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Online Graduate Teacher Education: Establishing an EKG for Student Success Intervention

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Abstract

Predicting which students enrolled in graduate online education are at-risk for failure is an arduous yet important task for teachers and administrators alike. This research reports on a statistical analysis technique using both static and dynamic variables to determine which students are at-risk and when an intervention could be most helpful during a semester. Time-series clustering analysis of online teacher education classes revealed that prediction is possible after the 10th week capturing over 78 % of at-risk students. Visual analysis of dynamic student activities shares a number of striking commonalities consistent with EKG charting. The potential exists for instructors to recognize simple graphic patterns that identify and formatively address these issues with their students. Next phases of research will apply further validation of both the models attempted and additional predictor variables.

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References

  • Aman, R. R. (2009). Improving student satisfaction and retention with online instruction through systematic faculty peer review of courses, Unpublished doctoral dissertation, Oregon State University.

  • Balfanz, R., Herzog, L., & Mac Iver, D. J. (2007). Preventing student disengagement and keeping students on the graduation path in urban middle-grades schools: Early identification and effective interventions. Educational Psychologist, 42(4), 223–235.

    Article  Google Scholar 

  • Baran, E., & Correia, A. (2014). A professional development framework for online teaching. TechTrends, 58(5), 95–101.

    Article  Google Scholar 

  • Baran, E., Correia, A., & Thompson, A. (2011). Transforming online teaching practice: Critical analysis of the literature on the roles and competencies of online teachers. Distance Education, 32(3), 421–439.

    Article  Google Scholar 

  • Cain, M., Phillip, S., Ting, S. R., Gonzalez, L. M., Johnson, J., & Galy, E., et al. (2013). An exploration of students’ experiences of learning in an online primary teacher education program. Journal of Online Learning & Teaching, 9(3).

  • Chiocchio, F., & Lafrenière, A. (2009). A project management perspective on student’ s declarative commitments to goals established within asynchronous communication. Journal of Computer Assisted learning, 25(3), 294–305.

    Article  Google Scholar 

  • Cohen, G. L., Garcia, J., Apfel, N., & Master, A. (2006). Reducing the racial achievement gap: A social-psychological intervention. Science, 313(5791), 1307–1310.

    Article  Google Scholar 

  • Cohen, G. L., Garcia, J., Purdie-Vaughns, V., Apfel, N., & Brzustoski, P. (2009). Recursive processes in self-affirmation: Intervening to close the minority achievement gap. Science, 324(5925), 400–403.

    Article  Google Scholar 

  • Cole, B., Matheson, K., & Anisman, H. (2007). The moderating role of ethnic identity and social support on relations between well-being and academic performance1. Journal of Applied Social Psychology, 37(3), 592–615.

    Article  Google Scholar 

  • Crawford-Ferre, H. G., & Wiest, L. R. (2012). Effective online instruction in higher education. The Quarterly Review of Distance Education, 13(1), 11–14.

    Google Scholar 

  • Dray, B. J., Lowenthal, P. R., Miszkiewicz, M. J., Ruiz-Primo, M. A., & Marczynski, K. (2011). Developing an instrument to assess student readiness for online learning: A validation study. Distance Education, 32(1), 29–47.

    Article  Google Scholar 

  • Falloon, G. (2011). Making the connection: Moore’s theory of transactional distance and its relevance to the use of a virtual classroom in postgraduate online teacher education. Journal of Research on Technology in Education, 43(3), 187–209.

    Article  Google Scholar 

  • Frankola, K. (2001). Why Online Learners Drop Out. Workforce, 80(10), 53.

    Google Scholar 

  • Glezakos, T. J., Tsiligiridis, T. A., & Yialouris, C. P. (2014). Piecewise evolutionary segmentation for feature extraction in time series models. Neural Computing and Applications, 24(2), 243–257.

    Article  Google Scholar 

  • Harrell, I. L. (2008). Increasing the success of online students. Inquiry, 13(1), 36–44.

    Google Scholar 

  • Hart, C. (2012). Factors associated with student persistence in an online program of study: A review of the literature. Journal of Interactive Online Learning, 11(1), 19–42.

    Google Scholar 

  • Herbert, M. (2007). Staying the course: A study in online student satisfaction and retention. Online Journal of Distance Learning Administration, 10, 1.

    Google Scholar 

  • Heyman, E. (2010). Overcoming student retention issues in higher education onlineprograms. Online Journal of Distance Learning Administration, 8, 4.

    Google Scholar 

  • Ishitani, T. T. (2008). How to explore timing of intervention for students at risk of departure. New Directions for Institutional Research, 2008(137), 105–122.

    Article  Google Scholar 

  • Kayongo-Male, D., & Lee, M. B. (2004). Macro and micro factors in ethnic identity construction and educational outcomes: Minority university students in the People’s Republic of China. Race Ethnicity and Education, 7(3), 277–305.

    Article  Google Scholar 

  • Lee, Y., & Choi, J. (2011). A review of online course dropout research: Implications for practice and future research. Educational Technology Research and Development, 59(5), 593–618.

    Article  Google Scholar 

  • Liu, S., Yamada, M., Collier, N., & Sugiyama, M. (2013). Change-point detection in time-series data by relative density-ratio estimation. Neural Networks, 43, 72–83.

    Article  Google Scholar 

  • Macfadyen, L. P., & Dawson, S. (2010). Mining LMS data to develop an “early warning system” for educators: A proof of concept. Computers & Education, 54(2), 588–599.

    Article  Google Scholar 

  • Mazzolini, M., & Maddison, S. (2003). Sage, guide or ghost? The effect of instructor intervention on student participation in online discussion forums. Computers & Education, 40(3), 237–253.

    Article  Google Scholar 

  • Pan, W., Guo, S., Alikonis, C., & Bai, H. (2008). Do intervention programs assist students to succeed in college? A multilevel longitudinal study. College Student Journal, 42(1), 90–98.

    Google Scholar 

  • Patterson, B., & McFadden, C. (2009). Attrition in online and campus degree programs. Online Journal of Distance Learning Administration, 12, 2.

    Google Scholar 

  • Perry, B., Boman, J., Care, W. D., Edwards, M., & Park, C. (2008). Why do students withdraw from online graduate nursing and health studies education? Journal of Educators Online, 5(1), n1.

    Google Scholar 

  • Pullan, M. (2013). Using robotics to improve retention and increase comprehension in introductory programming courses. Journal of Educational Technology Systems, 42(2), 141–150.

    Article  Google Scholar 

  • Terrell, S. R., Snyder, M. M., & Dringus, L. P. (2009). The development, validation, and application of the Doctoral Student Connectedness Scale. The Internet and Higher Education, 12(2), 112–116.

    Article  Google Scholar 

  • Webb, E., Jones, A., Barker, P., & van Schaik, P. (2004). Using e-learning dialogues in higher education. Innovations in Education and Teaching International, 41(1), 93–103.

    Article  Google Scholar 

  • Winerman, L. (2012). Reading, writing, and self-esteem. Utne Reader: The Best Of The Alternative Press, 169, 16–17.

    Google Scholar 

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Authors and Affiliations

  1. Department of Educational Technology, Boise State University, Boise, ID, USA

    Brett E. Shelton, Jui-Long Hung & Sarah Baughman

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  1. Brett E. Shelton
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  2. Jui-Long Hung
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  3. Sarah Baughman
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Correspondence to Brett E. Shelton.

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Shelton, B.E., Hung, JL. & Baughman, S. Online Graduate Teacher Education: Establishing an EKG for Student Success Intervention. Tech Know Learn 21, 21–32 (2016). https://doi.org/10.1007/s10758-015-9254-8

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  • DOI: https://doi.org/10.1007/s10758-015-9254-8

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