Attrition Rate of Online Learning
WHAT INFLUENCES ONLINE CLASSES HIGH ATTRITION RATE by Lora Hines Bachelor of Science in Business Education December 1984 College of Education A Research Paper Submitted in Partial Fulfillment of the Requirements for the Master of Science in Education Degree Department of Workforce Education and Development In the Graduate School Southern Illinois University – Carbondale December 1, 2011 TABLE OF CONTENTS ChapterPage I. INTRODUCTION ………………………………………………. ………….
. 1 Background………………………………………………………………. 1 Statement of the Problem…………………………………………………. 6
Research Questions……………………………………………………….. 7 Significance of the Problem………………………………………………. 7 II. REVIEW OF RELATED LITERATURE……………………………….. ….. 9 Demographics……………………………………………………………. 10 Best Practices…………………………………………………………….. 16 Student Characteristics…………………………………………………… 24 III. CONCLUSIONS AND RECOMMENDATIONS……………………. ……. 32 Summary …… ……………………………………………………………. 32 Findings . ……….. ……………………………………………………….. 33 Recommendations………………………………………………………… 38 REFERENCES………………………………………………………….. 41 VITA……………………………….. ……………………………………52
AN ABSTRACT OF THE RESEARCH PAPER OF Lora Hines, for the Master of Science degree in Workforce Education and Development, presented on December 1, 2011, at Southern Illinois University at Carbondale. TITLE: WHAT INFLUENCES ONLINE CLASSES HIGH ATTRITION RATE MAJOR PROFESSOR: Glen Blackstone Online education programs have grown tremendously in the past 10 years. From 1991 to 2006, online enrollments have grown from virtually 0 to over 2. 35 million students. Over 3. 5 million students, or roughly one in every six, were enrolled in at least one online course during the fall of 2006.
By 2015, 25 million post-secondary students in the United States will be taking an online class. Universities worldwide are providing some type of online learning by developing courses that are available to both on-campus and off-campus students. Online education is no longer in its infancy. Students, parents, educational institutions, government, and businesses are concerned with the quality of online education. This study focuses on quality and the relationship that exists between student satisfaction and faculty effectiveness.
At issue is the question of whether “faculty effectiveness, as perceived by learners, plays a significant role in learner satisfaction” (Rehnborg, 2006, p. 1). This study reveals that students of varying age, gender, and other demographics value education differently. These differences vary among completers and non-completers, and both groups note differences in the way their instructors implement instructional practices. CHAPTER 1 INTRODUCTION Background There are many definitions for online education. These include virtual education, Internet-based education, and Web-based education.
For the purpose of this research, the definition of online education is based on Keegan’s (1988) definition of distance education. (a) the separation of teachers and learners which distinguishes it from face-to-face education, (b) an educational organization which distinguishes it from self-study and private tutoring, (c) the use of a computer network to present or distribute educational content, and (d) the provision of two-way communication via a computer network in order for students to benefit from communication with each other, teachers, and staff. Keegan, 1988, p. 4) Kaufman (as cited by Bates, 2005) suggests that there have been three generations of distance education. The first generation used one primary technology-print. The second generation integrated print and other multimedia such as video tapes, television broadcasts, and other forms of broadcast media. The third generation of distance education gave birth to online education. Online education is characterized by the use of the Internet or video conferencing to create two-way communications, connecting students and instructors.
Bates (2005) describes this communication as more equally distributed between students and instructors than in the past. In other words, while students and instructors are still separated geographically, they now have a greater ability to communicate with each other than in past generations. Students have progressively gained the ability to dialogue and use critical thinking skills rather than simple comprehension (Kaufman, 1989). Online education is well established as a viable means of education in both the corporate and academic environments, and it has taken a remarkable pace.
A survey undertaken in 2001 of online education instructors conducted by the National Education Association (NEA) indicated that 72% of online learning instructors have a positive opinion about online learning. They believe more students can be reached, learning can be customized and flexible, and interaction can increase among students (Focus, 2001). Online education programs have grown tremendously in the past 10 years. From 1991 to 2004, online enrollments have grown from virtually zero to over 2. 35 million students (Allen & Seaman, 2006).
Based on reports by over 2,200 colleges and universities, Allen and Seaman estimate growth in post-secondary online education to be more than 10 times that of other post-secondary markets. Over 4. 6 million students were taking at least one online course during the fall 2008 term; a 17 percent increase over the number reported the previous year (Allen & Seaman, 2010). The 17 percent growth rate far exceeds the 1. 2 percent growth of the overall student population. More than one in four higher education students now take at least one course online.
By 2015, 25 million post-secondary students in the United States will be taking an online class. While that happens, the classes that are taken physically on campus will plummet, from 14. 4 million in 2010 to just 4. 1 million 5 years later, according to a new forecast released by Ambient Insight; a market research firm (Nagel, 2011). Universities worldwide are providing some type of online learning by developing courses that are available to both on-campus and off-campus students. Online education is no longer in its infancy (Palloff & Pratt, 2003; Samarawickrema & Stacey, 2007).
Students, parents, educational institutions, government, and businesses are concerned with the quality of online education. Online or not online has been an ongoing debate, not only for how to preserve the value of human relations but also how to deliver course content. In a traditional or face-to-face classroom, communication and human connections are great assets for knowledge acquisition within a learning community (Allen & Seaman, 2010). When a course moves online, communication lines are altered.
Non-verbal communication cues disappear, and since students converse at different times, spontaneous interaction is impossible. Even with webcams in which students and professors can see and hear each other, interactions are not the same as in a face-to-face classroom. However, taking into consideration that online education allows students opportunities to learn independently from anywhere at any time, and to construct and acquire learning at their own pace, online education provides many advantages for students beyond the classroom walls.
We live in a changing population since more and more students entering college have grown up in today’s digital world, they possibly are “digital natives” whose brains could potentially be wired differently from the previous generation (Prensky, 2001). Draves (2002) lists ten reasons why online learning is more popular and, in his opinion, why it is better, cognitively, than in-person learning: • You can learn at your own peak learning time of day. • You can learn at your own speed. • You can learn faster. • You can interact more with the teacher and other participants. There are more topics and subjects online. • Participants come from around the world. • You can learn from the foremost authorities and experts. • Online learning is less expensive and thus more accessible. • Internet links provide more resources. • You can form a virtual community. Courses taught in an online format hold many challenges for the learner and educator alike (Howell, Williams, & Lindsay, 2003). Challenges include the need for computer literacy and navigation skills, greater electronic connection capabilities, and concerns over isolation.
Within online classes students must not only learn the course material, but also the technology skills needed to participate in class. The online learning format places the burden on students to initiate the learning process, and assume primary responsibility for the learning experience. It is likely that in this tremendous movement toward online education, faculty members will be pushed to provide more Web-based courses for both their on-campus and off-campus students. Faculty members are concerned with the quality of online courses they are developing and teaching.
While the 2000 NEA survey indicated a highly positive opinion of online courses, the faculty members expressed deep concern that online courses take more work, are more technologically challenging, and require more training and mentoring to develop and teach than traditional face-to-face courses (Focus, 2001). Maddux (2004) suggests that the increased competition for universities to offer online courses has caused campus administrators to put forth numerous online courses as rapidly as possible.
Many professors, according to Maddux, are less than a technologic expert and find themselves under pressure to produce these courses. Faculty complain that with their workload they do not have time to get adequate training and support from those on campus that provide it. Only 19 percent of institutions with online offerings report that they have no training or mentoring programs for their online teaching faculty. The most common training approaches for online faculty are internally run training courses (65 percent) and informal mentoring (59 percent) (Allen & Seaman, 2010).
Of the 10 biggest myths about synchronous online teaching, faculty training focuses on technology tools and educational best practices and is of major concern to the professors (DeMaria, & Bongiovanni, 2010). Various research studies have found a higher percentage of students taking online courses tend to drop those courses when compared to students taking traditional courses (Frankola, 2001; Oblender, 2002). Some have reported attrition from eLearning as high as 70-80% (Tyler-Smith, 2005, Flood 2002. One major reason to study student satisfaction is completion rate of non-traditional students versus traditional students. . Some educators suggest that the high drop rates should “disqualify online education as high-quality option to traditional education” (Distance Education, 2001 as cited by Diaz, 2002, para. 1). Researchers cite numerous reasons for attrition in both online and face-to-face courses. Students have work, family, and social commitments. Others lack the commitment of time or technological skills necessary to persist in the online environment.
Other reasons aside, this research paper focuses on quality and the relationship that exists between student satisfaction and faculty effectiveness. At issue is the question of whether “faculty effectiveness, as perceived by learners, plays a significant role in learner satisfactions” (Rehnborg, 2006, p. 1). Institutions retrieve student end-of-course data from students who persist and complete online courses. A review of the literature reveals a large quantity of material on faculty effectiveness, with numerous recommendations and conclusions drawn from that student end-of-course data.
There is relatively little data available from course non-completers. A 1991 study indicated that 75% of colleges and universities use the end-of-course questionnaire as a method of evaluating the effectiveness of their instructors. Though some doubt the validity of student end-of-course questionnaires, most accept the fact that they are useful in providing a measurement of the instructors’ teaching ability and directly reflect the satisfaction level of students (Ramsden, 1991). Statement of the Problem
With student diversity changing, higher education institutions are finding that it is necessary to meet the needs and demands of our nontraditional students. However, with the growth of distance learning, rates of attrition have increased significantly (Parker, 2003). Some have reported attrition from eLearning as high as 70-80% (Tyler-Smith, 2005, Flood 2002. ) Carr stated, however, that many higher education administrators believe that the completion rates of non-traditional students are 10-20% higher in online learning.
Research Questions The research questions for the paper were: 1. What similarities and differences, in terms of demographics (age, gender, ethnicity), are present in non-traditional (online) students attrition rate? 2. What affect do best practices have on non-traditional (online) student’s attrition rate? 3. What affect do student characteristics have on non-traditional (online) student’s attrition rates? Significance of the Problem Online courses are generally the first format of course offerings to fill up during registration.
Since many online courses have a high withdrawal rate, it would be beneficial for students to be placed in a course format most conducive to their learning (Dutton, Dutton, & Perry, 2002). The identification of characteristics associated with successful online students could provide the necessary information for teachers and admissions personnel to suggest or discourage a student from registering for an online course. A student mistakenly placed into a course may encounter more difficulties and have reduced changes for success compared to an appropriately placed student.
With improved technology, students may find it more convenient to take classes online in order to meet their educational needs. Changes in the student population as well as the delivery of the online course at the university may present challenges. Many interconnecting factors contribute to the numbers of students who drop out of distance education courses, many of which are beyond the institution’s control (Rovai, 2002). Rovai (2002) pointed out that this learning-sharing connection among students could provide the learner with a feeling of support from their fellow students.
Rovai’s (2002) research also suggested that there might be a possible connection between the sense of community and increased motivation resulting in increased cognitive learning. If individual circumstances affect the ability of a student to continue in an online course and if various curricular delivery and instructional methods contribute to variable outcomes, then the development of online delivery should be researched to determine the best way to serve the needs of the student enrolled in an online course. CHAPTER 2
REVIEW OF RELATED LITERATURE The advances in telecommunications and the saturation of computers into almost every home in American has drastically changed the way we communicate, the way we store and retrieve data, the way we do research, and the way we socialize. These changes in our day-to-day lives have also obliged us to rethink the way we deliver education. Public, private, and proprietary institutions have come under intense pressure to develop educational systems that are independent of time and place. Within the past 0-12 years, the growth of online course has increased tremendously. The proportion of institutions with fully online programs rises steadily as institutional size increases, and about two-thirds of the very largest institutions have fully online programs, compared to only about one-sixth of the smallest institutions. Doctoral/Research institutions have the greatest penetration of offering online programs as well as the highest overall rate (more than 80%) of having some form of online offering. (Allen & Seaman, 2006, p. 2)
Along with this growth comes the need to ensure courses are developed with some universal structure and the need for instructors to teach these courses using the best practices in the field. Student attrition is also under the microscope. The government, educators, parents, and students want assurances that online education works as well or better than its traditional face-to-face counterpart. One must understand the background and the best practices and issues that relate to student needs and satisfaction in online education. The literature review will discuss these relevant issues.
What similarities and differences, in terms of demographics (age, gender, ethnicity), are present in non-traditional (online) students attrition rate? An extensive reading of the literature reveals that face-to-face instruction includes courses in which zero to 29 percent of the content is delivered online; this category includes both traditional and web facilitated courses. The remaining alternative, blended (sometimes called hybrid) instruction is defined as having between 30 percent and 80 percent of the course content delivered online.
A course where most or all of the content is delivered online with typically no face-to-face meetings is considered an online course (Allen & Seaman, 2010). Universities want to improve graduation rates and attract non-traditional students by increasing online offerings (Allen & Seaman, 2007; 2010). According to the Allen and Seaman’s report, online students may not share the same demographics as traditional higher education students, thus, instructors need to understand the challenges of distance learning when designing online learning experiences.
The shift towards offering more online courses will continue to affect higher education institutions in ways that are not yet understood. The benefits (e. g. , convenience for institutions, instructors, and students) and the challenges (e. g. , student retention) need to be balanced to ensure that students’ outcomes of online courses are comparable with those in traditional face-to-face courses (2010). A continuing question that the researcher must consider is among those studying online education has been the issue of student retention.
Online courses typically attract students who might otherwise have not been able to attend traditional on-campus instruction, either because of work, family or other obligations. This difference in the nature of the student body has made the direct comparison of the online and face-to-face very difficult. If students tend to drop out of online classes because of work or family responsibilities, does that accurately reflect the nature of the course or the nature of the student (Allen & Seaman, 2010)? In a study completed by Dutton, Dutton & Perry (2002), the purpose was to determine how online students differ from traditional students?
There were two major categories studied. The first class of information related to the external, observable characteristics of the students. These include such things as age and gender, work, academic and childcare commitments commute distance and previous computer experience. The second information category contains preferences or considerations that are less easily observable by an outsider but may have influenced the student’s choice of online versus lecture format. Using the demographic data that Dutton, Dutton & Perry (2002) gathered from the student records, it appeared that the gender played little role in the choice format.
However, it is clear that older, non-traditional students prefer the online class. The average age of an online student’s age compared to a lecture student was more than five years greater. Nearly two-thirds of the lecture class was less than 22 years old while the same proportion of online section was older than 22. The study also determined that full-time students preferred the lecture course and the part-time students preferred the online. On average the study determined that the online students had greater outside responsibilities and that they live farther from campus.
In his dissertation, Bangurah (2004) compared students with passing grades in traditional and online courses. Student’s grades were compared across courses where the same instructor taught both online and traditional formats. Within this study, 3,601 students participated and Bangurah (2004) found that in each course and context, mean GPA’s were highest among traditional students. He also noted females who were enrolled in web-based courses outnumbered their male counterparts by nearly two-thirds. This ratio of female to male students was not found within the traditional course setting.
The claim that “the demographic differences between online and traditional students has been duly noted” (Diaz, 2002, p. 1) has mixed implications. For instance, while Gibson and Graff (1992) and Thompson (1998) concluded that online students are generally older, have a higher GPA, and have completed more credits than traditional students. There are several unidentified assumptions. First, these demographic characteristics portray a trend rather than a fixed number. Observing online education over time has indicated that students are getting younger and demographic populations are shifting (Allen & Seaman, 2010).
The Instructional Technology Council (Allen & Seaman, 2010) has reported that in 2008, 52% of students were considered traditional age; whereas, only 46% of students were considered traditional age in 2006. The second assumption is that methods of identifying online students are universal. What constitutes an online student from a traditional student may vary from institution to institution or from course to course. Lastly, demographic characteristics vary largely across the United States and should be taken into consideration when applying theory to practice.
For instance, Iowa’s minority population constitutes only 9. 4% of the student population and was ranked the fifth lowest state in terms of diversity in 2007. Thus the number of students represented by any one ethnic category is likely to be very different than population numbers from other states and vary highly from states outside of the Midwest (Iowa Department of Education, 2008). The research should consider the question of student performance and how it has also been further reviewed along lines of gender (Price, 2006; Yates, 2001). Whereas, reviously women were presumed to have an online disadvantage due to access (Kirkup & von Prummer, 1997) or family commitments (Wolf, 1998), studies have shown that enrollment is greater among females in online courses and females may in fact be more successful in the online setting (Price, 2006). In her study, Price (2006) sought to uncover gender differences in female and male students who are enrolled in online courses. In order to do so, she compared the same course in both a traditional and online setting. From 2002 to 2004, 1,991 students participated in the study from the Open University.
Two questionnaires were utilized to demonstrate course experience and academic engagement. From her study, Price (2006) was able to conclude that women were more likely to outperform their male counterparts in online course settings. In Aragon and Johnson’s study, they found no significant difference in characteristics of age, ethnicity or financial aid eligibility of students enrolled in online classes. Once again, they found that gender had significant association with completion and non-completion in online courses.
Their findings were that females completed at a higher rate than male students in an online but not face-to-face courses (2008). Additionally, it is worth noting that the thought that online instruction is eliminating many of the barriers to education for all students in general and indicated through student interviews (2008). The interviews determined that the self-reported reason for non-completion of an online class was personal and time constraints which accounted for 34% of the reasons for non-completion of their online courses, compared to 100% of the reasons given by the face-to-face students (Aragon & Johnson, 2008).
Online students often outperform traditional students when success is measured by the percentage of students that attain a grade of “C’ or above, overall classroom performance (e. g. , exam scores), or student satisfaction (Diaz, 2000). When comparing the characteristics and success of online and traditional students, Diaz found that online students received twice as many “A” grades, while traditional students received twice as many “D” and “F” grades in a general health education class. The online students were also more satisfied with multiple aspects of their course as demonstrated by their responses to an 11-question satisfaction survey.
While online students generally fared better in overall grades and grades on exams, they also dropped the course more frequently: a 13. 5% drop rate for online students versus a 7. 2% drop rate for traditional students. As Diaz noted, “. . . it seems very clear that students who enroll and persist in an online course will fare at least as well as their on-campus counterparts” (p. 95). While the use of surveys in conjunction with empirical data can often provide a more complete picture, surveys as a sole means of predicting student success and learning has been less than successful (Hall, 2008).
Employing two different survey instruments, Hall (2008) attempted to uncover which instrument would be the most accurate in determining online student success. Two hundred and twenty-eight students participated in the study which encompassed three regional community colleges in the Midwest. These students were all enrolled in at least one online course in the following areas: business, computer information services, criminal justice, and early childhood development. Hall (2008) found that the class categories were a better predictor of student success than either of the two survey instruments.
In fact, the surveys showed little than 8% accuracy in predicting final grades for these students. If online students typically possess characteristics that research has linked with academic success (e. g. , older age and more academic experience), why are they less successful in terms of persisting in a class for the full term? One possible answer is that we may have mistakenly defined “drop rate” as a characteristic synonymous with “academic non-success. ” However, I believe that many online students who drop a class may do so because it is the right thing to do.
In other words, because of the requirements of school, work, and/or family life in general, students can benefit more from a class if they take it when they have enough time to apply themselves to the class work. Thus, by dropping the class, they may be making a mature, well-informed decision that is consistent with a learner with significant academic and life experience. This explanation would be consistent with their demographics while calling into question the idea that these students are academically unsuccessful or possess inferior academic abilities. In act, a case could be made that many of the students who earn “D” and “F” grades would be better served by dropping a class. By doing so at the appropriate time, some might increase the likelihood of a successful academic career. For example, they would obviate the need to retake a course immediately, and dropping the class would not adversely affect their GPA, perhaps helping them to avoid academic probation. (Diaz, 2000, p. 3) What affect do best practices have on non-traditional (online) students? An extensive reading of the literature reveals numerous significant approaches to improving online courses.
One method is determining what may contribute or detract from a student’s success in an online course is to take a customer/business approach to the question. In other words, what is the business doing and what is the business doing that is satisfying the customer? This approach would lead researchers to look at central themes of investigation in determining the factors that contribute to or detract from student success. First the researcher must determine what aspects students perceive are important to producing success in online learning.
In the customer/business approach, it is a given that a satisfied customer is the end-point from which one works backwards to build a successful business. The literature indicates that student perceptions, attitudes, and satisfaction (Biggs, 2006; Clayton, 2004; Valasidou & Makridiou-Bolusiou, 2006) are almost certainly key in the development and instruction of online courses. According to Pearson and Trinidad (2005), hearing from students is essential to learning about what works and where improvements should be made in the future.
It is the business/customer model applied to online education. Secondly, the research should consider how educators are conducting their online courses. The scholarly literature reveals that researchers are finding several central factors related to student perceptions and the methods instructors are using to teach and design their courses. Palloff and Pratt (2003) concisely define these factors as (a) instructor support, (b) a sense of community, and (c) an appropriate use of technology in the online setting.
However, there continues to be instructor support as well as a sense of community in the traditional classroom as well. Instructor Support The foregoing conclusion for a number of years in education is that the greater the amount of instructor support, the more successful students will be in understanding and achieving the learning objectives of their courses. Sahin (2007), and Valasidou and Makrdiou-Bousiou (2006) all agree and suggest that a major predictor in online courses is instructor support.
In the online environment, students have come to expect instructor support. As an example, data from a qualitative study conducted by Motteram and Forrester (2005) revealed that students have more or less unwittingly come to believe that because of the nature of online learning as being any-time and any-place, instructors are available on a 24-7 basis, able to respond at any hour. Students not only expect instructional support, they expect it in a more expedient manner than the face-to-face student.
Another example that indicates students want and need instructor support comes from a study by Ice, Curtis, Phillips, and Wells (2007) who conducted research from Spring 2004 through Summer 2005 with 26 master’s level students and 8 doctoral students in online courses to determine if there is value in using asynchronous audio feedback in grading student work. The researchers were attempting to determine what effect, if any, the use of audio feedback might have on increasing students’ success in online courses.
In this study, five research questions were posed to determine (a) whether students preferred audio or text feedback, (b) to what degree audio feedback is an effective replacement to the interaction that takes place in a face-to-face course, (c) how audio feedback improved a sense of community, (d) in what manner is perceived learning impacted by the use of audio feedback, and (e) what relationship exists between audio feedback and student satisfaction. The results concluded that students believed that asynchronous audio feedback gave them more insight into what the instructor was trying to onvey, students experienced an increased feeling of involvement, the instructor was perceived as more caring, and content retention improved (Ice, et al, 2007). Again, a major finding of this research revealed that instructor support and involvement created what students described as a caring attitude, and this caring is a key to students’ satisfaction and, ultimately, their success in the online course. Leners and Sitzman (2006) undertook a study with online nursing students by seeking their voice in defining what online caring meant.
The research revealed the same conclusions that many other studies ( Irlbeck, 2008, & Keengwe, & Kidd, 2010) with online students have reported. What students defined as caring was the method and degree to which the instructors interacted with students and the timelines of the communication. Instructor support was, again, a key to student satisfaction. The body of literature exists in large quantities with reference to research studies revealing that both practitioners and researchers agree: Interaction between students and instructors is an important predictor of student satisfaction in online courses.
One of the major findings that Chickering and Gamson (1987) in Seven Principles for Good Practice in Undergraduate Education is just as true in online education today. It is good practice to encourage contact between students and instructors. Whether referred to as instructor, tutor, mentor, teacher or technician, students expect support and are more satisfied when they receive support from that individual. A Sense of Community Next to contact between instructor and student is the contact that emerges within what has become known as the learning community.
That community represents interaction from instructor to student and from student to student. Research conducted by Motteram and Forrester (2005) suggests that students’ relationships with fellow students emerged as a prime need in online courses. When taking an online course, students often voice feelings of solitude and the fear of learning alone. A need for interaction with other students is just as apparent in the online environment as it is within the face-to-face classroom. According to Garrison and Anderson (2003), social presence has become highly important in online education.
Social presence is defined as “the extent to which students can project their presence online when communicating in the textual milieu in the absence of visual or verbal signs” (Motteram & Forrester, 2005, p. 284). Kazmer puts forth that when students come into an online classroom they are really performing for each other, for themselves, and for the instructor. In the absence of visual and verbal cues that are normally found in the face-to-face classroom, students create for themselves an identity, and they need a variety of diverse media for interaction to articulate these online identities (2004).
Community within the adult online learning environment may be even more important than with traditional-aged students. A great body of research highlighted by Malcolm Knowles’ (1990) theory of andragogy reveals that one way adults learn is by comparing past knowledge and experiences with current experiences. Stilborne and Williams (1996) further advance the need for community in online education when teaching adult students by suggesting that providing a means for interaction and encouraging adult students to share their knowledge is essential to their style of learning.
Adult students have a lifetime of knowledge and experience to share, and finding a sense of community brings this to life. University administrators have known for some time that when students are involved in the campus community, attrition decreases. Eastmond (1995) sensed that an increased dropout rate among online students is directly related to the reduction or elimination of social and visual cures lost in an online course format; conversely, increased online community reduces the attrition rate (Rovai, 2002).
Diaz (2002) and Carr (2000) report that attrition is up to 10% higher in online courses than the face-to-face counterpart. As a course design strategy, the use of learning communities has helped reduce this attrition (Diaz, 2002), and when students persist, they become more successful in their learning and persevere to graduation. Not all students are looking for community within online courses, however. Some studies indicate that students do not necessarily desire a sense of community (Brown 2001).
In some cases, Brown learned that students simply do not wish to participate or engage in community building, while others participate based on availability of time. Other studies have indicated that students feel they are risking academic rigor if they participate in social relationships or class community building. Based on these views, Liu and Ginther (n. d. ) undertook exploratory study to determine, among other things, if students feel a sense of community in online courses and if that sense of community added to the learners’ engagement and perceived learning and satisfaction.
Their conclusion was that there are many positive relationships between sense of community and student satisfaction and perceived learning. No specific agreement between students and instructors emerged, however, on how community building should be undertaken. This led the researchers to further suggest that community building in online courses may not be as intuitive as the advocates of online community might suggest. In other words, community building needs to be intentional; it may not just happen. Analysis and synthesis of the literature explains several things regarding online learning communities.
Many students feel that social presence in an online course is essential to reducing their feelings of aloneness and solitude while other students opted for online learning because of the solitude. Still others do not participate in community building for lack of time or fear of lagging behind academically. It may be difficult to distinguish among these groups of students, but a number of instructors and researchers believe that a sense of community helps with retention and, in cases of adult students, adds significantly to the learning and knowledge acquisition process.
Diaz (2002) characterized this notion of community by suggesting that good practice would encourage cooperation and discussion among students. The literature illustrates that this principle is present in the online environment as well. Developing community will most likely require concerted design and effort on the part of the instructor. Use of Appropriate Technology Interaction among the participants in higher education, instructor to student and student to student, is generally accepted as fundamental (Liu& Ginter, n. . ). This interaction is also considered a condition to student satisfaction (Garrison & Anderson, 2003) and decreased attrition (Rovai, 2002). Therefore, as previously presented, just as a sense of community and human interaction are both expected in the face-to-face context, they are expected as well in an online learning environment. The question then becomes, what is the appropriate technology that should be implemented to best facilitate interaction and sense of community?
The two primary forms of technology that have emerged within online courses are asynchronous and synchronous interaction (Hines & Pearl, 2004). Synchronous, or real time, interaction requires that students participate at the same time. Asynchronous, or delayed time, interaction does not require students to simultaneously participate (Rose, 2006). Synchronous. Branson and Essex surveyed educators and found that instructors mostly used synchronous communication for holding “virtual” office hours, brainstorming, community building, dealing with various technical issues, and one-on-one tutoring.
The shortcomings of synchronous communications is in the logistics of getting the students together online at one time, students not participating in the faster paced chats because of poor typing skills, and less reflection time for students in formulating their answers (2001). As Hines and Pearl put it, “Synchronous chats have the advantages of providing a greater sense of presence and generating spontaneity” (2004, p. 34). Synchronous communication, however, is difficult since students may be separated by immense geographic time differences.
Maushak and Ou (2007) conducted a study to examine how well synchronous interaction facilitated collaboration among graduate students in their group work. The researchers concluded that students regarded the synchronous interaction with an instant messaging system as beneficial in collaborating on group projects and as very helpful in creating a sense of community. There was not a sense that synchronous interaction would be the appropriate method for communicating full class discussion meetings. Asynchronous.
The use of asynchronous interaction lies more in the form of discussion forums whereby students are allowed more time for reflection, where archiving of the discussion can take place, and where all students have the opportunity to participate at a more leisurely rate. Referred to as threaded discussions, these forums generally begin with the instructor or moderator submitting a question for discussion. Students then read the question and comment on it and the threads builds (Palloff & Pratt, 1999).
Many educators report more in-depth and thought provoking discussion taking place with asynchronous online interaction (Branson & Essex, 2001) than occurs in face-to-face classroom discussions. Dede and Kremer concluded that the forums produced richer, more inclusive discussions among students but are more time consuming to mediate and generally do not provide much social interaction (1999). A synthesis of the literature shows that educators have always felt that discussion adds value.
Knowledge that participants supply is often thought to add as much value to the discussin as that of the instructor (Addesso, 2000). Knowles (1990) contends that in adult learning the value added by each student is of utmost importance. Physical anonymity in online threaded discussions, according to Sweeney and Ingram, can draw out inquisitiveness, decrease inhibition, and help to bridge the gender gap, thereby increasing interaction (2001). The analysis of the literature draws the conclusion that literature regarding appropriate use of technology in online courses reveals that it is essentially content specific.
Asynchronous and synchronous interaction are not mutually exclusive, but asynchronous interaction seems to provide for a higher level of academic and intellectual communication while synchronous interaction appears to be more useful in building a sense of community in the online environment. What affect do student characteristics have on non-traditional (online) student’s attrition rates? An extensive reading of the literature reveals numerous significant approaches to improving online courses. Vincent Tinto 2008), has stated that a wide range of studies have been conducted over the last 30 years that provides definitive data as to what affects high attrition rate. As a result the university administrators have reviewed the findings and implemented a variety of changes, many in student affairs, in order to reduce the attrition rate (Tinto). However, online instruction is here to stay, and the number of online courses has increased, as have the number of conflicting discussions that have attempted to define reasons and solutions for high attrition rate among online classes (Tyler-Smith, 2005).
Online students face different issues relating to high attrition rate than do their traditional face-to-face counterparts. As Rovai (2002) stated, online students seem to have very different challenges in which to overcome when attempting to complete an online course which may involve personal distractions, variations in technological abilities, learner readiness, feelings of alienation, the instructor, and fellow students. The research will follow these factors and determine the affects these variables have upon attrition rate in the online world.
Personal Conflicts Adult students have often indicated that they were unable to attend a traditional class due to conflicts with work, geographic, or family commitments and found that online classes were more suitable to their schedule. Online courses have been designed by the educator with flexibility in mind, as the student can work at their own pace and schedule without time constraints of the face-to-face class (Galusha, 1997; Kim 2004). However, due to work commitments as well as family, many still find completion of online course restrictive (Galusha).
Many administrators believe that high attrition rate is due to the fact that online learners are traditionally older and maintain a busy work and life schedule, causing students to drop classes more often (Carr, 2000). In Carr’s research he observed that many professors noted that they frequently lose students due to work, marriage, divorce, and pregnancy’s. Carr referenced one student’s observation that older students have more clearly defined goals and seems to be comfortable working independently, rather than a younger student more ikely to drop the online class. In a study conducted by Kemp (2002), factors such as “resilience, life events, and external commitments” (p. 67) were studied to predict online attrition rate. Questionnaires were administered and compared to student records in order to determine if there was a correlation between these three factors. It was determined that resilience and work commitments were significant among the findings, but they were not conclusive due in part to an inadequate method of accumulating data and the length of the study.
Parker (1999) observed and stated that many studies of attrition focus on a single factor as the cause for high attrition rate among online courses. Diaz (2002) believes that research be conducted in order to determine the varying reasons for students to drop online courses, as did Kerka (1995) who believes that students that drop online courses should not be lumped into one category, but should be grouped into several in order to recognize the seriousness of non-completion. One should not assume that the student is dropping the class because of academic problems.
Since online learners are found to be more mature and experienced, it is assumed that the reason in dropping the class results from careful reflection. Due to outside influences, it may be better for the student to successfully complete the course at a later date (Kerka). Variations in Learning Readiness According to the National Center for Educational Statistics (2003) online learning presents itself with a tremendous presence in higher education which creates a greater demand for exploring learner readiness and student perceptions of online learning.
More specifically, research directs the literature review to an investigation of learner readiness, on-screen reading speed and comprehension, followed by typing speed and accuracy. With the dramatic increase of online learners, successful identification of learner readiness has become a priority (Shilwant & Haggarty, as cited in Watkins, 2005). Profitt (2008) discusses the need for an institutional, pre-assessment requirement, tailored toward learner readiness.
The assessment results would not only present information to advise the college and potentially at-risk students, but would also alert students, who would in turn, use the results for self-evaluation and make the decisions if they are a good fit for online learning. However; Harrell (2008) states “There could be students for whom face-to-face is a better fit, but the online environment is their only option” (as cited in Profitt, 2008, p. 27). Based on the documented learner readiness assessment, at risk students may then contact the institution of higher learning and seek xtra orientation or support services to help prevent an unpleasant online learning experience. Hsu and Shiue along with other researchers have studied individual learner readiness as a reason one might drop an online course (2005). This is a reflection of Knowles theory of andragogy, whereby the assumption of adult self-concept is made that he or she has reached a level toward self-directed learning (Knowles, 1998). Parker (1999) approved the Internet as a method for providing the “opportunity for the self-directed learner to go where no person has gone before” (p. 1).
Parker believes that in order for learning to be successful, instructional media should be carefully selected. In doing so, the online learner should take an online learner readiness quiz that assesses the ability of the student and the potential for success in an online course. READI indicates “the degree to which an individual student possesses attributes, skills and knowledge that contributes to success in online learning” (Readi. info, 2010). As noted by Willis & Lockee (2004) a determination of goodness of fit of online learning of a potential student should be assessed prior to the initiation of the distance learning commitment.
Technological Abilities The revolution of technology and the rise of the Internet age has increased the ease and accessibility to learning for the online student, thereby, allowing a greater opportunity for the autonomous learning which can be defined as “self-planned, self-organized and self-assessed learning” (Peters, 2000, p. 9). Osika and Sharp (2002) concluded that without solid technical skills, students may have a difficult time succeeding in Web-based learning environments.
Through a survey of faculty at a midsize regional commuter campus in the Midwestern United States, an inventory had been established of the minimum technical competencies faculty members believe students should possess to be successful in Web-based instruction. Additionally students at the same university were surveyed to determine how well they thought they met the minimum competencies outlined by the faculty. What was found confirmed the faculty’s concerns that students often did not possess the technical skills required to be successful in a Web-based course.
Osika and Sharp (2002) concluded that even though students are exposed to technology at a much earlier age, “this does not mean they are technically competent with the skills required to be successful with Web-based instruction” (p. 324). Muse conducted a study whereby looking at students reasons for dropping a course. He reported that many of the students found difficulties managing the software, falling behind in their course work and became frustrated and anxious, therefore, dropping the class. Today many universities have technical support that will provide guidance to the students so that they do not fall behind.
Over half of the faculty in Osika and Sharp’s (2002) study listed computer skills such as the ability to use the basic hardware on a computer, prepare word processing task, use the Internet, and send and receive e-mails, which is a prerequisite for online instruction. Students that were polled in their study claimed that they had the ability to access the Internet and word processing, but when asked specific questions about their competency levels, they were unable to do so (Osika and Sharp). However, perceived ability, on the part of the student and instructor, may not actually meet levels of competency.
Muse (2003) conducted a similar study that looked at reasons for dropping an online class. They study found that the students that had difficulties with managing the software (Blackboard, Moodle) fell behind in their assignments, therefore, making them feel anxious and frustrated. Feelings of Alienation In order for online students to succeed, they need to feel as if they are part of a “larger school community” (Galusha, 1997, p. 4). This is indicative of the lack of communication that may exist in distance education, more specifically to the lack of interaction among staff, students, materials and services.
In a study, Meyer (2001) observed that the student and teacher lack interaction as the Internet does not allow for it, which commonly occurs in the classroom. The feeling of alienation may give students even more reasons to drop out of the online course. Administrators conveyed that students identified that one problem in taking an online course is lack of personal interaction which they desire, but do not receive with online instruction (Carr, 2000). One student quoted by Carr, “…you don’t have direct contact on a regular basis with your instructor,” (p.
A39) and in order to succeed, the student must possess a level of confidence that does not require immediate feedback. Galusha (1997) also reported the lack of confidence that is required when there is a lack of immediate feedback. This is troublesome for the student, and the lack of contact was specifically identified as an area that affected the success of online students. Rovai and Wighting (2005) addressed the issue “alienation and low sense of community” (p. 101) and the relationship of student attrition in their research with a sample of graduate students at a private university in Virginia.
They felt that the study yielded “a valid predictive and explanatory tool for researchers concerned with the welfare and persistence of students in higher education programs” (p. 108). Rovai and Wighting stated that, the high quality experiences that students receive in the classroom improve student retention, therefore, these findings should be considered when developing an online class. Rovai and Wighting advised that there needs to be additional research to identify how to foster community in an online classroom in order to lower attrition, particularly among diverse cultures. CHAPTER 3
CONCLUSIONS AND RECOMMENDATIONS Summary The literature review summarized that online students have a great number of deterrents to completing an online course (Carr, 2000; Galusha, 1997; Kerka1995). Some of these deterrents include family, employment, finances, technology, instructor communication, feelings of isolation, and procrastination (Kerka, 1995). Instruction is an identifiable problem that can affect the performance of a student. There may be a problem of communication between instructor and fellow students, as well as technological difficulties on the part of the student and instructor.
Rovai (2003) states that early intervention with reference to the identifiable problems stated above will better meet the needs of the students. Student’s performance suffers when there is a lack of personal contact among the instructor and fellow students. Therefore, there is a breakdown in communication that must be enhanced when students are taking an online class. How does one enhance communication? There can be exchanges between the student/instructor through emails, virtual office hours, message boards as well as telephone communication.
There is an importance among student and instructor services for online classes. Floyd and Casey-Powell (2004) recommended five student areas that are in need of development for online learner. “Orientation, development, support, transition, and evaluation are areas that the instructor and or university must provide. ” Orientation should be given at the beginning of the online class. The instructor should develop those skills with the students through making assignments, and requiring students to log on to the course a number of times during the week. Colleges, such as John A.
Logan College offer an orientation class to their students at the beginning of each semester. They also provide support for online students. There needs to be a gradual transition into the online course, as well as mid-term evaluation and an end of semester evaluation so that the instructors can learn from those evaluations. The curricular design of the online class can provide the instruction in a meaningful manner. The course welcome or introduction should include an overview of the course establishing boundaries for the course. This would also be the time that the instructor establishes a learning community.
Findings What similarities and differences, in terms of demographics (age, gender, ethnicity), are present in non-traditional (online) students attrition rate? According to Allen and Seaman’s report, online students may not share the same demographics as traditional higher education students, thus, instructors need to understand the challenges of distance learning when designing and creating an online learning experience (Allen & Seaman, 2010). Universities want to improve graduation rates and attract non-traditional students by increasing online offerings (Allen & Seaman, 2007; 2010).
The shift towards offering more online courses will continue to affect higher education institutions in ways that are not yet understood. The benefits (e. g. , convenience for institutions, instructors, and students) and the challenges (e. g. , student retention) need to be balanced to ensure that students’ outcomes of online courses are comparable with those in traditional face-to-face courses (Allen & Seaman, 2010). Using the demographic data that Dutton, Dutton & Perry (2002) gathered from the student records, it appeared that the gender played little role in the choice format.
However, it is clear that older, non-traditional students prefer the online class. The average age of an online student’s age compared to a lecture student was more than five years greater. Nearly two-thirds of the lecture class was less than 22 years old while the same proportion of online section was older than 22. The study also determined that full-time students preferred the lecture course and the part-time students preferred the online. On average the study determined that the online students had greater outside responsibilities and that they live arther from campus. We need to close the age gap, and encourage young students to take online classes. Advertisement is the key to promoting online classes. Full-time students should be encouraged during advisement to take online classes. However, at the same time, advisors must screen potential online students in order to provide proper placement of each individual student. It may be best to first introduce the traditional learning through hybrid classes. This gives them the best of both worlds. What affect do best practices have on non-traditional (online) students?
One method is determining what may contribute or detract from a student’s success in an online course is to take a customer/business approach to the question. First of all, a determination of what is being done correctly, and what is not. This approach would lead researchers to look at central themes of investigation in determining the factors that contribute to or detract from student success. Secondly, the researcher must determine what aspects students perceive are important to producing success in online learning.
In the customer/business approach, it is a given that a satisfied customer is the end-point from which one works backwards to build a successful business. The literature indicates that student perceptions, attitudes, and satisfaction (Biggs, 2006; Clayton, 2004; Valasidou & Makridiou-Bolusiou, 2006) are almost certainly key in the development and instruction of online courses. According to Pearson and Trinidad (2005), hearing from students is essential to learning about what works and where improvements should be made in the future.
It is the business/customer model applied to online education. There needs to be more communication between the instructor and student. An instructor might assign group work, which will allow the student to get to know their fellow students, which will enhance the learning experience for the online student. Secondly, the research should consider how educators are conducting their online courses. The scholarly literature reveals that researchers are finding several central factors related to student perceptions and the methods instructors are using to teach and design their courses.
Palloff and Pratt (2003) concisely define these factors as (a) instructor support, (b) a sense of community, and (c) an appropriate use of technology in the online setting. However, there continues to be instructor support as well as a sense of community in the traditional classroom as well. Instructor Support In an online environment, students have come to expect instructor/technical support. Educational institutions should provide online support through orientation, and staff support. A Sense of Community The student needs a sense of community. This is established through a good rapport with the instructor.
The instructor needs to establish assignments that will bring the fellow students together through projects, discussion board assignments, and creating an environment where as the students may share their knowledge. Developing community will most likely require concerted design and effort on the part of the instructor. Use of Appropriate Technology The two primary forms of technology that have emerged within online courses are asynchronous and synchronous interaction (Hines & Pearl, 2004). Synchronous, or real time, interaction can occur through vi