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Dissertation Prospectus PPT I Draft

Dissertation Prospectus PPT I Draft

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Dissertation Prospectus PPT I Draft

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  1. Dissertation ProspectusPPT I Draft Barbara Kilthau HEOC 803 Benedictine University 8 July 2012

  2. The Issue/Topic sixty-five percent of all reporting institutions said that online learning was a critical part of their long-term strategy(Allen, 2011). With over 6.1 million students taking at least one online course during the fall 2010 term; an increase of 560,000 students over the number reported the previous year and the ten percent growth rate for online enrollments far exceeding the less than one percent growth of the overall higher education student population (Allen, 2011), it is easy to assess that students are increasingly choosing online classes as part of their educational journeys. With students and institutions realizing the advantages of online learning we must also be diligent in recognizing the concerns associated with this new community in higher education.

  3. The Issue/Topic cont. A number of studies have shown that a higher percentage of students participating in online courses tend to drop out compared to students in traditional, face-to-face, classroom environments (Hiltz, 1997; Phipps & Merisotis, 1999). In spite of the growth in online learning many organizations and higher education organizations are concerned with the high dropout rates of this population of student.

  4. The Research Problem How do we balance online enrollments and dropout rates of learners to ensure we are retaining the population of online learners that are vastly becoming “the traditional-non-traditional student” in higher education?

  5. The Evidence Thirty-one percent of all higher education students now take at least one course online (Allen, 2011). “With the growth of online education has come the problem of exceedingly high attrition rates” (Parker, 1999). Parker suggests that online student attrition in some institutions exceeds 40%, while others (Frankola, 2001) and (Diaz, 2002) put it at between 20-50%. 31%

  6. The Evidence Tinto’s student integration model (1993) Bean and Metzner’s student attrition model (1985) Kember’slongitudinal process model of dropouts (1989) Rovai’spersistence model (2003) Park’s review of studies that focused on identifying factors affecting non-traditional and non-degree online program students who drop out (2007) Several theories and theoretical frameworks have been developed to explain why students drop out: Analyzing these studies and comparing and contrasting them against factors that identify why students choose online learning may show relationships between the two phenomenon

  7. The Purpose of the Research The purpose of this study is to examine the relationship between student’s decisions to choose online courses and the factors that affect them in dropping out of online courses. Factors Affecting Online Student Retention: A Study of the Factors of Students Decisions to Choose Online Courses and their Relationship to their Decisions to Drop Out Research Questions: What contributions influence a student's decision to choose an online course? What contributions influence a student’s decision to drop out of an online course? What is the relationship between factors that affect a learner’s choice of online learning and their decision to drop out?

  8. The Purpose of the Research cont. Based on the findings of this research: -We anticipate that we will be able to identify correlating factors that affect online learner choices to enroll and drop out of online courses -Contrast them in relationship to those factors that affect the decision to drop a course in hopes to discern those factors that specifically apply to increasing the retention of an online learner

  9. The Targeted Audience By conducting a quantitative analysis involving several studies in dropout rates and students choices for online learning, we will be able to contrast and compare these factors to better understand any relationship between choosing online learning and dropping out of online learning. With the identified relationships, administrators and advisors will be better prepared to plan interventions that will assist them in retaining online learners.

  10. Bibliography to Date Allen, E. & Seaman, J. (2011). Going the Distance: Online Education in the United States, 2011. Babson Survey Research Group. November, 2011. Bean, J. P., & Metzner, B. S. (1985). A conceptual model of nontraditional undergraduate student attrition. Review of Educational Research, 55(4), 485-540. Diaz, D. P. (2002). Online drop rates revisited. The Technology Source, May/June. Retrieved June 26, 2012, from drop_rates revisited/ Frankola, K. (2001). Why online learners dropout. Workforce. October 10. 53-63 Hiltz, S. R. (1997). Impacts of college-level courses via asynchronous learning networks: Some preliminary results. Journal of Asynchronous Learning Networks, 1(2), 1-19. Kember, D. (1989). A longitudinal-process model of drop-out from distance education The Journal of Higher Education, 60(3), 278-301. Park, J. (2007). Factors related to learner dropout in online learning. In Nafukho, F. M., Chermack, T. H., & Graham, C. M. (Eds.)Proceedings of the 2007 Academy of Human Resource Development Annual Conference (pp. 25-1-25-8). Indianapolis, IN:AHRD.

  11. Bibliography to Date cont. Park, J., & Choi, H. (2007). Differences in personal characteristics, family and organizational supports, and learner satisfaction between dropouts and persistent learners of online programs. In G. Richards (Ed.), Proceedings of World Conference on ELearningin Corporate, Government, Healthcare, and Higher Education 2007 (pp. 6444-6450). Chesapeake, VA: AACE. Park, J. & Choi, H. (2009). Factors Influencing Adult Learners’ Decision to Drop Out or Persist in Online Learning. Educational Technology & Society, 12 (4), 207-217) Phipps, R., & Merisotis, J. (1999). What's the difference? A review of contemporary research on the effectiveness of distance learning in higher education. Washington DC: Institute for Higher Educational Policy. Rovai, A. P. (2003). In search of higher persistence rates in distance education online programs. Internet and Higher Education, 6, 1-16. Tinto, V. (1982). Limits of theory and practice in student attrition. Journal of Higher Education, 53(6), 687-700. Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student attrition (2nd ed.). Chicago, IL: University of Chicago Press.

  12. The Literature Matrix