Proposal Title

Using the ARCS-V Model to Reframe Success in Online Courses

Proposal 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

Presentation (Open Access)

 
Mar 25th, 10:00 AM Mar 25th, 10:45 AM

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.