Abstract
This study is designed to increase understanding of how learner-centered instruction and emerging technologies can be applied to improve online courses and increase student satisfaction and performance at the higher education level. The research questions examine predictors of student achievement, persistence, and satisfaction in online learning and investigate what strategies are most effective at building learner success and optimal online learning contexts. Three models for systematic design of online learning courses are considered. Two of these models are used in a reflective data analysis process that uses data from three recent online courses as test cases. Analysis of results shows that an integrated use of the two models featured provides a useful design approach to support on-going innovation and systemic analysis of online course implementation. Recommendations for expanding upon this research are provided.
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References
Palloff, R.M., Pratt, K.: Building Online Learning Communities: Effective Strategies for the Virtual Classroom, p. 18. Jossey-Bass, San Francisco (2007)
Elam, E.: A quantitative inquiry into the factors that influence success in online classes. A dissertation presented to the faculty of the Curry School of Education, University of Virginia. UMI 3528581. ProQuest LLC, Microform edn. (May 2012)
Joo, Y.J., Lim, Y.L., Kim, J.: Locus of control, self-efficacy, and task value as predictors of learning outcome in an online university context. Comput. Educ. 62, 149–158 (2013)
Sun, P.-C., Tsai, R.J., Finger, G., Chen, Y., Yeh, D.: What drives a successful e-learning? An empirical investigation of the critical factors influencing learner satisfaction. Comput. Educ. 50(4), 1183–1202 (2008)
Tang, M., Byrne, R.: Regular versus online versus blended: a qualitative description of the advantages of the electronic modes and a quantitative evaluation. Int. J. E-learn. 6(2), 257–266 (2007)
U.S. Department of Education (NCES), National Center for Education Statistics. Digest of Education Statistics, 2012 (NCES 2014-015), Chapter 3. (2013) http://nces.ed.gov/fastfacts/display.asp?id=98
Motte, K.: Strategies for online educators. Turk. Online J. Distance Educ. 14(2), 258–267 (2013)
Reik, A., Maurer, M.: Consideration of dynamics in knowledge prioritization preparing an efficient company-internal knowledge transfer. Impact: J. Innov. Impact. ISSN: 2051-6002, http://www.inimpact.org 7(1), 257–265: inkt14-026 (2014)
Eccles, J., Adler, T.F., Futterman, R., Goff, S.B., Kaczala, C.M., Meece, J.L., Midgley, C.: Expectancies, values and academic behaviors. In: Spence, J.E. (ed.), Achievement and Achievement Motivation, pp. 75–146. Freeman, San Francisco (1983)
Moore, J.C.: A synthesis of Sloan-C effective practices: December 2009. J. Asynchronous Learn. Netw. 13(4), 73–97 (2009)
Ashwin, P., Boud, D., Coate, K., Hallett, F., Keane, E., Krause, K.-L., Leibowitz, B., MacLaren, I., McArthur, J., McCune, V., Tooher, M.: Reflective Teaching in Higher Education. Bloomsbury Academic, London (2015)
Butler, A.C., Marsh, E.J., Slavinsky, J.P., Baraniuk, R.G.: Integrating cognitive science and technology improves learning in a STEM classroom. Educ. Psychol. Rev. 26, 331–340 (2014)
Koehler, M.J., Mishra, P.: What happens when teachers design educational technology? The development of technological pedagogical content knowledge. J. Educ. Comput. Res. 32, 131–152 (2005)
Niess, M.L.: Preparing teachers to teach science and mathematics with technology: developing a technology pedagogical content knowledge. Teach. Teach. Educ. 21, 509–523 (2005)
Voogt, J., Fisser, P., Roblin, N.P., Tondeur, J., van Braak, J.: Technological pedagogical content knowledge—a review of the literature. J. Comput. Assist. Learn. (2012). doi:10.111/j.1365-2729.2012.00487.x
Wang, C.H.: Questioning skills facilitate online synchronous discussions. J. Comput. Assist. Living 21, 303–313 (2005)
Garrison, D.R., Cleveland-Innes, M.: Critical factors in students’ satisfaction and success: facilitating student role adjustment in online communities of inquiry. In: Bourne, J., Moore, J.C. (eds.) Elements of Quality Online Education, pp. 29–38. Needham, SCOLE (2004)
Ajavi, L.: An exploration of pre-service teachers’ perceptions of learning to teach while using asynchronous discussion board. Educ. Technol. Soc. 12(2), 86–100 (2009)
Curtis, R.: Analyzing students’ conversations in chat room discussion groups. Coll. Teach. 52(4), 143–149 (2004)
So, H.J.: When groups decided to use asynchronous online discussions: collaborative learning and social presence under a voluntary participation structure. J. Comput. Assist. Living 25, 143–160 (2009)
Geijets, P.H., Hesse, F.W.: When are powerful learning environments effective? The role of learner activities and of students’ conceptions of educational technology. Int. J. Educ. Res. 41, 445–465 (2004)
Juarez, A.M.: Student success in the online classroom. Doctoral dissertation, Capella University, Minneapolis, MN (2003)
Martinez, S.L., Stager, G.: Invent to Learn: Making, Tinkering, and Engineering in the Classroom. Constructing Modern Knowledge Press, Torrance (2013)
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Ruberg, L.F. (2015). Transferring Smart E-Learning Strategies into Online Graduate Courses. In: L. Uskov, V., Howlett, R., Jain, L. (eds) Smart Education and Smart e-Learning. Smart Innovation, Systems and Technologies, vol 41. Springer, Cham. https://doi.org/10.1007/978-3-319-19875-0_22
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DOI: https://doi.org/10.1007/978-3-319-19875-0_22
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