An analytical review of the literature on
student persistence in post-secondary distance education courses
Zachary Wheeler
student persistence in post-secondary distance education courses
Zachary Wheeler
INTRODUCTION
The purpose of this paper is to present an analysis on the theme of student persistence in post-secondary distance learning. Student persistence refers to whether or not an individual would persist or withdraw from a post-secondary distance course in which he or she was enrolled (Harrell & Bower, 2011). It is an important theme because as Harrell & Bower (2011) indicated, knowledge into the reasons why post-secondary students persist or withdraw can help institutions and instructions take a proactive approach to increasing the likelihood that their students successfully complete distance courses. Moreover, there is a strong notion among academic scholars that one of the main goals among educators in post-secondary distance learning environments should be an emphasis on ensuring their students persist in their academic courses (Levy, 2007; Hershkovitz & Nachmias, 2011; Park & Choi, 2009).
Organization of the paper
This paper begins with a methods’ section that describes how the analysis was conducted. The findings’ section reports on the results of the analysis on 10 studies as well as identifying themes that emerged. These studies will then be critiqued in the discussions session, with a specific emphasis on comparing and contrasting the major findings. Highlights from this review will be presented in the conclusions section and will cover several important limitations. Finally, implications for practice pertaining to both course instructors and academic policy makers will be given.
Organization of the paper
This paper begins with a methods’ section that describes how the analysis was conducted. The findings’ section reports on the results of the analysis on 10 studies as well as identifying themes that emerged. These studies will then be critiqued in the discussions session, with a specific emphasis on comparing and contrasting the major findings. Highlights from this review will be presented in the conclusions section and will cover several important limitations. Finally, implications for practice pertaining to both course instructors and academic policy makers will be given.
METHODS
The 10 sources analyzed in the paper were selected from seven peer-reviewed educational technology journals. Because all sources were selected from educational technology journals, all included an electronic medium. The analysis only included sources with the words persist or persistence, and distance or online as part of their title. To figure as part of the analysis, the journal sources had to include research participants. This means that meta-analyses, book reviews etc. were excluded. Studies were found using specific keyword searches (as mentioned previously) conducted through online databases, predominantly Education Resources Information Centre (ERIC) and Google Scholar. The following journals have articles represented in this analysis:
Distance Education
International Review of Research In Open And Distance Learning
Internet And Higher Education
Computers and Education
American Journal Of Distance Education
Education Technology and Society
Open Learning
The studies selected ranged in published years between 1997 to 2011, with the majority of the research stemming from the 2008 and more current. While most of the studies analyzed derived data from United States students, three studies examined institutions outside of the United States, including Indonesia (Belawati, 1998), Korea (Joo, Lim & Kim, 2011) and New Zealand (Zajkowski, 1997). Methods of data collection were diverse and consisted of online student log analysis, interventions, case studies, survey data and interviews. The numbers of participants again varied from a low of 20 to a high of 1,189. Furthermore, while most studies examined undergraduate students specifically, two studies computed data from both undergraduate and graduate students (Levy, 2007; Muller, 2008) while no authors studied graduate students solely. Information pertaining to the specific course subject matter was unknown in the vast majority of the studies.
The purpose of the analysis was to identify similarities and differences, and to identify patterns in the scholarly research on the topic of student persistence in post-secondary distance education. This was achieved using a content analysis method (Masood (2004) where by articles were sorted and sifted into different topics, and then coded and categorized based on their themes. Patterns emerged with the goal of deriving overarching themes and presenting conflicting findings.
FINDINGS
Demographics’ Characteristics and Student Persistence
Student demographic characteristics include biographical information such as grade point average, weekly hours worked, gender, age group, resiliency status and academic major (Levy, 2007). As Levy (2007) reported, there was no linkage between student persistence and a learner’s demographic characteristics among undergraduate and graduate students. Similarly, Park & Choi (2009) found learner demographics, specifically age, gender, and educational level, to be insignificant predictors in determining withdraw and attrition instances among post-secondary students in their study on 147 adult learners enrolled in one of 18 distance courses. However, it was observed by Herrell & Bower (2011) that among post-secondary students, those with higher GPAs were more likely to persist in a distance course. The authors stated the reason for this finding centered on the belief that “students with higher GPAs showed evidence that they have learned how to navigate college courses and understand what it takes to be successful in the college environment” (p. 187). Among female learners, a major barrier to persistence pertained to the need to balance multiple responsibilities (childcare, family obligations, and professional responsibilities) (Muller, 2008). The study discovered that approximately 75 percent of participants “referred to their struggles managing their responsibilities as parents and teachers” (p. 8).
Learning styles were also analyzed by Harrell & Bower (2011). According to these authors, auditory learners were more likely to withdraw from a course, compared to those who process information more effectively through written communication. The authors stated that the incongruence between an auditory preference and the written nature of online learning “could lead to frustration and eventually course withdraw” (p. 187).
Among mature aged post-secondary students, Kemp (2002) observed that student persistence was linked to four resiliency skills (initiative, generating, relationships, and insight) and five resiliency sub skills (attaching, generating resilience, recruiting, valuing, and persistence). Further, the findings showed that external commitments (personal, financial, community, and home) “were not found to be significant predictors of persistence (or lack of persistence) in distance education” (p. 75).
Student Persistence and Technology Difficulties
Students experienced technological difficulties in several of the studies analyzed. Women learners faced technological problems when attempting to access their course (Muller, 2008). In this study, participants expressed feelings of confusion when online course tools would fail to work correctly. Furthermore, there were examples of students missing online group meetings because of internet issues, computer issues or issues with the course tools. Interestingly, Harrell & Bower (2011) found that students who reported they had higher levels of computers competence were more likely to withdraw from distance classes. While the authors acknowledged this finding was unexpected, they proposed that students with “very high computer skills are more inclined than students with lower skills to succumb to the distractions of the Internet” (p. 187), and spend more time on non-course related activities online. Conversely, student’s previous experiences with distance education, and thus, their familiarity with the technological elements associated with distance learning, did not contribute to student persistence to a meaningful degree in a study of 121 undergraduate students (Kemp, 2002).
Student Persistence and Student Satisfaction & Motivation
Another important sub theme that emerged was the significance that student satisfaction and motivation had on their decision to persist or withdraw from a distance course. Data from Levy’s (2007) study on 133 students in 18 undergraduate courses reveled that student satisfaction played a critical role in predicating student persistence. Moreover, Park & Choi (2009) observed that higher levels of learner satisfaction to be significantly linked to student persistence. The authors encouraged instructors to incorporate learning activates that relate to student’s interests or goals, and at the same time, they stressed the importance of employer led recognition initiatives in an effort to motivate students to persist throughout their course. Interventions such as contacts from the course instructor, information on learning strategies, and encouragement were found to be strong motivators, resulting in feelings of acknowledgement and attention (Belawati, 1998). However, these interventions did not significantly increase student persistence.
Course Usefulness
Course usefulness, defined as the way a course is designed to guarantee the learners’ satisfaction and meet the relevant academic or job related needs (Park & Choi, 2009), was found to be an important component for student persistence in post-secondary distance courses. The vast majority (96 percent) of respondents in Zajkowski’s (1997) study on persistence in distance education indicated that higher education played a pivotal role in future professional success. Among female students, post-secondary learning opportunities were seen as motivating as a means to future financial growth. Further, Park & Choi’s (2009) findings revealed that post-secondary students were more likely to persist in distance classes when they perceived that the course was relevant to their vocation or academic program. However, Joo, Lim & Kim (2011) identified that even among students enrolled in a large elective course, course usefulness was not significantly linked to student persistence, and finding that lead the authors to conclude that course usefulness was not a strong enough variable to influence a student’s decision whether to persist or withdraw from a distance course.
Student Support Interventions
Student support was studied in several different ways among the studies analyzed. Belawati (1998) examined the impacts interventions (written contacts, reminders, instructor encouragement, brochures on learning strategies, and providing the names and addresses of classmates) had on student persistence in a correspondence distance course. While students found these interventions to be encouraging and motivating, the interventions did not significantly increase student persistence. Similarly, Muller (2008) discovered that, among women learners, support systems such as classmate support and an instructors availability through email were important supporting elements in encouraging student persistence. Student support was also studied from an external view-point, both from a student’s employers and family. When a student’s employer supported the student’s education financially, they were more likely to complete all their courses and less likely to fail, compared to those who paid for the course themselves (Zajkowski, 1997). Park & Choi (2009) found that support from the learner’s family and organizational support can also influence student persistence. Conversely, Kemp (2002) discovered that student’s external commitments (family, community, financial and home commitments), in addition to life events were not strong predictors of student persistence.
Log Analysis
Student behaviors in post-secondary distance education was another important subtopic in relation to student persistence. One such method of research this is through accessing logs. Morris, Finnegan & Wu (2005) maintain that this method “provides researches with opportunities to track not only where a student goes online within a course, but also how much time they spend at various discussions, how often they return and the various tools they use” (p. 229). Hershkovitz & Nachmias (2011) studied 1,189 students in 58 online post-secondary classes using log analysis and data mining. The findings revealed split results, indicating that 46 percent of students quit or decelerated their online activity, while 42 percent were only active towards the later part of the term or accelerated their course activity by accessing the course more frequently towards the end of the semester. Morris, Finnegan & Wu (2005) also analyzed student access traffic logs and determined that those students who do not participate, either through engaging in discussions or viewing the course content, were more likely to withdraw from their course.
Student demographic characteristics include biographical information such as grade point average, weekly hours worked, gender, age group, resiliency status and academic major (Levy, 2007). As Levy (2007) reported, there was no linkage between student persistence and a learner’s demographic characteristics among undergraduate and graduate students. Similarly, Park & Choi (2009) found learner demographics, specifically age, gender, and educational level, to be insignificant predictors in determining withdraw and attrition instances among post-secondary students in their study on 147 adult learners enrolled in one of 18 distance courses. However, it was observed by Herrell & Bower (2011) that among post-secondary students, those with higher GPAs were more likely to persist in a distance course. The authors stated the reason for this finding centered on the belief that “students with higher GPAs showed evidence that they have learned how to navigate college courses and understand what it takes to be successful in the college environment” (p. 187). Among female learners, a major barrier to persistence pertained to the need to balance multiple responsibilities (childcare, family obligations, and professional responsibilities) (Muller, 2008). The study discovered that approximately 75 percent of participants “referred to their struggles managing their responsibilities as parents and teachers” (p. 8).
Learning styles were also analyzed by Harrell & Bower (2011). According to these authors, auditory learners were more likely to withdraw from a course, compared to those who process information more effectively through written communication. The authors stated that the incongruence between an auditory preference and the written nature of online learning “could lead to frustration and eventually course withdraw” (p. 187).
Among mature aged post-secondary students, Kemp (2002) observed that student persistence was linked to four resiliency skills (initiative, generating, relationships, and insight) and five resiliency sub skills (attaching, generating resilience, recruiting, valuing, and persistence). Further, the findings showed that external commitments (personal, financial, community, and home) “were not found to be significant predictors of persistence (or lack of persistence) in distance education” (p. 75).
Student Persistence and Technology Difficulties
Students experienced technological difficulties in several of the studies analyzed. Women learners faced technological problems when attempting to access their course (Muller, 2008). In this study, participants expressed feelings of confusion when online course tools would fail to work correctly. Furthermore, there were examples of students missing online group meetings because of internet issues, computer issues or issues with the course tools. Interestingly, Harrell & Bower (2011) found that students who reported they had higher levels of computers competence were more likely to withdraw from distance classes. While the authors acknowledged this finding was unexpected, they proposed that students with “very high computer skills are more inclined than students with lower skills to succumb to the distractions of the Internet” (p. 187), and spend more time on non-course related activities online. Conversely, student’s previous experiences with distance education, and thus, their familiarity with the technological elements associated with distance learning, did not contribute to student persistence to a meaningful degree in a study of 121 undergraduate students (Kemp, 2002).
Student Persistence and Student Satisfaction & Motivation
Another important sub theme that emerged was the significance that student satisfaction and motivation had on their decision to persist or withdraw from a distance course. Data from Levy’s (2007) study on 133 students in 18 undergraduate courses reveled that student satisfaction played a critical role in predicating student persistence. Moreover, Park & Choi (2009) observed that higher levels of learner satisfaction to be significantly linked to student persistence. The authors encouraged instructors to incorporate learning activates that relate to student’s interests or goals, and at the same time, they stressed the importance of employer led recognition initiatives in an effort to motivate students to persist throughout their course. Interventions such as contacts from the course instructor, information on learning strategies, and encouragement were found to be strong motivators, resulting in feelings of acknowledgement and attention (Belawati, 1998). However, these interventions did not significantly increase student persistence.
Course Usefulness
Course usefulness, defined as the way a course is designed to guarantee the learners’ satisfaction and meet the relevant academic or job related needs (Park & Choi, 2009), was found to be an important component for student persistence in post-secondary distance courses. The vast majority (96 percent) of respondents in Zajkowski’s (1997) study on persistence in distance education indicated that higher education played a pivotal role in future professional success. Among female students, post-secondary learning opportunities were seen as motivating as a means to future financial growth. Further, Park & Choi’s (2009) findings revealed that post-secondary students were more likely to persist in distance classes when they perceived that the course was relevant to their vocation or academic program. However, Joo, Lim & Kim (2011) identified that even among students enrolled in a large elective course, course usefulness was not significantly linked to student persistence, and finding that lead the authors to conclude that course usefulness was not a strong enough variable to influence a student’s decision whether to persist or withdraw from a distance course.
Student Support Interventions
Student support was studied in several different ways among the studies analyzed. Belawati (1998) examined the impacts interventions (written contacts, reminders, instructor encouragement, brochures on learning strategies, and providing the names and addresses of classmates) had on student persistence in a correspondence distance course. While students found these interventions to be encouraging and motivating, the interventions did not significantly increase student persistence. Similarly, Muller (2008) discovered that, among women learners, support systems such as classmate support and an instructors availability through email were important supporting elements in encouraging student persistence. Student support was also studied from an external view-point, both from a student’s employers and family. When a student’s employer supported the student’s education financially, they were more likely to complete all their courses and less likely to fail, compared to those who paid for the course themselves (Zajkowski, 1997). Park & Choi (2009) found that support from the learner’s family and organizational support can also influence student persistence. Conversely, Kemp (2002) discovered that student’s external commitments (family, community, financial and home commitments), in addition to life events were not strong predictors of student persistence.
Log Analysis
Student behaviors in post-secondary distance education was another important subtopic in relation to student persistence. One such method of research this is through accessing logs. Morris, Finnegan & Wu (2005) maintain that this method “provides researches with opportunities to track not only where a student goes online within a course, but also how much time they spend at various discussions, how often they return and the various tools they use” (p. 229). Hershkovitz & Nachmias (2011) studied 1,189 students in 58 online post-secondary classes using log analysis and data mining. The findings revealed split results, indicating that 46 percent of students quit or decelerated their online activity, while 42 percent were only active towards the later part of the term or accelerated their course activity by accessing the course more frequently towards the end of the semester. Morris, Finnegan & Wu (2005) also analyzed student access traffic logs and determined that those students who do not participate, either through engaging in discussions or viewing the course content, were more likely to withdraw from their course.
DISCUSSION
The analysis conducted provided evidence that supports the argument that student persistence in post-secondary distance environments is an important area of research because the challenges adult learners face are diverse and can often be complex. While many adults view post-secondary education as a means to climbing the cooperate ladder (Zajkowski, 1997), barriers such as external commitments, support services, technical difficulties and student motivation remain strong sticking points in relation to student persistence.
Several studies revealed mixed results as to the relationship between a student’s biographical information and student persistence. Although several studies identified these pieces of information to be statistically insignificant (Levy, 2007; Park & Choi, 2009), others have found a strong linkage between student persistence in post-secondary distance courses and a student's high school GPA (Herrell & Bower, 2011). It was recommended by Herrell & Bower (2011) that student success courses be implemented and promoted to those students with lower GPAs. This course could focus on such areas as test taking strategies, time management and effective study habits. Moreover, as Muller (2008) found, female learners typically struggle with balancing multiple external responsibilities. As such, the author recommend flexible, one credit modules be introduced into academic programs to assist in alleviating some of these barriers. In addition, these courses could have flexible entry points to “allow women to stop out and return without having to repeat already completed course work” (p. 12).
Additional studies highlighted the importance of student support services, both from an academic point of view, and from an external point of view. Among female students, support systems such as classmate support and instructor availability over email were discovered to be important supporting elements in keeping students motivated (Muller, 2008). Employers who supported their employee’s post-secondary endeavors through tuition funding, improved their students persistence rates (Zajkowski, 1997). Moreover, according to Park and Choi (2009), organization support can improve student persistence. Park and Choi (2009) state that this can be achieved by communicating to the organization of the “advantages of the course in order to induce their supports” (p. 215). Furthermore, if an instructor knows that a learner is failing to receive enough organizational support, the instructor may assist this student by providing “extra attention, using appropriate motivational strategies, and providing additional internal support” (p. 215). While instructor led interventions were seen to be motivating and encouraging among students completing a correspondence distance course, Belawati (1998) found that there was no significant link to student persistence among the interventions employed in her study. The author however noted that this finding may be related to institutional specific problems that had a more significant influence on student persistence.
Findings were also varied on the topic to technological competencies and the role they play in impacting student persistence. Technological problems relating to course access were seen as an impairment to student persistence among female students (Muller, 2008). Students with higher levels of computer competence were found to withdraw at a higher rate than less technologically competent students (Harrell & Bower, 2011), while Kemp (2002) identified that previous experience with distance education was not a significant contributor to student persistence.
Results consistently reported on the need to develop distances courses in such a way that promote student engagement. As mentioned previously, student engagement is central in promoting student satisfaction and increasing levels of motivation; these are two important factors in student persistence. Promoting student engagement can be done through teamwork activates, learner centered discussions facilitated by the instructor (Joo, Lim & Kim, 2011), counseling services (Muller, 2008; Belawati, 1998), faster response times of student inquires (Muller, 2008) and through developing engaging course designs (Morris, Finnegan and Wu, 2005).
Several studies revealed mixed results as to the relationship between a student’s biographical information and student persistence. Although several studies identified these pieces of information to be statistically insignificant (Levy, 2007; Park & Choi, 2009), others have found a strong linkage between student persistence in post-secondary distance courses and a student's high school GPA (Herrell & Bower, 2011). It was recommended by Herrell & Bower (2011) that student success courses be implemented and promoted to those students with lower GPAs. This course could focus on such areas as test taking strategies, time management and effective study habits. Moreover, as Muller (2008) found, female learners typically struggle with balancing multiple external responsibilities. As such, the author recommend flexible, one credit modules be introduced into academic programs to assist in alleviating some of these barriers. In addition, these courses could have flexible entry points to “allow women to stop out and return without having to repeat already completed course work” (p. 12).
Additional studies highlighted the importance of student support services, both from an academic point of view, and from an external point of view. Among female students, support systems such as classmate support and instructor availability over email were discovered to be important supporting elements in keeping students motivated (Muller, 2008). Employers who supported their employee’s post-secondary endeavors through tuition funding, improved their students persistence rates (Zajkowski, 1997). Moreover, according to Park and Choi (2009), organization support can improve student persistence. Park and Choi (2009) state that this can be achieved by communicating to the organization of the “advantages of the course in order to induce their supports” (p. 215). Furthermore, if an instructor knows that a learner is failing to receive enough organizational support, the instructor may assist this student by providing “extra attention, using appropriate motivational strategies, and providing additional internal support” (p. 215). While instructor led interventions were seen to be motivating and encouraging among students completing a correspondence distance course, Belawati (1998) found that there was no significant link to student persistence among the interventions employed in her study. The author however noted that this finding may be related to institutional specific problems that had a more significant influence on student persistence.
Findings were also varied on the topic to technological competencies and the role they play in impacting student persistence. Technological problems relating to course access were seen as an impairment to student persistence among female students (Muller, 2008). Students with higher levels of computer competence were found to withdraw at a higher rate than less technologically competent students (Harrell & Bower, 2011), while Kemp (2002) identified that previous experience with distance education was not a significant contributor to student persistence.
Results consistently reported on the need to develop distances courses in such a way that promote student engagement. As mentioned previously, student engagement is central in promoting student satisfaction and increasing levels of motivation; these are two important factors in student persistence. Promoting student engagement can be done through teamwork activates, learner centered discussions facilitated by the instructor (Joo, Lim & Kim, 2011), counseling services (Muller, 2008; Belawati, 1998), faster response times of student inquires (Muller, 2008) and through developing engaging course designs (Morris, Finnegan and Wu, 2005).
CONCLUSIONS, LIMITATIONS AND IMPLICATIONS
Conclusions
The findings from the 10 sources suggest that student persistence in post-secondary distance education is a complex issue with unique variables such as external commitments, demographics, financial constraints, technological difficulties, adult motivation and satisfaction, and varying levels of support, ranging from institutional, family and organizational levels.
This analysis has shown that academic scholars have yet to arrive at a consensus regarding several factors that influence student persistence in post-secondary education. For example, demographic characteristics (GPA, age, gender) were found to be statistically significant predictors of student persistence among some scholars (Herrell & Bower, 2011; Muller, 2008), while others (Levy, 2007; Park & Choi, 2009; Kemp, 2002) identified no link between the two.
Moreover, the this analysis has also shown there that student support interventions are important elements in encouraging persistence (Park & Choi, 2009; Muller, 2008; and Zajkowski, 1997), and increasing levels of student motivation (Belawati, 1998).
A number of studies highlighted the importance student satisfaction and motivation has on rates of persistence. Both Leavy (2007) and Park & Choi (2009) found learner satisfaction to be significantly linked to persistence. Student motivation was also a variable in student’s perceptions of a course’s usefulness. Persistence in post-secondary education was seen a powerful motivator for future professional success and financial growth (Zajkowski, 1997; Park & Choi, 2009). However, courses must be relevant to the student’s vocation or academic program (Park & Choi, 2009).
Implications
Several implications for student persistence in post-secondary distance courses emerged from this analysis. Findings and conclusions from these studies analyzed can be helpful in aiding in the design of future online courses.
Two studies analyzed here stressed the importance of student log analysis and tools that track student behavior (Morris, Finnegan & Wu, 2005; Hershkovitz & Nachmias, 2011) among distance education facilitators. There was a resounding belief that through using this data, courses can be developed which more are engaging, not only in terms of content, but also course design and relevant discussions.
Scholars also recommended a stronger focus on student engagement throughout the distance course pedagogy. This can achieved through teamwork activities and discussions facilitated by the instructor (Joo, Lim & Kim, 2011), engaging course designs (Morris, Finnegan & Wu, 2005), and activities that are related to the student’s goals or interests.
Among employers who fund their employee’s post-secondary course, results from the studies analyzed have indicated that recognition of achievement is a strong motivator among leaners (Park & Choi, 2009). Moreover, when employers fund their employee’s post-secondary courses, rates of student persistence increase and instances of failure decreases (Zajkowski, 1997).
Limitations
Among the studies examined, there were no longitudinal students examined, leading one scholar (Kemp, 2002) to stress the need for studies spanning longer periods of time. With the exception of one study spanning three academic semesters (Morris, Finnegan & Wu, 2005), all studies in this analysis obtained data from short periods of time (two semesters or fewer). As evidence suggested that more experienced students withdraw from post-secondary distance courses at a higher rate (Levy, 2007), longitudinal studies with a focus on qualitative data would be one method of capturing information on student persistence in distance education courses throughout an academic program.
The findings from the 10 sources suggest that student persistence in post-secondary distance education is a complex issue with unique variables such as external commitments, demographics, financial constraints, technological difficulties, adult motivation and satisfaction, and varying levels of support, ranging from institutional, family and organizational levels.
This analysis has shown that academic scholars have yet to arrive at a consensus regarding several factors that influence student persistence in post-secondary education. For example, demographic characteristics (GPA, age, gender) were found to be statistically significant predictors of student persistence among some scholars (Herrell & Bower, 2011; Muller, 2008), while others (Levy, 2007; Park & Choi, 2009; Kemp, 2002) identified no link between the two.
Moreover, the this analysis has also shown there that student support interventions are important elements in encouraging persistence (Park & Choi, 2009; Muller, 2008; and Zajkowski, 1997), and increasing levels of student motivation (Belawati, 1998).
A number of studies highlighted the importance student satisfaction and motivation has on rates of persistence. Both Leavy (2007) and Park & Choi (2009) found learner satisfaction to be significantly linked to persistence. Student motivation was also a variable in student’s perceptions of a course’s usefulness. Persistence in post-secondary education was seen a powerful motivator for future professional success and financial growth (Zajkowski, 1997; Park & Choi, 2009). However, courses must be relevant to the student’s vocation or academic program (Park & Choi, 2009).
Implications
Several implications for student persistence in post-secondary distance courses emerged from this analysis. Findings and conclusions from these studies analyzed can be helpful in aiding in the design of future online courses.
Two studies analyzed here stressed the importance of student log analysis and tools that track student behavior (Morris, Finnegan & Wu, 2005; Hershkovitz & Nachmias, 2011) among distance education facilitators. There was a resounding belief that through using this data, courses can be developed which more are engaging, not only in terms of content, but also course design and relevant discussions.
Scholars also recommended a stronger focus on student engagement throughout the distance course pedagogy. This can achieved through teamwork activities and discussions facilitated by the instructor (Joo, Lim & Kim, 2011), engaging course designs (Morris, Finnegan & Wu, 2005), and activities that are related to the student’s goals or interests.
Among employers who fund their employee’s post-secondary course, results from the studies analyzed have indicated that recognition of achievement is a strong motivator among leaners (Park & Choi, 2009). Moreover, when employers fund their employee’s post-secondary courses, rates of student persistence increase and instances of failure decreases (Zajkowski, 1997).
Limitations
Among the studies examined, there were no longitudinal students examined, leading one scholar (Kemp, 2002) to stress the need for studies spanning longer periods of time. With the exception of one study spanning three academic semesters (Morris, Finnegan & Wu, 2005), all studies in this analysis obtained data from short periods of time (two semesters or fewer). As evidence suggested that more experienced students withdraw from post-secondary distance courses at a higher rate (Levy, 2007), longitudinal studies with a focus on qualitative data would be one method of capturing information on student persistence in distance education courses throughout an academic program.
REFERENCES
Belawati, T. (1998). Increasing student persistence in Indonesian post-secondary distance education. Distance Education, 19(1), 81-108.
Harrell, I. L., & Bower, B. L. (2011). Student characteristics that predict persistence in community college online courses. American Journal Of Distance Education, 25(3), 178-191.
Hershkovitz, A., & Nachmias, R. (2011). Online persistence in higher Education web-supported courses. Internet And Higher Education, 14(2), 98-106.
Joo, Y., Lim, K., & Kim, E. (2011). Online university students' satisfaction and persistence: Examining perceived level of presence, usefulness and ease of use as predictors in a structural model. Computers & Education, 57(2), 1654-1664.
Kemp, W. C. (2002). Persistence of adult learners in distance education. American Journal Of Distance Education, 16(2), 65-81.
Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers & Education, 48(2), 185-204.
Masood, M. (2004). A ten year analysis: Trends in traditional educational technology literature, Malaysian Online Journal of Instructional Technology, 1(2), 72-91.
Muller, T. (2008). Persistence of women in online degree-completion programs. International Review Of Research In Open And Distance Learning, 9(2), 1-18.
Morris, L., Finnegan, C., Wu, S. (2005). Tracking student behavior, persistence, and achievement in online courses. Internet & Higher Education. 9(1), 221-231.
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.
Zajkowski, M. E. (1997). Price and persistence in distance education. Open Learning, 12(1), 12-23.
Harrell, I. L., & Bower, B. L. (2011). Student characteristics that predict persistence in community college online courses. American Journal Of Distance Education, 25(3), 178-191.
Hershkovitz, A., & Nachmias, R. (2011). Online persistence in higher Education web-supported courses. Internet And Higher Education, 14(2), 98-106.
Joo, Y., Lim, K., & Kim, E. (2011). Online university students' satisfaction and persistence: Examining perceived level of presence, usefulness and ease of use as predictors in a structural model. Computers & Education, 57(2), 1654-1664.
Kemp, W. C. (2002). Persistence of adult learners in distance education. American Journal Of Distance Education, 16(2), 65-81.
Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers & Education, 48(2), 185-204.
Masood, M. (2004). A ten year analysis: Trends in traditional educational technology literature, Malaysian Online Journal of Instructional Technology, 1(2), 72-91.
Muller, T. (2008). Persistence of women in online degree-completion programs. International Review Of Research In Open And Distance Learning, 9(2), 1-18.
Morris, L., Finnegan, C., Wu, S. (2005). Tracking student behavior, persistence, and achievement in online courses. Internet & Higher Education. 9(1), 221-231.
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.
Zajkowski, M. E. (1997). Price and persistence in distance education. Open Learning, 12(1), 12-23.