Dissertation ProspectusPPT II Draft

Characteristics and Persistence of Traditional Students in Online Classes

Barbara KilthauHEOC 803

Benedictine University5 Aug 2012

Chapter 1:The Introduction

Problem Statement: Characteristics and Persistence of Traditional Students in Online Classes

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.

What We Know:What We Don’t Know:

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). Student persistence is 20% lower in online courses than in equivalent face-to-face courses (Johnson, 2003).

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%.

Why respondents rated programs designed specifically for adult/non-traditional students and programs designed specifically for online learners least effective among 60 items that were measured for their effectiveness in supporting student retention (Noel & Levitz, 2009)?

What influences a traditional students choices to enroll in an online course?

Are students who are enrolled in both face-to-face instruction and online classes equally persistent in both?

Do campus interventions play a role in online student persistence in a traditional university?

Chapter 1:The Introduction

Purpose Statement:

The purpose of this study is to explore undergraduate student stories regarding their decisions to choose online classes to augment their traditional, face-to-face classes and Identify the characteristics that make them equally persistent in both at a traditional university offering online classes to undergraduate students.

Chapter 1:The Introduction

Research Questions:

What influences a traditional students choices to enroll in an online class versus a traditional class?

What are the common characteristics of students who are enrolled in both face-to-face instruction and online classes?

What are the common characteristics that make them equally persistent in both?

What campus interventions play a role in online student persistence in a traditional university?

Chapter 1:The IntroductionSignificance of the Study:

There are several studies that explore and examine persistence in online learning:

Tinto’s student integration model (1993) Bean and Metzner’s student attrition model (1985)Kember’s longitudinal process model of dropouts (1989)Rovai’s persistence 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)Wilson and Allen’s Success rates of online versus traditional college students (2010)Hart’s Review of Literature on Factors Associated with Student Persistence in online Programs of Study (2012)

Other studies focus on comparing online and traditional learning student characteristics:

Hannay and Newvine’s Perceptions of Distance Learning: A comparison of online and traditional learningKatz’s Attitudes affecting college students’ preferences for distance learning

Although there is much more I need to accomplish in my literature review; I have noticed a gap in literature on undergraduate students who attend traditional university’s and chose online classes to augment their traditional programs of study.

Therefore my research will attempt to add to the literature in the field of education by more specifically studying online learner characteristics and persistence in undergraduate classes from students who attend a traditional university and chose to enroll in online classes to augment their academic programs. This will attempt to improve the practice in identifying factors for online persistence and attempt to help university’s understand successful characteristics of students with dual-enrollment choices.

Chapter 2:Review of the Literature

Attrition Models-Tinto’s student integration model (1993) -Bean and Metzner’s student attrition model (1985)-Kember’s longitudinal process model of dropouts (1989)-Rovai’s persistence model (2003)

Persistence Studies-Park’s review of studies that focused on identifying factors affecting non-traditional and non-degree online program students who -drop out (2007)-Hart’s Review of Literature on Factors Associated with Student Persistence in online Programs of Study (2012)-Frankola, K. Why online learners dropout(2001)-Park, J. & Choi, H. Factors Influencing Adult Learners’ Decision to Drop Out or Persist in Online Learning (2009)-Wilson and Allen’s Success rates of online versus traditional college students (2010)-Allen, E. & Seaman, J. Going the Distance: Online Education in the United States (2011) Comparing online and traditional learning student characteristics-Hannay and Newvine’s Perceptions of Distance Learning: A comparison of online and traditional learning-Katz’s Attitudes affecting college students’ preferences for distance learning-Park, J., & Choi, H. Differences in personal characteristics, family and organizational supports, and learner satisfaction between -dropouts and persistent learners of online programs(2007).

Chapter 3:Proposed Methodology

Major Research Perspective:Nested Mixed Method Design: qual-QUANT Triangulation

The intent of a mixed method design would be to explore undergraduate student stories regarding their decisions to choose online classes to augment their traditional, face-to-face classes and to identify through coding from the semi-structured interviews, their characteristics and the characteristics that make them equally persistent in both traditional and online courses (qual). Next, to serve as a validity check on the coding from the QL data, the quantitative scales, which will be produced from a questionnaire developed from the QN data will be administered to ~150 students ,dual-enrolled in online and traditional classes to complete the QN piece of this study which is to explore and to examine choices of online learning and persistence of traditional undergraduate students.

Chapter 3:Proposed Methodology

Nested Mixed Method Design: qual-QUANT Triangulation

With the qualitative approach grounded in Positivism ,I hopeto discern a causal relationship between variables that exist, can be identified, and can be further explained by conductingA Narrative study that involves the implementation of a semi-structured Interview.

Population and Site: (5-7) Undergraduate students attending an on campus Program at a traditional university who choose to augment their curriculum with online classes.

Data Collection: Semi structured interviews will be conductedWith questions that are developed to guide the conversation but with enough generality to allow respondents latitude to discuss Openly issues relevant to the topics discussed.

Data will be collected from the interview guide, coded with the Identification of themes between the respondents, literal coding Will be used to generally identify the themes and then focused Coding will be used to begin generating theoretical constructs.

With the quantitative approach I would develop and conduct a survey using a questionnaire developed from the coding of the QL phase one, then select a sample of students(undergraduate students who have enrolled in at least one online class to augment their traditional classes),have them complete the questionnaire, analyze the results, and then draw conclusions to validate the findings in the QL phase about this population .

Identify the type: I will use a cross sectional design so that I can examinecurrent attitudes, beliefs, opinions, and practices. This will allow me to capture how individuals think about the issue, but also practices thatsupport/do not support the issue as well.

Population: (150) Undergraduate students attending a traditional university who choose to augment their curriculum with online classes.

Sampling Procedures: The questionnaire developed will have personal, attitudinal, and behavioral questions; sensitive questions, and closed and open-ended questions. Questions will be developed in respect to The findings of the QL interviews.

Phase One: QL Phase Two: QN

References: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 http://technologvsource.org/article/online drop_rates revisited/ Frankola, K. (2001). Why online learners dropout. Workforce. October 10. 53-63

Hannay, M. & Newvine, T. (2011). Perceptions of Distance Learning: A Comparison of Online and Traditional Learning. Journal of Online Learning and Teaching. Retrieved on 25 May from http://jolt.merlot.org/05011.htm 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.

References 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.

The Literature Matrix

Variables Considered in the Study of Factors Affecting Online Student Retention

Authors Year Online growth

Dropout rates Nontraditional learners

Attrition models Factors for choosing

online

Student retention

Allen, E 2011 • • • Hannay, M 2011 • • • Park, J 2009 • • • • Park, J 2007 • • Park, J 2007 • • • Rovai, A 2003 • • Diaz, D 2002 • • Frankola, K 2001 • • Phipps, R 1999 • • • • Hiltz, S 1997 • • Tinto, V 1993 • • • Kember, D 1989 • • Bean, J 1985 • • Tinto, V 1982 • •

Back up Slides

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.

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.

The Research Problem

High attrition rates for online learners

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%

The Evidence

Several theories and theoretical frameworks have been developed to explain why students drop out:

Tinto’s student integration model (1993) Bean and Metzner’s student attrition model (1985)

Kember’s longitudinal process model of dropouts (1989)

Rovai’s persistence 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)

Analyzing these studies and comparing and contrasting them against factors that identify

why students choose online learning may show relationships between the two phenomenon

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?

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

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.