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Editor’s Note: Within the College arena there are three major areas for focus on attrition rates for students whether distance learning or not. These are 1) community colleges, 2) universities, and 3) academic continuing education programs. Dr. Parker has some interesting research on rates of completion and factors significant in student attrition.

 

Identifying Predictors of Academic Persistence in Distance Education

Angie Parker

Introduction

Distance education as an alternative to face-to-face instruction has witnessed steady growth since its beginning in the mid-1800's. This growth is evidenced by the fact that in 2002 nearly 78 percent of all adult students had received education in some distance format. This influx of adults taking distance education courses has occurred in part because of the proliferating demands of our technological society and in part because of the complexity of modern life. While society calls for lifelong learning, employment and family responsibilities call for adults to seek forms of education other than traditional, face-to-face instruction. Distance education affords adults the required formal education while allowing for flexible scheduling.

With the growth of distance-education has come the problem of exceedingly high attrition rates. Carr and Ledwith (2000) found rates to exceed 40 percent in some institutions. In an attempt to identify causes for non-completion, numerous studies have centered on application of a variety of traditionally-based theoretical models to the distance education setting. Diaz (2002) used a test of learning styles to determine the correlation between students who scored as independent, self-directed individuals and completion of online instruction. Diaz reported a statistically significant correlation between self-motivated and academic persistence.

There is a critical need for colleges to be able to predict with some accuracy the potential persistence of distance education students. With institutions of higher education generally receiving governmental support based on enrollment, the issue of attrition is particularly important. If rate of completion could be enhanced, through better placement and counseling of distance education students, subsequent fiscal budgets could become more predictable.

The current study sought to test the theory that locus of control, or the level of self-motivation, is significantly correlated with academic persistence.  This study also examined potential changes in locus of control scores over a semester for students who complete an online course. While numerous variables such as financial aid (Parker, 1999) and experience levels of instructors (Carr, 2000) have been touted as predictors of attrition in distance education, locus of control has consistently shown promise. The problem facing academic administrators and instructors tasked with finding answers to the current high levels of attrition in distance delivered courses is the limited number of studies utilizing this variable.

Hypotheses

This study had two hypotheses:

1. Locus of control, as measured by the Rotter's Locus of Control scale, is a significant predictor of academic persistence.
2. Locus of control scores increase, moved toward internality, over the course of a semester for students enrolled in web-based instruction.

Review of the Literature

Locus of control is a learned trait (Rotter, 1966). The actual patterns of reinforcement influence the development of either internal or external locus of control. A person who is consistently reinforced for personal accomplishments will be more likely to possess an internal locus of control than a person who receives reinforcement sporadically or inconsistently. Rotter found that people differ in the extent to which they attribute outcomes to internal versus external sources of control. The results of Rotter's (1966, 1976) studies consistently suggest that "Those with internal…[control]…show more overt striving for achievement than those with external control" (p.21). The findings of Altman and Arambasich (1992) at the University of Calgary constitute a similar argument. This team of researchers hypothesized that internality would be positively related to program completion. The 1992 study found a significant difference between internal and external groups in attrition with internals demonstrating a greater degree of persistence.

Further evidence of the relationship between dropout and locus of control comes from a study by Dille and Mezack (1991). This research team utilized the Rotters I-E Locus of Control scale with 151 students enrolled in a telecourse at a southwestern community college. The data indicated that the 43 non-completers had an external locus of control while the 108 successful students were more internally oriented.

The research has indicated that students leave traditional higher education for a myriad of reasons but research indicates online students face a greater challenge to complete. The mediation of technology and the often lack of personal interaction are serious considerations for instructors and students alike.  Bailey (2002) believes colleges must move to the point where student-learning styles are matched with the delivery medium. Diaz (2002) believes that locus of control in addition to learning styles, should serve as a roadmap for potential online students. Diaz and Cartnal (1999) reiterate the fact that internally motivated students are often the same students who complete online instruction:

It is not surprising that students who prefer independent, self-paced instruction would self-select into an online class. It may be that the distance education format appealed to students with independent learning styles, and that independent learning preferences are well suited to the relative isolation of the distance learning environment (p.134).

A recent study (Liu, Lavelle & Andris, 2002) found that locus of control evolved over the course of a semester with students scoring higher (becoming more internal) at the end of a semester of online instruction. Liu, Lavelle & Andris state, "Online instruction can improve students' sense of personal competence, self-responsibilities, and beliefs about their own learning" (2002). Online instruction requires students to develop a stronger sense of their own competence through self-directed assignments. Interaction, which is mediated by technology, also requires the student to become an independent thinker and thus transition their locus of control to a more internal capacity.

Research indicates the significance of locus of control as an indicator of persistence in web-based instruction. Additionally, it has been illustrated that self-motivation can be enhanced with well-designed online instruction which encourages the students to be self-directed learners. Knowles (1984, 1992) indicated a strong need for adult learners to be self-directed and to take responsibility for their own decisions. Web-based instruction lends itself to this belief, as students must be responsible for their own time management, skill building, and eventual academic success or failure. 

Method

This study was conducted at a community college in Arizona. Ninety-five students and four instructors participated. Two of the four instructors taught the same class in both traditional and online formats. During the first week of the semester, both online and traditional students received the Rotter's Locus of Control survey. Online students were given one week to complete the survey while face-to-face students were asked to complete it the first night of class. Both groups of students received 15 weeks of instruction. The surveys were hand-scored and data analyzed using SPSS 10.

Instruments

Internal-external (I-E) locus of control is hypothesized to be a bipolar construct. The locus of control in internal if a person perceives events to be contingent upon his or her own behavior; the locus of control is external when events are perceived to be contingent upon luck, fate, the control of others, the environment or anything else not under the student's control (March & Richards, 1987). While a number of scales have been developed to study locus of control, Rotter's (1966) scale dominates the literature.

The locus of control survey was offered online and in paper format. All surveys were hand scored with 12 as the cut off score for internality and externality. Low scores of 10 or less indicated internal control. Higher scores of 14 or higher indicated an external preference. Scores ranged from 1 to 23.

Experimental Design

This study involved a single group pretest-posttest design. The participants were given the Locus of Control survey the first week of class. The students were then given 15 weeks of online, using Blackboard, or traditional instruction. In the last week of the course, students were given the Locus of Control survey again as a posttest. Scores from the pre and post Locus of Control surveys were correlated to determine if any change had occurred during the semester. A correlation analysis used to determine the relationship between the locus of control and academic persistence.

Results and Discussion

This study was designed to test two hypotheses for the purpose of determining the relationship between locus of control and academic persistence. Locus of control data was obtained using the Rotter's I-E Locus of Control scale. College records provided information on attrition in each of the four classes used in the sample.

Table 1 provides the sample size for both the online and the traditional classes used in this study. It should be noted that two of the instructors chosen for this research taught both a web-based and a traditional section of the same course. The other two instructors taught only online or only in a traditional, face-to-face format.

Table 1.

Number of Students by Delivery Method

Table 2 provides a descriptive review of the study. The mean scores for the online component illustrate the fact that the online sample became more internal, or self motivated, during the course than did the traditional students. The table also demonstrates that traditional students tend to be more external than those who select technology-mediated instruction. These two findings were collaborated by the work of Liu, Lavelle and Andris (2002). The results also evidence the fact that web-based instruction has the potential for moving students to greater levels of self-directed motivation.

Table 2.

Means and Standard Deviation for Interval Variables Pre and Posttest

Carr (2000) also found that incoming freshmen tended toward external motivation and yet wanted the convenience of online instruction. Drop out rates for this group reached nearly 32 percent.

Table 3.

Completion Rates by Delivery Method

Table 3 provides data on the frequency and percentage of completers by delivery method. As is evidenced throughout the literature, the traditional sections had a significantly higher rate of completion than that of the web-based.

Correlations

The second analysis involved a chi-square whereby the status of completion was coded as 1(completed) or 2 (non-completer) and correlated with the locus of control scores. The purpose was to determine the strength of the relationship between these two variables. These results indicate a strong correlation between academic persistence and internality, or self-motivation, in web-based courses. While traditional students showed little change in motivational scores, the level of completion was nearly 95 percent. Locus of control had no significant value in predicting completion rates in the traditional classroom.

Table 4.

Correlation between Locus of Control and
Status of Completion Delivery Method

            p=.05

Hypotheses

1. Locus of Control, as measured by the Rotter's Locus of Control scale, is a significant predictor of academic persistence.

Through the use of a chi-square, this hypothesis was shown to be significant. Locus of control and academic persistence were shown to have a correlation of .83 (p=.05). Students with internal locus of control, self-motivated, were more likely to complete the online course than students who scored as externally motivated.

2. Locus of control scores increase, moved toward internality, over the course of a semester for students enrolled in web-based instruction.

This hypothesis was also proven to be significant. Students who enroll in online courses tend to become more self-motivated than students who attend traditional courses. Change in locus of control scores by the students enrolled in the traditional sections of the courses was not significant.

Conclusion

The results of this study have generated a number of implications for those individuals charged with reducing high attrition rates in distance education courses. Although the results have not provided evidence that can be generalized to all distance education courses, the results do indicate a correlation between locus of control and academic persistence.

The study also illustrates that students who are moderately internal tend to become more self-directed in web-based courses. The implication for web-course designers and instructors is to understand that instructional intervention can be a powerful tool for accelerating motivational change. This same result was found by Liu, Lavelle & Andris, (2002) who illustrated that students who had a tendency toward internality increased their skills as self-motivated students during an online course.

This research also indicated a need for a screening procedure to determine students' locus of control. Those who score as internal should be encouraged to register for non-traditional delivery. Students who score as external may be better suited to the traditional format of coursework.

Further research is needed in the area of locus of control and self-motivation. Several studies (Diaz, 2002: Carr, 2000: Parker, 1999) have used Rotter's Locus of Control scale to compare student characteristics between distance education and traditional samples. Results of these studies have again added to the knowledge base by providing further insight into attrition. Moore (1989) has cautioned future researchers, however, to stop comparison studies and to focus only on the distance education student. "Distance and traditional forms of education draw from different populations, and thus learner problems must remain separate in future studies" (p. 89). It is, therefore, important for future research to develop constructs from which distance education can be evaluated and from which predictions of dropout can be formulated.

References

Altman, H. & Arambasich, L. (1992). A study of locus of control with adult students. Canadian Counselor, 16(2), 97-101.

Bailey, M. (2002). A new perception on the construct of distance learning. New York: Miller & Associates Publishing.

Carr, R. & Ledwith, F. (2000). Helping disadvantaged students. Teaching at a Distance, 18,77-85.

Carr, S. (2000, February 11). As distance education comes of age, the challenge is keeping the students. Chronicle of Higher Education.

Diaz, D. (2002). Online drop rates revisited. Technology Source, May/June 2002.

Diaz, D. & Cartnal, R. (1999). Students' learning styles in two classes: Online distance learning and equivalent on-campus. College Teaching, 47(4), 130-135.

Dille, B. & Mezack, M. (1991). Identifying predictors of high risk among community college telecourse students. American Journal of Distance Education, 5(1), 24-35. 

Knowles, M. (1984). Androgogy in action. San Francisco: Jossey-Bass.

Knowles, M. (1992). Androgogy: A study of the adult learner. San Francisco: Jossey-Bass.

Liu, Y., Lavelle, E. & Andris, J. ( 2002). Experimental effects of online instruction on locus of control. USDLA Journal [Online] 16(6). Available: http://www.usdla.org/html/journal/JUN02_Issue/article02.html

March, H. & Richards, G. (1987). The multidimensionality of the Rotter I-E Scale and its higher order structure: An application of confirmatory factor analysis. Multivariate Behavioral Research, 22, 39-69.

Moore, M. (1989). Recruiting and retaining adult students in distance education. New Directions for Continuing Education, 47,69-98.

Parker, A. (1999). A study of variables that predict dropout from distance education, International Journal of Educational Technology [Online],1(2). Available: http://www.outreach.uiuc.edu/ijet/v1n2/parker/

Rotter, J. (1966). Generalized expectations for internal versus external control of reinforcement. Psychological Monographs, 80,1-28.

Rotter, J. (1976). Some problems and misconceptions related to the construct of internal versus external control of reinforcement. Journal of Consulting and Clinical Psychology, 48, 56-67.

About the Author:

Dr. Angie Parker received her Ph.D. from Arizona State University where she majored in Distance Delivery of Instruction.  Upon graduation, she taught for ASU for three years and conducted research on the effect of distance on learning.

Angie was also instrumental in developing an online instruction program while she chaired the Department of Educational Technology at Gonzaga University in Spokane, Washington. Angie believes that distance delivery is not right for every student nor is it the answer for every business or institution of higher learning. Instead, distance delivery must be done with extreme skill and care and with the student as the priority.

Today, Dr. Parker is the Associate Dean of Distributed Learning for Yavapai College in Prescott, Arizona.  She oversees the development and delivery of numerous courses per semester.  Delivery methods include interactive television, Internet, and Cable television.

Dr. Angie Parker, Associate Dean
Yavapai College, Distributed Learning
1100 Sheldon Street, Prescott, Arizona, 86301

(928) 776-2074  angie_parker@yc.edu