 2869–2882 (2017)
Reeves, T.C., Benson, L., Elliott, D., Grant, M., Holschuh, D., Kim, B., Kim, H., Lauber, E., Loh, S.: Usability and Instructional Design Heuristics for E-Learning Evaluation (2002)
Reinecke, L., Eden, A.: Media use and well-being (2017)
Schermelleh-Engel, K., Moosbrugger, H., Müller, H.: Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures. Methods Psychol. Res. Online 8(2), 23–74 (2003)
Shea, P., Bidjerano, T.: Does online learning impede degree completion? A national study of community college students. Comput. Educ. 75, 103–111 (2014). https://doi.org/10.1016/j.compedu.2014.02.009
Skinner, E., Furrer, C., Marchand, G., Kindermann, T.: Engagement and disaffection in the classroom: part of a larger motivational dynamic? J. Educ. Psychol. 100(4), 765 (2008)
Stahl, G.: Group Cognition: Computer Support for Building Collaborative Knowledge, pp. 451–473. MIT Press, Cambridge, MA (2006)
Stein, D.S., Wanstreet, C.E., Calvin, J., Overtoom, C., Wheaton, J.E.: Bridging the transactional distance gap in online learning environments. Am. J. Distance Educ. 19(2), 105–118 (2005)
Suksudaj, N., Lekkas, D., Kaidonis, J., Townsend, G.C., Winning, T.A.: Features of an effective operative dentistry learning environment: students’ perceptions and relationship with performance. Eur. J. Dental Educ. 19(1), 53–62 (2015)
Volery, T., Lord, D.: Critical success factors in online education. Int. J. Educ. Manag. 14(5), 216–223 (2000)
Xu, M., Benson, S.N.K., Mudrey-Camino, R., Steiner, R.P.: The relationship between parental involvement, self-regulated learning, and reading achievement of fifth graders: a path analysis using the ECLS-K database. Soc. Psychol. Educ. 13(2), 237–269 (2010)
Yang, Y.F.: Engaging students in an online situated language learning environment. Comput. Assist. Lang. Learn. 24(2), 181–198 (2011)
Zhang, Z., Kenny, R.: Learning in an online distance education course: experiences of three international students. Int. Rev. Res. Open Distrib. Learn. 11(1), 17–36 (2010)
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Tao, Z., Zhang, B., Lai, I.K.W. (2018). Perceived Online Learning Environment and Students’ Learning Performance in Higher Education: Mediating Role of Student Engagement. In: Cheung, S., Lam, J., Li, K., Au, O., Ma, W., Ho, W. (eds) Technology in Education. Innovative Solutions and Practices. ICTE 2018. Communications in Computer and Information Science, vol 843. Springer, Singapore. https://doi.org/10.1007/978-981-13-0008-0_6
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