2015 Conference Archive
Using the ARCS-V Model to Reframe Success in Online Courses
Copyright
This work is archived and distributed under the repository's Standard Copyright and Reuse License (opens in new tab). End users may copy, store, and distribute this work without restriction. For all other uses, permission must be obtained from the copyright owners or their authorized agents.
Abstract
This session addresses one major question for online course design and a related question about factors of student retention: (1) Should the Attention, Relevance, Confidence, Satisfaction, and Volition (ARCS-V) motivation model by John Keller (Zammit, Martindale, Meiners-Lovell, & Irwin, 2013) reframe the design and teaching of online courses? (2) Do factors of student retention in higher education (Demetriou & Schmitz-Sciborski, 2011; Jenson, 2011) continue to make sense in the growing context of online education?
Answers will evolve from discussing the following findings:
a. Different variables affect dropout rates in on-campus v. online courses. (Herbert, 2006; Park & Choi, 2009; Shanley, 2009,2011).
b. Student effort overcomes other variables (Firmin, Schiorring, Whitmer, Willett, Collins, & Sujitparapitaya, 2014; Henson 2014).
c. Predictors of success (retention) include organizational support, online resources, relevance, confidence (including Internet self-efficacy), and satisfaction (Chang, Liu, Sung, Lin, Chen, and Cheng, 2014; Cho, 2012; Cochran, Campbell, Baker, & Leeds, 2014; Park & Choi, 2009; Shanley, 2009, 2011).
d. Student-student interactions can increase withdrawals, but some interactions improve retention (Boyle, Kwon, Ross, Simpson, 2010; Moore, 2014; Schubert-Irastorza & Fabry, 2011).
Handouts and visuals will summarize the ARCS-V model and compare standards for success in online courses and brick-and-mortar courses.
Location
Room 2011
Publication Type and Release Option
Event
Recommended Citation
Goodson, Ludwika, "Using the ARCS-V Model to Reframe Success in Online Courses" (2015). SoTL Commons Conference. 101.
https://digitalcommons.georgiasouthern.edu/sotlcommons/SoTL/2015/101
ARCSVSoTLRetentionByLGoodson.pdf (717 kB)
ARCSintegrated_handout.pdf (249 kB)
2015ARCSVIssueAHandout.pdf (292 kB)
2015ARCSVIssueBHandout.pdf (450 kB)
2015ARCSVIssueCHandout.pdf (416 kB)
2015ARCSVIssueDHandout.pdf (456 kB)
Using the ARCS-V Model to Reframe Success in Online Courses
Room 2011
This session addresses one major question for online course design and a related question about factors of student retention: (1) Should the Attention, Relevance, Confidence, Satisfaction, and Volition (ARCS-V) motivation model by John Keller (Zammit, Martindale, Meiners-Lovell, & Irwin, 2013) reframe the design and teaching of online courses? (2) Do factors of student retention in higher education (Demetriou & Schmitz-Sciborski, 2011; Jenson, 2011) continue to make sense in the growing context of online education?
Answers will evolve from discussing the following findings:
a. Different variables affect dropout rates in on-campus v. online courses. (Herbert, 2006; Park & Choi, 2009; Shanley, 2009,2011).
b. Student effort overcomes other variables (Firmin, Schiorring, Whitmer, Willett, Collins, & Sujitparapitaya, 2014; Henson 2014).
c. Predictors of success (retention) include organizational support, online resources, relevance, confidence (including Internet self-efficacy), and satisfaction (Chang, Liu, Sung, Lin, Chen, and Cheng, 2014; Cho, 2012; Cochran, Campbell, Baker, & Leeds, 2014; Park & Choi, 2009; Shanley, 2009, 2011).
d. Student-student interactions can increase withdrawals, but some interactions improve retention (Boyle, Kwon, Ross, Simpson, 2010; Moore, 2014; Schubert-Irastorza & Fabry, 2011).
Handouts and visuals will summarize the ARCS-V model and compare standards for success in online courses and brick-and-mortar courses.