Improving Online Motivation Through Emails

Huett, J. B., Kalinowski, K. E., Moller, L., & Huett, K. C. (2008). Improving the motivation and retention of online students through the use of ARCS-based e-mails. The American Journal of Distance Education, 22, 159-176.

Huett et al., created a study to examine how periodic mass email messages could improve the motivation and retention of students enrolled in an online course. They felt there are significant challenges when it comes to retaining online learners and were searching for a simpler approach to motivating those learners in a cost-effective way, fit within the time constraints of the class or for the teacher, and could be seamlessly integrated into the teaching and learning process (p. 160). The authors selected the ARCS model as the overall framework for creating the motivational mass emails because the approach attempts to synthesis behavioral, cognitive, and affective learning theories and demonstrates that learner motivation can be influenced through external conditions (Huett et al., 2008). Through their research, studies have cited that motivation can account for 16% to 38% of the variations in overall student achievement (Means et al., 1997), thus the importance of designing appealing instruction to manipulate learner motivation for online learning courses.

According to the authors, there has been little research in using the ARCS model for motivational messaging in online learning. I do believe there is value in studying this phenomena as a potential mass intervention to improve learner motivation and performance in an online learning environment. The ARCS model is quite comprehensive and broken down into two parts. The first part of the model is a set of categories (attention, relevance, confidence, satisfaction) that represent the components of motivation and the second part of the model is a systematic design process that assists in creating motivational enhancements that are appropriate for a given set of learners. Overall, the study revealed that there was a statistical difference in means between students receiving the treatment and those who did not receive the treatment. In fact, Huett et al., highlighted that there was a statistical difference in every measure of motivation except relevance in the study and explained why given the nature of the treatment that their results made sense (p. 171). Additionally, the study yielded greater student retention as well as a lower student failure rate for the treatment group. Any positive findings related to new motivation and retention strategies should warrant further studies.

In my district, we do offer online learning courses for students who need credit recovery, a class that is not offered for a specific hour or trimester and/or for a class generally not offered. The program is administered through our Alternative High School and students who participate must take their online classes within the school district in designated locations during the school year. Although the online programming is somewhat manageable now, as the number of students requesting online classes continues to grow, I feel it is important to develop a set of strategies and interventions to support a multitude of learners and realize that not all communication exchanges can be personalized each and every time. This study gives pause to current and future practice and potentially represents another tool to use to complement our current efforts.

Means, T., Jonassen, D., & Delaney, H.D. (1997). Enhancing relevance: Embedded ARCS strategies vs. purpose. Educational Technology Research and Development, 45, 5-17.

On My Mind…Higher Ed. Online Learning

As more and more K-12 institutions consider adding online learning courses to their learning pathways, it becomes more important to read about the reasons for heading this route i.e., what are the lessons learned, how institutions should prepare for the shift, what constitutes learner readiness, what courses yield better results, what training should be provided to teachers, etc. With the online learning movement spreading to the K-12 industry, now is the time to study the good, bad and ugly. Higher Ed. institutions had to cross the teaching/learning chasm a few years ago in order to retain students, meet diverse student learning styles & other needs, secure highly qualified instructors, and keep costs contained to name a few. Listed below are some initial readings to begin to gain a better understanding of the underpinnings and frameworks needed to support online learning:

  • Abrami, P. C., Bernard, R. M., Bures, E. M., Borokhovski, E., Tamim, R. M. (2011). Interaction in distance education and online learning: Using evidence and theory to improve practice. Journal of Computer in Higher Education, 23(2), 82-103.
  • Dikkers, A. G. (2015). The intersection of online and face-to-face teaching: Implications for virtual school teacher practice and professional development. Journal of Research on Technology in Education, 47(3), 139-156.
  • King, S. E., Arnold, K. C. (2012). Blended learning environments in higher education: A case study of how professors make it happen. Mid-Western Educational Research, 25(1/2), 44-59.
  • McDonald, P. L., Straker, H. O., Schlumpf, K. S., Plack, M. M. (2014). Learning partnership: Students and faculty learning together to facilitate reflection and higher order thinking in a blended course. Online Learning Journal, 18(4), 1-22.
  • Picciano, A. G., Seaman, J., Shea P., Swan, K. (2012). Examining the extent and nature of online learning in american K-12 education: The research initiatives of the Alfred P. Sloan foundation. Internet and Higher Education, 15, 127-135.
  • Reece, S. A. (2015). Online learning environments in higher education: Connectivism vs. dissociation. Education and Information Technologies, 20(3), 579-588.
  • Richardson, J. C., Swan, K. (2003). Examining social presence in online courses in relation to students’ perceived learning and satisfaction. Journal of Asynchronous Learning Networks, 7(1), 68-88.
  • Smith, S. J., Basham, J., Rice, M. F., Carter Jr., R. A. (2016). Preparing special educators for K-12 online learning environments: A survey of teacher educators. Journal of Special Education Technology, 31(3), 170-178.
  • Vaughan, N. (2007). Perspectives on blended learning in higher education. International Journal on E-Learning, 6(1), 81-94.