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The Role of Educational Technology and Online Learning in Preventing Dropouts

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By Yu-Chun Kuo
Rowan University
[email protected]

The use of educational technology appears to be a method to prevent students from leaving school (Harper & Boggan, 2011; Reimer & Smink, 2005; Roblyer, 2006; Smith, Clark, & Blomeyer, 2005). Fully online and blended learning are two of the most popular course delivery methods in K-12 education. The majority of these online or blended programs are provided for high school students; significantly fewer opportunities are given to middle and elementary students (DiPietro, Ferdig, Black, & Preston, 2008; Harper & Boggan, 2011). The potential of online learning may help remove learning barriers by increasing student motivation to learn or by improving student attitudes towards learning, which decreases the negative influences of individual and institutional factors contributing to student dropout issues (Rumberger & Lim, 2008). Developing an online program for credit recovery or for students at risk of dropping out may be challenging, and several factors related to online effectiveness need to be considered carefully. We provide several recommendations (see Table 1) through a summary of prior research that may be helpful for K-12 administrators or educators to consider when developing online and blended programs for at-risk students or those who have dropped out.

[table id=1 /]

References

Alnahdi, G. (2014). Assistive technology in special education and the universal design for
learning. Turkish Online Journal of Educational Technology, 13(2), 18-23.

Archambault, L., Diamond, D., Brown, R., Cavanaugh, C., Coffey, M., Foures-Aalbu,
D., Richardson, J., & Zygouris-Coe, V. (2010). Research committee issues brief: An exploration of at-risk learners and online education. Vienna, VA: iNACOL

Brewster, C., & Fager, J. (2000). Increasing student engagement and motivation: From time-on-
task to homework. Retrieved from
http://educationnorthwest.org/sites/default/files/byrequest.pdf

Corry, M., & Carlson-Bancroft, A. (2014). Transforming and turning around low-performing
schools: The role of online learning. Journal of Educators Online, 11(2), 1-31.

DiPietro, M., Ferdig, R. E., Black, E. W., & Preston, M. (2008). Best practices in teaching K-12
online: Lessons learned from Michigan virtual school teachers. Journal of Interactive Online Learning, 7(1), 10-35.

Harper, S., & Boggan, M. (2011). Opinions, benefits, and weaknesses of virtual high school and
compressed video courses in a rural Mississippi high school. Journal of Technology Integration in the Classroom, 3(2), 37-39.

Hawkins, A., Graham, C. R., Sudweeks, R. R., & Barbour, M. K. (2013). Academic performance,
course completion rates, and student perception of the quality and frequency of interaction in a virtual high school. Distance Education, 34(1), 64-83.

Kuo, Y. C., Walker, A., Schroder, K. E. E., & Belland, B. R. (2014). Interaction, Internet
self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education, 20, 35-50. doi:10.1016/j.iheduc.2013.10.001

Marino, M. T., Sameshima, P., & Beecher, C. C. (2009). Enhancing TPACK with assistive
technology: Promoting inclusive practices in preservice teacher education. Contemporary Issues in Technology and Teacher Education, 9(2). Retrieved from http://www.citejournal.org/volume-9/issue-2-09/general/enhancing-tpack-with-assistive-technology-promoting-inclusive-practices-in-preservice-teacher-education

Reimer, M., & Smink, J. (2005). 15 effective strategies for improving student
attendance and truancy prevention. Retrieved from
https://www.dpi.state.nd.us/title1/progress/present/15ways.pdf

Ritzhaupt, A. D., Liu, F., Dawson, K., & Barron, A. E. (2013). Differences in student
information and communication technology literacy based on socio-economic status, ethnicity, and gender: Evidence of a digital divide in Florida Schools. Journal of Research on Technology in Education, 45(4), 291-307.

Roblyer, M. D. (2006). Virtually successful: Defeating the dropout problem through online
school programs. Phi Delta Kappan, 88(1), 31-36.

Rumberger, R. W., & Lim, S. A. (2008). Why students drop out of school: A review of 25 years
of research. Santa Barbara, CA: University of California, Santa Barbara.

Watson, J., & Gemin, B. (2008). Using online learning for at-risk students and credit recovery.
Vienna, VA: NACOL.

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Michigan Virtual Learning Research Institute

Michigan Virtual Learning Research Institute

The Michigan Virtual Learning Research Institute (MVLRI) is a non-biased organization that exists to expand Michigan’s ability to support new learning models, engage in active research to inform new policies in online and blended learning, and strengthen the state’s infrastructures for sharing best practices. MVLRI works with all online learning environments to develop the best practices for the industry as a whole.

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