Conflicts Online Students Encounter that Promote Attrition Case Study

The focus of this study identified a group of students using what is considered to be a trend in higher education, the online medium. Further, this study examines the established inclination that students, who attend college, both online and in introductory courses have higher attrition rates then their traditional “on campus” peers. By examining the observable traits these students display, the conclusion may be drawn that online students may deal with conflicts they encounter differently and their attrition may be attributed to more nonacademic factors than academic insufficiencies. These nonacademic influences may lead to the online students’ decision to quit instead of negotiating the conflict and successfully completing their online courses. The focus of this study is the story voiced through online faculties, who have first-hand experiences with the identified group of new students in their courses.

Due to privacy considerations, the selected population of new students taking an online course is not accessible. Therefore the online faculties, who teach these courses, have been selected to participate in an instrument that will interpret experiences and observable traits that can be measurable and without encroaching upon any identifiable students. These faculty members were not compensated for their participation, nor were they penalized for their decision not to fully complete, or participate in the anonymous study instrument. Nevertheless, there are good reasons to believe that the rate of selected respondents’ participation will be adequate enough to represent an academically valid cross-sectional value. This is because educators are assumed to be personally interested in having the actual reasons behind online an students’ high attrition being thoroughly investigated, as it will in turn help teachers to increase the extent of their professional efficiency.

This study is a case study which examines one online based institution of higher learning. While the trends revealed are evident to conclude that this study confirms some reasons that attrition rates are higher for this group. The findings will identify these drop-out factors as primarily nonacademic conflicts that these students experience. Moreover, this study will also aim to identify reasons behind a phenomenon that, despite the concept of an online learning having been considered academically legitimate for decades, up to this date not a single effective method for reducing an online students’ attrition have been worked out. This study’s approach towards tackling the absence of universally recognized tactics for encouraging online students to remain committed towards studying is based upon the hypothesis that, within the conceptual framework of a web-based education, the particulars of learners’ psychological phenotype and the particulars of their cognitive predisposition are being rarely taken into consideration.

Since the wide spread availability of the personal computer, people have found more uses to access life altering opportunities. Among this widespread usage, the area of education has likewise expanded. In 2000, the National Center for Educational Statistics reported that “91% of public four- year institutions and approximately 50% of all private institutions, representing a total of 1.6 million students, were currently offering distance education programs delivered via an online environment” (2010). Universities have been expanding these technologies to increase the availability of classes to include online, distance learning, where a student can attend a class via the computer without stepping foot in a traditional campus setting. Since the advent of the online format, online learning has emerged as the most prominent area in education raising enrolment 33% per year (Pethokoukis, 2002). The online learning environment is developed so that a student can attend a class at a particular university virtually from anywhere in the world and often times at an hour that is convenient to them. Thus, the concept of online learning can be best discussed as one among many byproducts of an ongoing technological progress, which during the course of recent decades started to gain an exponential momentum. As it was noted by Blakey (2010), “The beauty of online learning is that now the distance can be spanned through multiple interactive means through the internet rather than through the static medium of a paper or a video distance education course” (29). Nevertheless, the fact that the medium of online learning negates geographical barriers and provides educational opportunities to the fully employed individuals is not only the reason why it grows increasingly popular with more and more people. According to Brookfield (2005), the theoretical premise of online learning is being thoroughly consistent with the foremost principles of adult-oriented education, concerned with the establishment of preconditions for adult learners to be prompted to challenge prevailing ideologies, to contest hegemonies, to unmask the roots of socio-cultural oppression, to overcome alienation, to promote liberation, to reclaim reason and to practice democracy.

As distance learning developed, however, students and universities have had to make ongoing changes to facilitate issues that increasingly lead to attrition. The high rates of attrition in online courses has plagued many institutions since the onset of the implementation of the these type of programs and University concerns, for this high dropout rates, could be generally described as security, learning styles, delivery of materials, policies, technologies and life changing adaptations (Carr, 2000).

At any University, it is highly unlikely to graduate a class of one hundred percent of the admitted cohort. The long and short term goal of all universities is to have qualified students, admitted, register and ultimately graduate. A high graduation rate would be dependent on numerous factors and by both, the University and the students’ commitment, determination and resolve to gain the most from the experience. As conflicts arise, colleges and universities have to be apportioned accordingly by adapting new methods, regulations and policies, these adaptations are centered on the students themselves and their success. Students often times are faced with contradictory interpretations, expectations and experiences that occasionally can lead them to experience conflicts that can deter pursuit of a degree instead of working to resolve these problem. This, of course, undermines the effectiveness of online learning rather significantly. However, it would be inappropriate to consider online learning’ pitfalls as such that organically derive out of the very theoretical premise of this type of learning. It is important to understand that, as of today, the medium of a web-based education remains utterly innovative. This is why; as time goes on, the conventions of online learning continue to undergo a qualitative transformation, which in turn brings the element of uncertainty to the proposed approaches to increasing the efficiency of this type of education.

The purpose of the study is to explore the conflicts that some Universities face when experiencing higher online attrition rates, as well as the phenomena these entry level students face when taking distance learning classes, which could prevent them from successfully completing their degrees. This study will further examine that nonacademic reasons often times are the cause of conflicts that deter students from completing online courses. The source for this information is centered on the perspectives of the people who have the most relative relationship with these students, the professors. The legitimacy of a proposed approach to exploring this study’s subject matter is based upon the assumption that, unlike what it happened to be the case with online students, online educators posses a three-dimensional insight into the whole scope of factors that contribute to the high attrition rate among individuals that pursue web-based degrees. The professors would be the paramount source of knowing what aspects the online students individually face when considering the percentage of students who decide to withdrawal from the educational process. This study will explain, by gathering information from these professors, as to what conflicts these students perceived as not being able to resolve and overcome as well as the factors surrounding their decision to leave their programs.

This chapter will provide background as to some nonacademic reasons students drop out of online programs, a statement of the problem and purpose of this study and a credible importance of the findings. This chapter will also offer an overview of the research methods and the questions.

Background of the Problem

Students have many reasons pursuing degrees and with the changing economic climate and commitments to employers as well as family, they understand that they may not be able to attain degrees in traditional, in classroom settings. To improve their economic and social status, adults focus their method of achieving this to additional training and education (Cross, 1981). For these reasons, adult learners often times turn to the online offerings available by many universities that allow them to seek a degree while posing minimal interruption to their personal lives. The online environment offers these students an alternative method to maintain various obligations while achieving their academic goals.

The foremost preconditions, which cause the concept of a distant/online learning to grow increasingly popular with more and more people, have been outlined by Schuetze and Slowey (2002), “The increasing social demand for higher education and the rapid massification of higher education systems… structural and organizational changes associated with the diversification and increasing marketization of higher education systems…the impact of changing labor market requirements… and rising qualification requirements for many employment opportunities” (313). It is important to understand that the very laws of history, which in turn suggest the linearly nature of a technological progress, are dialectically predetermining the earlier mentioned trend. Whereas, even as recent as fifty years ago, the proper functioning of free-market economies was based upon the assumption that it is namely a financial capital and natural resources that represent the foremost economic value, by the end of 20th century this effectively ceased to be the case.

The reason for this is apparent – due to an exponential progress in the field of informational technologies, which has been taking place during the course of last few decades, it is specifically the ‘human capital’, which is now being assumed to represent a chief economic value. In its turn, the actual value of ‘human capital’ is being reflective of the extent of its intellectual potential. This is because, as of today, it became possible to replace natural resources with intellect – in a literal sense of this word. For example; whereas, 80% of the original Atlantic telephone cable’s self-cost accounted for copper, the material cost of today’s fiber-optical Atlantic telephone cable accounts for only 10%. Yet; whereas, the old cable could only sustain 128 parallel calls, the fiber-optical one sustains 750.000 parallel calls (Hoag, 2006). Therefore, it does not come as a particular surprise that, as time goes on, more and more people with even multiple college/university diplomas decide in favor of advancing further the level of their professional competence. In its turn, this brought about the concept of ‘lifelong learning’, which now is becoming increasingly incorporated into the very matrix of a Western academic curriculum.

The earlier mentioned exponential progress in the field of informational technologies provides additional incentives for people to consider enrolling into web-based academic courses. This is because, due to the emergence of Internet, the concept of distance learning had effectively ceased being solely associated with the medium of conventional correspondence. Nowadays, people can enroll into colleges and universities that are being located at the opposite corners of the globe, as Internet effectively eliminates the prolonged time-laps in the process of students and educators communicating with each other. In its turn, this causes many sociologists to go as far as suggesting that the very medium of a conventional face-to-face education has grown conceptually outdated. As it was noted by Molen (2001), “In the network society it is inescapable that the universities will have to deal with the information and communication technologies (ICT), not only for research but also for education. Some even think that universities as educational institutions will become totally virtual” (7). Such a situation has been brought about by the fact that e-learning does feature a number of distinctive characteristics, which provide online students with a wide array of educational advantages over their peers in the conventional learning environment. The foremost of these advantages can be listed as follows:

  • Nonlinearity – As compared to what it is being the case with traditional, students, online students are being in position to exercise a complete control over the structural organization of educational inputs. In its turn, this allows them to adjust the process of obtaining educational content via Internet to match their cognitive leanings with perfect precision.
  • Flexibility – Due to the qualitative characteristics of a web-based, educational medium, both: students and instructors are being provided with an opportunity to substantially increase the effectiveness of their daily schedules. The validity of this statement can be well explored in regards to the fully employed adult learners, who would be unable to pursue their much desired academic degrees, if being required to attend conventional classes. According to Clark-Ibanez and Scott (2008), “Online courses provide increased access to students who work multiple shifts or are unable to leave their homes. These students are given the opportunity to engage in so­ciological discussions and material even if they cannot attend class on campus” (35). Given the highly dynamic nature of today’s living, such an online learning’ feature does establish a full discursive legitimacy of this newly emerged educational paradigm.
  • Technological friendliness – Students’ exposure to the format of online learning does encourage them to strive to gain a basic user-proficiency in the field of informational technologies. Thus, there are good reasons to believe that, as compared to what it is being the case with students that were spared of an opportunity to actively engage with recently designed software-based educational applications, online students would be better adjusted to the realities of post-industrial living.
  • Affordability – The medium of online learning is not only being capable of eliminating geographical obstacles on the way of students pursuing the academic degrees of their choice, but financial ones, as well. After all, when compared to what are the costs of pursuing an academic degree in the conventional learning environment, the costs of pursuing web-based academic degrees may well be described as being rather negligible.
  • Non-authoritarianism – Unlike what it is being the case within the methodological framework of a face-to-face education, the effectiveness of web-based learning strategies is assumed to be dependent on instructors’ ability to collaborate with online students, throughout the course of a learning process, “Most experts in Web-based learning argue that teaching online requires a new form of pedagogy, one that is more focused on the facilitation of a collaborative process than on the delivery of content” (May & Short, 2003, 679). This particular feature of the format of online learning provides an additional confirmation to the idea that this particular educational format is indeed being discursively relevant.

Nevertheless, a practice indicates that, unlike what it is being the case with their peers in the conventional learning environment, online students are much more likely to drop out. According to Klaus and Changchit (2010), “There is a 43% attrition rate for an online section of a statistics course versus 13% for its traditional format counterpart. For a managerial marketing course the attrition rate was 24% for the online format versus a 9% rate for the traditional format” (74). The nature of this phenomenon has been discussed from a variety of different perspectives, which can be generally categorized in terms of how they advance an ‘academic’ view on the nature of online students’ attrition, on the one hand, and ‘non-academic’ view, on the other. The proponents of the first view suggest that the actual reasons why, as compared to their conventional peers, online students exhibit a clearly inadequate level of educational commitment, is that the very formal of online learning is being innately inconsistent. According to them, while in the process of acquiring a relevant web-based knowledge, online students are being spared of an opportunity to indulge in close and personal socialization with their instructors and peers (Rayan, 2002). In its turn, this significantly undermines the pace of a learning progress, on the part of online students. In addition, it became a commonplace practice among the critics of e-learning to suggest that the alleged advantages of this specific educational format are being essentially mythical. In their article, Sarker and Nicholson (2005) specify what they consider to be the primary myths of a web-based educational paradigm, “Technological connectivity implies interaction among participants in online IS (information systems) courses… For online IS courses to be effective, they should embody a student-centered learning philosophy… Any IS faculty can teach online, any IS student can learn online, and any IS course can be taught online” (60). Among other commonly heard criticisms of a web-based education are: the fact that e-learning turns technology into an education per se; whereas, technology can only supplement educational strategies, the fact that it encourages students to spend too much time living in the virtual reality, and the fact that the effects of newly emerged informational technologies on students’ ability to cope with academic assignments, have not been fully investigated.

Nevertheless, the majority of researchers promote an idea that the phenomenon of online students’ high attrition must be of an essentially non-academic nature. For example, according to Park and Choi (2009), the primary reason why the attrition rate among online students appears being particularly high is that the bulk of these students consist of adult learners, who tend to prioritize taking care of their domestic/professional responsibilities, above studying, “Most adult learners have many responsibilities for their family as well as for their job, and these two are key factors affecting adult learners’ decision to drop out of online courses” (209). The authors’ line of logic, in this respect, makes a perfectly legitimate sense. Nevertheless, given the fact that it presupposes that online students’ high academic attrition derives out their inability to effectively plan their daily schedules, it is being suggestive of online learners’ existential immaturity, which cannot be by definition, as authors themselves describe online students as the individuals endowed with an acute sense of social/educational responsibleness.

Other authors tend to tackle the issue of online students’ high attrition through the conceptual lenses of a number of motivational theories, which will be reviewed throughout this study’s consequential phases. The main premise, upon which their line of argumentation is being based, is that fact that many distant learners simply experience a lack of motivational incentives. For example, Cross ascertains that to be persistent, adults, in a non-traditional setting, need a strong motivation to achieve this goal. It is when outside (non-academic) factors become dominant the motivations to achieve these goals become less important and the student’s priorities often time result in students setting aside their intention to pursue these interests, and thus become attrition statistics (1981). Cross’s idea, in this respect, resonates with that of Paas et al. (2005), “In e-learning environments, motivation can be identified especially as a critical dimension that determines learning success and causes the high dropout rate among online learners… Cognitive load researchers need to determine the motivational effects of instructional conditions, and identify strategies that keep student attention on the learning materials without their being distracted by the world outside” (27). Nevertheless, given the fact that the factor of motivation plays a rather decisive role in prompting people to indulge in just about any activity, it would be quite inappropriate to think of that the presence/absence of this factor alone, within the methodological framework of a particular e-learning strategy, may explain the varying degree of this strategy’s effectiveness.

There are also a number of researchers that believe that it is namely the reduced level of online students’ social integration, which explains their heightened likelihood to consider the possibility of dropping out, “While online social communication has become a main component of computer use among today’s students, the use of social communication in courses, especially in online courses, is limited, and facilitation of a social network as a part of course design in higher education is rarely considered” (Misook, 2011, 77). It goes without saying, of course, that while being socially integrated in a particular academic curriculum; students will be much more likely to remain enthusiastic about proceeding with their studies. This is because, when being exposed to a highly integrative learning strategy, students will not only be able to ‘process’ the acquired knowledge more effectively, but they will also be better motivated to remain thoroughly committed to studying. The reason for this is apparent – socially integrated students are being additionally motivated to continue with their studying, as a foremost mean of maintaining their sense of self-esteem. Nevertheless, given the fact that, as it will be illustrated later, many students are being innately predisposed towards a solitary mode of studying, it would be equally wrong to think of the factor of online students’ reduced social integration as such that provides a complete explanation as to the actual essence of a high attrition, associated with e-learning.

While conducting this study’s theoretical phases, we will explore the validity of the earlier mentioned insights into what may account for the attrition-inducing factors, within the procedural framework of e-learning, at length.

Statement of the problem

This study will center on two factors causing such a high dropout rate; these would include the students’ conflicts they encountered that encouraged them to leave the program and the online aspect of the pursuit of their degree being an influenced in some way being as a determining factor in their decision to leave. “While there is now some statistical information available on distance education at higher education institutions in the United States, very few, if any, research surveys have focused on online education” (Allen and Seaman, 2003, 161). Diaz (2002) indicates that drop rates for distance classes have been consistently higher than those offered in a traditional environment and tend to indicate online learners experience less academic success than their residential counterparts. Therefore, it will only be logical, on our part; to refer to the high attrition rate among online students as such that constitutes a major challenge to the legitimacy of an online learning educational format. After all, the extent of just about any educational institution’s operative efficiency has been traditionally discussed in regards to what accounts for the retention rate among this institution’s students. At the same time, it would be inappropriate to suggest that the inconsistencies of an online learning format, which many researchers link to the unnaturally high rate of attrition among online students, are being embedded into the very theoretical premise, upon which the concept of e-learning rests. This is because, as it will be shown later, it is not only that the procedural matrix of a web-based education appears being perfectly adjusted to the highly technological realities of today’s living, but that it also undergoes a continual transformation, in order to be able to keep up with an ongoing progress in the field of informational technologies.

The focus of the research is based on the experiences the professor have with these students in online courses. By exploring the perceptions that professors, who teach online courses encounter with the students, an affirmative determination can be made that will support the theory that most on line students who leave computer based courses do so for more non-academic reasons than academic.

Purpose of the Study

By focusing the research on the professors, who have the most contact with the online students, it is the purpose of this project to explore a group of professors who teach an exclusively online course. To gain a similar baseline, these professors will be qualified by teaching or have recently taught (within 1 year) an online course, usually one that will be considered an entry level or initial experience with these exclusively online students.

By exploring the perceptions and experiences these professors have gained in these courses, an in- depth understanding of factors that influence persistence in online courses can be determined. The studies participants include full time and part time (adjunct) professors at an exclusively online University who teach on line students enrolled in undergraduate online degree completion programs by a college in the Southern Association of Colleges and Schools accreditation region offers.

The university’s online program enrolls degree seeking, adult learners in a variety of liberal arts programs. The university serves students (adult learners) in both a traditional and online environment. Herbert contends that more studies have addressed degree completion of traditional (on campus) learners then that of the distance (online learner) (2006). The purpose of this study is to gain a better understanding that online students face different challenges then traditional students. Additionally, factors unique to the online students may influence them to leave the course or university then to rely on their motivation to complete their degree. These factors will be elaborated upon at length throughout the study’s consequential phases. An argument will be provided in regards to the fact that, unlike what it is being the case with students in the conventional learning environment; online students need to possess certain psychological characteristics, potentially capable of ensuring the integrity of online students’ emotional comfortableness with the very format of an online learning. This is because, as it will be argued later, online students’ psychological compatibility with the web-based educational methodologies is the foremost precondition of their retention.

The online professors have strong opinions as to why this phenomenon exists. The instrument for this research project will now give these professors a forum to justify their reasoning as to why these drop outs are occurring. A survey instrument is the appropriate method to measure the experiences of these subjects and to quantify their responses in coded answer where the data can be interpreted to show patterned responses. Given the fact that the relevant qualitative data, which will be obtained during the course of conducting this study’s latter phases, may be quantified, there are good reasons to expect that it will provide readers with practically valuable insights as to how they may approach addressing the following set of dilemmas, concerned with the spatial subtleties of e-learning’ conceptualization:

  • What represents the adequate perception of distant/online learning? As of today, the concept of distant/online learning is being commonly referred to as having a supplementary educational role, within the procedural framework of Western academic curriculum. The dialectically predetermined nature of such state of affairs is being subtly supported by the fact that e-learning is associated with a high attrition among online students. At the same time, however, there a number of rational reasons to think of distant learning as being thoroughly consistent with the realities of post-industrial/globalized living. While analyzing the qualitative implications of an empirically obtained data, we will aim to define whether the obstacles on the way of online students striving to obtain web-based degrees are being of temporal/mechanical nature, or whether they are being predetermined by the innate subtleties of the methodology of online learning.
  • What is the significance of often clearly defined informality within the framework of web-based learning? The very fact that the process of e-learning takes place outside of conventional classrooms/auditoriums, suggests that there is a certain informality about how educators go about evaluating the extent of students’ academic progress and about how students go about addressing web-based academic assignments. Therefore, it represents a matter of academic interest to determine whether this particular aspect of e-learning contributes to many online students’ inability to remain thoroughly committed to studying.
  • What may be considered an appropriate criteria for evaluating the effectiveness of distant learning’ methodologies? As it was mentioned earlier, as of today, there have been only a comparatively few studies conducted on this particular subject matter. Therefore, while proceeding to assess the qualitative implications of an obtained empirical data, we will also aim to gain a better understanding of non-academic reasons behind online students’ attrition through the lenses of currently deployed methodological approaches towards providing distant learners with a high quality education. In its turn, this should allow us to predict the essence of circumstances, which make it challengeable to determine whether a particular student’s decision to drop out is being of academic or non-academic nature.
  • Is it possible to determine the likelihood of a particular online student to decide on favor of dropping out, in regards to the qualitative characteristics of his or her psychological constitution? If proven valid by the empirical data that is yet to be collected, this study’s premise will have one important implication. It will legitimize the idea that the most effective method of ensuring a high rate of retention among online students is subjecting them to prior-to-enrollment socio-psychological evaluation, which will determine the extent of their compatibility with the very concept of distant learning. Therefore, the survey-questionnaires that are going to be distributed among study’s participants will be designed for the specific purpose of eliciting relevant responses, in this respect.
  • Is there a link between how online students perceive the actual quality of a web-based education they strive to obtain and their heightened likelihood to drop out? As it was mentioned earlier, people’s attitude towards e-learning is far from being considered thoroughly positive, mainly because many educational institutions that offer web-based courses are being motivated to do so by the prospect of generating a quick commercial profit alone. Therefore, figuring out how a popular perception of e-learning affects students’ decision-making on whether to persist with studying or to choose in favor of dropping out, represents an additional aim of this study’s qualitative inquiry.

Research Questions

This study is to determine patterns that reflect the many variables that influence the new student’s decision to leave online courses. The primary goal of this research is to identify the non-academic reasons these students would rather quit than to work through these identified, non-academic shortcomings. The primary research questions this study is designed to address are: What reasons do new students fail to persist in online education? Do more students leave for non-academic reasons then academic inadequacies? Secondary research questions are: What are these conflicts that students experience that deter them from completing online programs? How can instructors facilitate factors or barriers that deter the students from withdrawing from online course? What support systems can online instructors incorporate to deter these students from withdrawing from on line course? How do negative factors relate to a student’s critical decision to withdraw from on line courses?

By surveying the instructors, the standpoint will generally be a more of an observational and experience driven perspective. Instructors want to see their students be successful. Success rates of students are often, justified or not, assumed the reflections of the instructors’ ability to teach the course. After all, even today, a particular instructor’s prospects of career advancement directly depend upon his or her ability to graduate as many students, as possible. Nevertheless, as practice indicates, educators cannot be held accountable for many online students’ tendency to drop out; as such their tendency often times appears being deeply embedded in the very fabric of their cognitive capacities. The fact that, as of today, students are being assumed to be equally capable of excelling in academia, regardless of what happened to be the essence of their inborn learning predispositions, adds to the problem rather substantially.

By examining a course where the same material is delivered by similarly situated instructors a valid sample will be obtained. By subjecting participated instructors’ responses to qualitative and quantitative analysis, an insight will be gained as to what may be considered the innermost causes behind online students’ attrition. Moreover, we also expect this insight to be partially indicative of the actual mechanics of how essentially non-academic motivations behind many online students’ reduced ability to remain thoroughly committed to studying, end up being referred to as such that reflect the lessened adequacy of the very paradigm of online learning.

Theoretical Framework

The theoretical background of this study will explore two widely accepted theories in the study of student attrition; Tinto’s Student Integration Model will be applied as well as Bean’s Model of Student Departure. This theoretical background is explained in detail in the following section.

These theories will be linked to the help explain the authors theory that more online students leave because of non-academic reasons then academic failures. This theory is applied in conflict by Bush and Folger (2005), It is important to elicit the wisdom and experience of adult learners as much as possible. “Thus, as we return to the ‘heat of the moment’ with the participants, it is important to elicit the ‘in conflict’ words used to describe the associated personal feelings, such as powerless, angry, stressed, over-heated, manipulated, unheard, despised, hurt, disappointed, hopeless, out-of-control, emotional, stupid, belittled, etc., …we feel weak and powerless when in conflict” (131). In order for us to be able to explain the metaphysical ground, out of which the earlier mentioned conflicts originate, we will need to expose the actual mechanics of how online students grow disappointed in remaining committed towards studying.

This study’s intentions, substance and subsequent findings have been apportioned into four additional chapters. This is followed by a detailed and thorough conclusion affirming the theory that online students have higher attrition rates due to nonacademic factors moreover than academic inadequacies. Each chapter is intended to discuss and explain the research process in detail.

Chapter two, theory model and literature review identifies these theories will be used to explain why students leave online programs and the decision making process when faced with these conflicts that perpetuate the students decision to continue through (fight) or quit (flight). Here the foundational theory of Tinto’s Student Integration Model is used to demonstrate the theory of persistence in the online environment to their eventual success of the student. This correlated with J.P. Bean’s Model of Student Departure concludes that student’s motivation is the foremost factor in determining student’s success. Nevertheless, given the fact that both theories emphasize the factor of students’ motivation as such that plays a primary role in defining the qualitative nature of these students’ attitudes towards studying and consequently their varying ability to persist with pursuing web-based academic degrees, we have also made a point in elaborating on the relevant theories of motivation at length.

Chapter two also provides a comprehensive review of the literature available, regarding various suggestion of online student attrition. The foremost insight into the operative essence of online students’ high attrition, which was gained throughout the course of conducting the earlier mentioned literature review, can be formulated as follows: there are a number of objective reasons to believe that students’ decision to drop out of a web-based academic course is being triggered by primarily non-academic considerations, on their part. Moreover, even in cases when such their decision appears to be a consequence of educators’ professional inadequacy or a consequence of web-based courses’ poor design, there is always a possibility to discuss these seemingly academic attrition-related reasons as being of an essentially non-academic essence. The reason for this is quite apparent – as the reviewed literature indicates, the ‘poor design’ of a particular online course is often being discussed in regards to its failure to take into account the particulars of every individual student’s psychological constitution. However, given the fact that the format of online learning is being conceptually different from the format of private studies, it is not up to online educators to strive to adjust web-based courses to the psychological needs of every individual student. The same argument applies to the suggestions that it is namely the lack of an online education’s interactivity (often deemed as the ‘academic’ reason behind online students’ high rate of attrition), which causes many students to decide in favor of quitting. As it was pointed out by Johnson and Pitcock (2010), “A growing body of literature suggests that some learners highly value the independent and self-directed nature of online learning, and place less value on learner-learner interactions such as collaborative group work. Such findings suggest that a blanket approach to improving online education – such as increasing learner-learner interactions – may not be warranted” (279). Throughout this proposal’s theoretical parts, the validity of Johnson and Pitcock’s idea, in this respect, will be explored at length.

The chapter three, methodology section provides a detailed explanation of the procedures that were used in acquiring first hand responses from online faculty who teach new students using the online medium. This chapter will demonstrate and explain how these voluntary participants were made aware of the study and how they were required not to identify any student during the course of participation in the course of the instrument. The development of the instrument and the measurement and coding of the instrument for the purpose of gathering information is also represented in this section.

Chapter four and five, Findings and Analysis, are designed to yield a clear comprehension of the quantified data in the case study. This information is presented in an unbiased approach to further explain the results in a precise and academic conclusion. This information is disseminated in clear and concise charts and graphs to substantiate the indicated suppositions.

These responses have been coded to further draw meaningful conclusions that affirm or deny the research questions presented. The analysis was conducted by comparing results of the instrument, identifying trends and establishing reasonable conclusions. These conclusions will support the hypothesis that factors that encourage online attrition are based more so on nonacademic conflicts than academic inadequacies.


Chapter one introduces the concept of online learning and the phenomena of the epidemic of student attrition in these online courses. It outlines the major problematic issues, faced by instructors within the spatial framework of a web-based educational curriculum. Moreover, it is being suggestive of what may be considered the discursively appropriate research-vectors, regarding the identification of metaphysical causes behind many online students’ tendency to drop out.

The theoretical framework of the research is based on a theory stated by the author that this high dropout rate is more foundational in non-academic conflicts students face than academic setback that can deter the students motivation to be successful in exclusive online degree seeking programs. The hope of this project is that these shortcomings will be identified by the professors who teach entry level students in initial courses.

Review of the Literature

Theoretical Background

Even though that the full legitimization of the concept of distant learning is assumed to have been brought about by revolutionary breakthroughs in the field of informational technologies, which had taken place throughout the course of last few decades, it is important to understand that along with purely technological prerequisites, there are many metaphysical/discursive ones for this concept to grow ever more popular. In its turn, this can be explained by the fact that the online learning environment indeed provides distant learners with a number of thoroughly objective benefits. These benefits can be conceptualized within the context of how the application of distant learning’ methodology prevents students from being subjected to the authoritarian teaching strategies (which often happens to be an integral part of the conventional learning environment), allows them much freedom in how they go about working on their homework assignments, and prompts them to choose in favor of an integrative approach towards absorbing the taught material (Wan & Howard, 2010). This creates objective preconditions for the discussion of the concept of distant learning and for the discussion of what should be considered contributive factors to the high attrition rate among online students to be consistent with the provisions of a number of classical learning theories.

For example, according to Vygotsky (1978) it is namely the fact that the majority of conventional educational strategies refer to the learning process in terms of students being ‘filled’ with essentially decontextualized information, which accounts for these strategies’ lessened degree of effectiveness “Pedagogical movements that… urged the teaching of classical languages, ancient civilizations, and mathematics have assumed that regardless of the irrelevance of these particular subjects for daily living, they were of the greatest value for the pupil’s mental development” (82). Given the fact that, unlike what it has traditionally been the case with what Vygotsky refers to as ‘conventional pedagogical movements’, the paradigm of online learning cannot be discussed outside of how the online-taught knowledge is supposed to ease the process of students addressing the challenges of their everyday living, it strengthens the validity of our earlier proposition that the key to the high rate of attrition among online students can be best conceptualized as being of essentially non-academic nature. This is because the actual aim of methodological approaches to online learning is to prompt students to never cease reflecting upon what accounts for the practical implications of their theoretical knowledge, obtained via Internet.

The fact that there can be very little rationale in considering the high rate of attrition among online students, as such that reflects the innate inconsistencies of an online-teaching paradigm, can also be illustrated in regards to the provisions of Bruner’s (1966) ‘constructivist’ learning theory. According to this theory, the process of students attaining theoretical knowledge and the process of them indulging in a variety of different cognitive tasks cannot be thought of in terms of a ‘thing in itself’, because the effectiveness of these activities reflects the extent of their attunement with the currently predominant socio-political and technological discourse “It is self-evident that each generation must define afresh the nature, direction, and aims of education… It is in this sense that education is in constant process of invention” (22). Given the fact that, as of today, there are objective preconditions for more and more educational activities to increasingly rely upon the utilization of informational technologies, the emergence of the concept of ‘online learning’ appears as such that has been predetermined by the very laws of history. This once again exposes the conceptual inconsistency of suggestions that the very paradigm of online learning is based upon innately fallacious methodological premises, which in turn would explain the high attrition rate among online students.

The provisions, contained in Hicks’s (1996) ‘discursively-interactive’ learning theory, are also being suggestive of the full appropriateness of currently deployed approaches to providing students with a web-based education. According to this particular theoretician of education, the successfulness of educational methods’ implementation depends on the measure of these methods’ discursive flexibility “Discourse is a central means through which new understandings are negotiated among participants. It is, in fact, this crucial meditational role of discourse in learning that is the focal point of the revolutionary changes occurring among educational and developmental theorists” (105). Given the fact that the paradigm of online learning presupposes participants’ continuous exposure to the spatial transformations of education-related discourses, it establishes prerequisites for online students to actively/critically engage with the received knowledge, relevant to their professional careers.

Partially, the validity of Hicks’s insights, in this respect, can be illustrated in regards to the phenomenon of memes, which nowadays proliferate almost exclusively within the informational medium of Internet. After all, it does not represent much of a secret that, as of today, the extent of one’s socio-discursive awareness is being often discussed within the context of his or her ability to understand the actual meaning of these continually transformed linguistic idioms. Because online students are expected to actively engage with the web-based learning environment, it naturally presupposes them towards assessing the significance of the studied subject matters in a highly contextualized manner, which has traditionally been considered one of the foremost predictors of academic successfulness, on students’ part. Therefore, it will prove quite impossible to agree with the criticism of online learning, which refers to a staticism as the major drawback of this type of learning “The majority of e-learning initiatives are limited on the application or the customization of learning platforms that facilitate the delivery of learning content on a predefined, static and sequential way. The flexibility of such implementations is rather inadequate to support the dynamic nature of learning” (Lytras & Pouloudi, 2001, 1185). It is not only that, while being required to deal with web-based academic assignments students get to recognize what accounts for the studied subject matter’s spatial emanations, but they also get to actively interact with the learning material that is being presented to them. Therefore, contrary to this particular provision of an e-learning’ criticism, during the course of a studying process, online students are in fact being provided with a number of different interactive opportunities. According to Marks, Sibley & Arbaugh (2005), “Interactivity in distance education is just as good as, or even better than, the traditional classroom, and recent research suggests that it is a highly significant predictor of online course outcomes” (535). The validity of this statement appears especially self-evident nowadays, when the design of the majority of web-based e-learning applications cannot be discussed outside of how these applications are expected to encourage students’ learning interactivity. Therefore, when it comes to defining the actual motivations behind the unnaturally high rate of online dropouts, it is important to understand that these dropouts cannot be discussed as such that have been triggered by online students’ reduced opportunities to actively interact with the studied materials.

The earlier deployed line of argumentation, in defense of a hypothesis that the actual causes behind the high attrition rate among online students should be assumed as being of essentially non-academic nature, suggests that in order for us to be able to effectively tackle this research’s actual subject matter, we will need to evaluate online students’ reduced capacity to remain thoroughly committed to pursuing web-based degrees through the lenses of motivational theories of education. In its turn, this will allow us to gain a preliminary insight into how the factor of motivation affects online students’ chances to obtain a diploma.

As of today, the motivational theories of education are being categorized as ‘extrinsic’, on the one hand, and as ‘intrinsic’, on the other. Whereas, the advocates of an extrinsic approach towards motivating students suggest that the motivational incentives, provided by educators, must necessarily be of clearly rationalistic nature, the advocates of an intrinsic approach believe that it is namely after students are being provided with ‘psychologically sound’ incentives to proceed with their studies that they may remain thoroughly committed to studying.

One of the foremost promoters of an extrinsic approach to motivating students has traditionally been considered Burrhus Skinner. In his books, Skinner never ceased stressing out the importance of motivation in the academic curriculum “Making sure that the student knows that he doesn’t know is a technique concerned with motivation, not with the learning process” (1968, 51). According to him, the process of providing students with proper incentives to excel in academia is being primarily concerned with educators identifying the factors that are being potentially capable of diverting students’ attention from studying and from addressing these factors. Given the fact that the foremost of education-hampering factors Skinner used to consider students’ often clearly defined inability to foresee what may account for the actual consequences of their reduced commitment to studying, it does not come as a particular surprise that he thought of the most effective educational incentive in terms of enforcement. In other words, in order for educators to be able to ensure that their students do not even consider the possibility of dropping out, teachers may never cease taking advantage of students’ ability to rationalize the consequences of their actions. When being utilized within the framework of web-based learning, the conventions of Skinner’s educational paradigm imply that many online students’ lessened commitment to studying come because of teachers’ failure to provide them with the strong enough ‘external’ educational incentives. Nevertheless, given the fact that the concept of externally enforced educational discipline has never been an integral part of the concept of distant/online learning, this again highlights the full appropriateness of a hypothesis that online students’ attrition must be of essentially non-academic nature.

Albert Bandura was another educational theorist to note that the strength of students’ commitment to studying is being reflective of the integrity of their self-motivational abilities, which he considered rationale-driven. Hence, his conceptualization of the concept of self-efficacy, which he defines as “The belief in one’s capabilities to organize and execute the courses of action required to manage prospective situations” (1995, 2). According to Bandura, in order for a particular student to be able to succeed in academia, he or she must be endowed with the sense of self-efficacy. This sense, however, cannot be referred to as having inborn subtleties. According to Bandura theory’s provisions, the sense of self-efficacy is being formed in students after they succeed with addressing the initially provided academic assignments. As time goes on, the sense of self-efficacy in students is expected to increase, because while taking an active part in the learning process, they get to observe the level of other students’ academic adequacy and to measure their own academic accomplishments against it. Eventually, students learn to think of their capacity to cope up with academic assignments not from solely institutional but also from socio-economic perspective. In its turn, this boosts up their sense of self-efficacy even further. However, the earlier outlined conceptual premise of Badura’s theory reveals its apparent weakness – the fact that, while theorizing on what should be considered contributing factors towards endowing students with the sense of self-efficacy, Bandura never considered the possibility of these factors being not of solely environmental (external) but also of psychological (internal) nature. Nevertheless, despite the earlier mentioned Bandura theory’s shortcoming, it does in fact provide us with a better understanding of the one of possible reasons behind the online students’ high attrition rate – the fact that most of them are being spared of an opportunity to pursue with their study in a highly competitive mode. At the same time, however, this should not be referred to as only the specific aspect of online learning. After all, due to the institutionalization of an ‘affirmative action’ policy in Western academic curriculum, educators often make a conscious point in trying to eliminate the spirit of competition among students – even in the environment of a conventional classroom (Adams, 1997). Moreover, given the fact that, as it was mentioned earlier, the bulk of online students consist of adults that strive to gain an additional academic degree, it would be quite inappropriate to think that their exposure to peer-competition may somehow increase the extent of these students’ educational enthusiasm.

The so-called ‘intrinsic’ approach to ensuring students’ commitment to studying derives out of Carl Rogers’s theory of motivation. According to Rogers, there are no objective reasons to believe that, while facing life’s challenges, people decide in favor of addressing these challenges in a manner that is being predetermined by purely environmental factors. In contrast to the provisions of extrinsic theories of educational motivation, Rogers’s theory is based upon the assumption that it is in people’s very nature to never cease striving towards self-actualization: “The human being is seen as having an inherent motivational system (which he shares in common with all living things) and a regulatory system (the valuing process) which by its ‘feedback’ keeps the organism ‘on the beam’ of satisfying his motivational needs. (1959, 222). Hence, Rogers’s suggestion that, in order for teachers to be able to prove their professional efficiency, they must be capable of encouraging students to derive an emotional pleasure out of their academic pursuits. Nevertheless, despite Rogers’s theory apparent soundness, there is an easily noticeable drawback to it – the fact that theory’s recommendations are based upon author’s irrational belief in the heterogeneous essence of people’s strives towards self-actualization. Such belief, however, cannot be thought of as representing an undeniable truth-value, because the strength of one’s self-actualization anxieties cannot be discussed outside of his or her endowment with the sense of perceptional individualism.

In its turn, such a sense has been long ago exposed as an extrapolation of essentially Western (Faustian) existential values. These values are based upon the assumption that “Individual’s will-power must never cease combating obstacles, that the catastrophes of existence come as an inevitable culmination of past choices and experiences, and that the conflict is the essence of existence” (Greenwood, 2009, 53). Nevertheless, given the fact that, as of today, the student body in Western countries can be best described as thoroughly multicultural, there may be no good reasons to think that the euro-centric paradigm of self-actualization, concerned with nature’s objectualization and with people’s endowment with the sense of self-discipline, applies to all students en masse, regardless of what happened to be the particulars of their ethno-cultural affiliation. After all, the very notion of self-actualization, where emphasis is being placed on self, appears quite inconsistent with non-Western (collectivist) mode of perceiving surrounding reality (Mkabela, 2005). The soundness of this suggestion can be well illustrated in regards to online students, the majority of which pursue online-based degrees in liberal sciences, because the medium of a web-based education does not correlate with pursuance degrees in technical sciences, where extensive practical experimentation is a must. Therefore, within the methodological framework of Rogers’s theory, online students’ high attrition appears being of essentially non-academic nature, because the specifics of how these students address educational challenges sublimate the qualitative aspects of their psyche’s functioning. In its turn, this explains the situations when, despite being provided with just about all the possible intrinsic incentives to continue on with studying, many online students nevertheless choose in favor of dropping out of the course.

Another educational theory, which promotes an ‘intrinsic’ approach to the conceptualization of students’ motivation and which appears being potentially capable of shedding light on the online students’ reduced ability to remain thoroughly committed to studying, is the so-called ‘experiential’ theory by David Kolb. According to this theory’s foremost provision, the successfulness of a particular learning strategy’s implementation can only be ensured by the mean of providing students with an opportunity to test their acquired theoretical knowledge in practice. This, however, should not mislead us towards a conclusion that Kolb’s theory only applies to educational processes, where students’ participation in the ‘field studies’ plays a particularly important role. After all, Kolb theory’s theoretical premise appears being thoroughly consistent with the paradigm of integrative learning, which has already been demonstrated to correlate with the paradigm of online learning “Experiential learning theory… proceeds from an assumption that ideas are not fixed and immutable elements of thought but are formed and re-formed through experience” (Kolb, 1984, 26). Nevertheless, it is namely the fact that Kolb’s theory establishes a dialectical relationship between the particulars of students’ psycho-type and their varying ability to proceed with studying, despite often unfavorable circumstances, which makes the discussion of this theory relevant to our study.

According to Kolb, students can be generally categorized as rmodators (those who tend to learn through a concrete experience), Assimilators – (those that assess the relevance of an empirical knowledge through the lenses of an abstract conceptualization), Converges – (those that tend to adjust theoretical notions to correspond to their experience-based knowledge), and Divergers – (those that assess the value of an abstract knowledge in regards to whether such a knowledge can serve as the problem-solving medium or not). Therefore, according to the author, the practical utilization of learning strategies within the academic environment, regardless of whether it happened to be of virtual or of conventional nature, should never cease being observant of students’ epistemic capabilities.

Even though that Kolb’s theory does presuppose educators’ accountability for choosing in favor of a proper educational approach, meant to apply to different categories of students, it nevertheless refers to the inborn subtleties of students’ mental constitution as such that define the innermost quintessence of their learning attitudes. When this particular provision of Kolb’s theory is being applied to address the issue of online students’ attrition, it will appear that this attrition can be best discussed as having non-academic origins. The reason for this is apparent – the very recognition of the fact that students’ attitude towards the studying does affect their academic prospects, points out to the fact that the high attrition rate among online students is being reflective of the specifics of their mentality’s functioning. In its turn, this explains why it often proves impossible to define the predictors of online students’ heightened likelihood to drop out, in regards to the actual mechanics of the deployed web-based learning strategies.

The above review of educational theories, relevant to this study’s subject matter, is far from being considered complete, of course. Nevertheless, it does provide us with the preliminary idea as to what should be thought of as the foremost challenge of applying these theories in practice, when tackling of the high attrition rate among online students is being concerned.

Importance of student retention

Distance education (also known as online education) has becoming increasingly popular in the 21st century. In fact, “by 2002 nearly 78 percent of all students had received education in some distance format” (Parker, 2003, 1). “To appeal to a larger student base, intuitions have utilized current online technologies to provide courses to those students who would not be otherwise served” (Herbert, 2006, 2). Apparently, contrary to some educators’ tendency to refer to the concept of online learning in terms of being a marginalized type of education, there can be no rationale-based reasons to think of this type of learning as having temporal subtleties. Slowly but surely, a web-based education is becoming thoroughly integrated into the very matrix of a post-industrial living. This, however, is coupled with another distinctive detail of online education, “Drop rates are among the characteristics that have routinely prompted distance education studies” (Diaz, 2002, 1). Intuitions have studied drop rates since the inception of distance learning. To understand the scope of the problem, we must examine what the benefits and liabilities that the intuitions incur by having high attrition rates, “When two colleges that enroll similar students have graduation rate gaps of twenty or thirty percentage points or more, it is fair to ask why” (Hess, et. al., 2009, 4). Educators and institutions alike are not in the business of admitting students with the intention that they will drop out prior to degree completion. The initial goal of an institution is to strive for graduating one hundred percent of the admitted in a given program, but realistically that is never the case. “There is a critical need for colleges to be able to predict with some accuracy the potential persistence of distance education students. With intuitions of higher learning generally receiving governmental support based on enrollment, the issue of student attrition is particularly important” (Parker, 2003,1). Nevertheless, it would be quite inappropriate to think that the pursuance of a corporate agenda, on the part of educational institutions, is a sole factor behind teachers’ endeavor to ensure the high rate of retention among students. It is important to understand that the proper functioning of colleges and universities, which in turn is being reflected by a high retention rate among students, is the one among foremost prerequisites of ensuring society’s integrity. After all, the more students fail to obtain their much desired diplomas, the greater would be their chances to end up being considered society’s marginalized elements.

Universities strive to produce graduates, this is the primary reason these businesses exist. To be successful, the institutions’ endeavor is to produce students who Hess, et al. (2009) define as, students who can benefit “in future earnings, in acquiring knowledge, in succeeding in the workplace and ultimately in becoming the kind of citizen on which stability and prosperity of society rest” (4). When students fail to graduate, does the university take responsibility? “Many colleges point to their academic admission or blame the student as the culprits, citing poor high school preparation and the need to enroll a diverse array [of students]” (Ibid.). Such colleges’ tendency, however, should not be regarded as being altogether irrational. After all, it fully correlates with the very paradigm of Western education, which in turn is being concerned with measuring the extent of students’ academic adequacy in regards to what accounts for their varied ability to not only memorize the obtained knowledge but also for their ability to put this knowledge into a practical use. This is exactly the reason why, despite the considerations of political correctness, which nowadays cause many educators to be afraid of even suggesting that some students’ clearly defined inability to succeed in academia may in fact has to do with these students’ underdeveloped intellectual abilities, rather than with their continual exposure to an ‘institutionalized racism’, the subtleties of students’ academic progress still remain a subject of rationale-based measurements. This suggestion applies to the paradigm of online learning, as well.

As it was noted by McPherson and Nunes (2004), “Learning is focused on performance. It involves the ability to do, rather than the ability to discourse about a subject… What constitutes expert execution of a task is obvious, and judgments about the learner’s competence emerge naturally and continuously in the context of the work” (37). Therefore, for as long as the online students’ reduced ability to persist with studying is being discussed within the framework of Western educational conventions (there are no other educational conventions to speak of), the hypothesis of this reduced ability being of essentially non-academic nature appears thoroughly plausible, by definition.

A survey of the current literature is limited when contemplating why online students choose to quit distance learning matriculation. “While there is now some statistical information available on distance education at higher education institutions in the United States, very few, if any, research studies have focused on online education” (Allen & Seaman, 2003, 15). One reason attributed to this lack of research initiated by the institutions themselves is that the perception of student success would be diminished and thus promoting a distorted view of the University by perspective students. “Since high dropout rates reflect poorly on a program, which can impact program promotion and recruitment efforts, some institutions have registration procedures that mask attrition” (Willging and Johnson, 2008, 115). One such effort is apparent at the Open University, of Scotland. Here, new students are admitted on a contingency basis for the first three months of coursework and then if they leave the program, for whatever reason, these students are purposefully not included in attrition statistics. Subsequently, they will not be included in (reported) official registration figures that boast higher than typical online graduation rates. These statistics are then made available to perspective students to influence the decision to attend the University (Guri-Rosenblit, 1999). Nevertheless, the review of the available literature, in this respect, still makes it possible to outline the foremost reasons behind the online students’ heightened rate of attrition. Out of these reasons, only one can be formally described as having a quasi-academic nature – the fact that the medium of online learning appears being ill adjusted to the pursuance of web-based degrees in highly technical academic disciplines. This is because, in order for a particular student that strives to obtain a diploma in physics, chemistry, architecture or engineering, for example, to be able to excel academically, he or she would be required to take part in a variety of different field-experimentations, “If students feel that there is a higher level of technical content, then a traditional course is preferred… Courses requiring technical skills tend to require projects. Students may prefer interaction with other students as they work on projects and thus prefer traditional courses” (Klaus & Changchit, 2010, 80). However, given the fact that online courses are being overwhelmingly concerned with allowing potential students to pursue academic degrees in specifically liberal sciences, the earlier mention attrition-contributing factor cannot be recognized as being truly acute.

Another factor, potentially capable of lessening the extent of an academic enthusiasm, on the part of online students, is that the medium of online learning presupposes the absence of physically present instructors. After all, such a presence has long become an inseparable element of a Western educational paradigm. At the same time, however, it is specifically the high school graduates who are being assumed to require close and personal guidance, while studying. This is because they simply lack life-experiences, which would have made it easier for them to adopt a proper procedural approach towards studying, in the first place. Nevertheless, given the fact that the bulk of online students consist of adult learners, it is rather unlikely for the earlier mentioned attrition-contributing factor to play an important role in undermining the effectiveness of a web-based education, as a whole.

A third factor, commonly believed to contribute to the accentuation of educational challenges, faced by online students, is the fact that the online learning format makes it harder for students to memorize the provided web-based content. This is because, as psychologists are being well aware of, in order for students to be able to memorize the factual information, relevant to a particular course they are taking, this information must also be ‘emotionally relevant’. That is, students need to be encouraged to link the freshly obtained academic knowledge with what used to be the emotional state of their mind at the time when they were in the middle of a knowledge-acquiring process. The paradigm of online learning, however, is being inconsistent with ‘emotional learning’ strategies, by definition – online students interact with their instructors and their virtual classmates via Internet, which diminishes the emotional aspects of a learning process. However, this detrimental aspect of online learning is being made less acute by another key feature of the same educational paradigm – the fact that the web-based learning strategies take a full advantage of technological breakthroughs in the field of informational technologies, which took place during the course of recent decades. Hence, the concept of ‘ancillary communication’ (based on video-conferencing), which is now being increasingly incorporated into the procedural matrix of online learning: “Video affords us (teachers) the ability to fairly rapidly evoke strong emotional response in viewers… Synchronous (technology-intensive) online learning environments afford us new capabilities that did not exist or would be difficult to implement in a traditional classroom” (Jones & Harmon, 2010, 110). Apparently, in order for educators to be able to achieve this, they need to be aware of what represents a difference between synchronous and asynchronous methodologies of subjecting online students to a particular learning strategy. Whereas, the effectiveness of an asynchronous methodology deployment’s is being hampered by the fact that it implies the existence of particularly prolonged time-lags between the process of teachers providing students with web-based academic assignments and the process of students addressing these assignments, the effectiveness of synchronous methodology implementation’s is being ensured by the absence of such a prolonged time-lags. As it was pointed out by Bernard et al. (2004), “Synchronous DE (distance learning) is defined as the time- and place-dependent nature of classroom instruction proceeding in synchronization with a DE classroom located in a remote location and connected by videoconferencing, audio-conferencing media, or both” (408). Apparently, it represents a matter of crucial importance for teachers to be able to make online students feel as if they were students proper. The reason for this is simple – while being prompted to think of themselves in these terms, online students will be much more likely to take a full advantage of their endowment with the sense of self-discipline. In its turn, this will substantially increase their likelihood to remain thoroughly committed to pursuing web-based academic degrees.

Thus, just as it is being the case with earlier mentioned learning-hampering factors, affiliated with the web-based educational paradigm, the acuteness of this particular one (online students’ emotional detachment from the acquired knowledge) also appears being continually diminished. However, given the fact that, despite being provided with an opportunity to emotionally interact with a web-based educational content, when exposed to synchronous learning strategies, many online students nevertheless continues to exhibit strongly defined dropout anxieties, this is being suggestive that the attrition-contributive factors in the medium of online learning are being of essentially non-academic nature.

Along with technology-based propositions for increasing the rate of online students’ retention, there are a number of those that can be generally referred to as ‘psychoanalytical’ ones. They rest upon the premise that, in order for an individual to be able to succeed in attaining a web-based degree, he or she would have to be mentally predisposed towards this particular type of learning. For example, according to Graff (2003), the extent of a particular student’s predisposition towards online learning can be measured in regards to what accounts for the qualitative characteristics of his or her cognitive style. Graff suggested that, just as it is being the case with students in the conventional learning environment, online students could be categorized as holistic learners, on the one hand, and as analytical learners, on the other. Whereas, holistic learners tend to approach the task of addressing academic assignments from a contextual perspective, analytical learners do so from a rationalistic/logical perspective, “They (holistic learners) make little use of categories and formal logic and instead focus on relations among objects and the context in which they interact… Analytical learners, on the other hand, adopt an ‘analytic’ perspective. They look for the traits of objects while largely ignoring their context” (410). Therefore, according to Graff, it is specifically students that can be classified as analytical learners, which are the most likely to benefit from pursuing web-based degrees, because it is in the very nature of an online learning medium to prompt students to regard the obtained knowledge as ‘thing in itself’. Essentially, Graff’s idea as to how the online students’ retention rate can be increased, is being concerned with adjusting the actual student body to the online learning paradigm, and not vice versa.

Nevertheless, despite the clearly unconventional sounding of Graff’s proposal, there is a certain rationale to it. This is because one’s analytical mindedness has been traditionally discussed as an essentially Western existential trait (Fox, 1976). In its turn, this explains why the online learning environment is being favored by overwhelmingly White students. According to Schneider and Clark (1999), “Significantly more White-Caucasian students enroll in Internet classes than non-white students… The percentages for the enrollment by ethnicity in spring 1997 are as follows: American-Indian, 0.8 percent; African-American, 5.4 percent; White-Caucasian, 75.3 percent; Asian, 4.2 percent; Hispanic, 7.7 percent” (43). Even though that Schneider and Clark’s findings, in this respect, cannot be referred as being particularly recent, they nevertheless accurately portray the essence of ethno-dynamics in today’s web-based academic curriculum. Therefore, it would only be logical, on our part, to assume that the actual reasons behind many online students’ tendency to drop out, must be of rather non-academic nature. This is because, as it was illustrated by the earlier mentioned authors, the majority of online students consists of individuals endowed with Western rationale-driven psyche, which should make them cognitively comfortable with the essentials of the online learning’ methodology. The actual implication of an earlier articulated idea is that there must be two foremost attrition-inducing factors in the web-based academic curriculum: students’ lack of time to properly address academic assignments (objective factor) and their lack of self-discipline (subjective factor). Whereas, the acuteness of the first attrition-inducing factor can hardly be reduced, unless the concerned students would be willing to drastically alter their lifestyles, the factor of lack of self-discipline, on the part of online students, can be addressed by the mean of educators applying the necessary adjustments to the process of designing web-based learning strategies.

There are, of course, a number of other conventional and not-so-conventional methods of encouraging online students to persist with studying. One method considered in the remediation of this situation is to “drop standards and hand a diploma to every student who walks through the door” (Hess, et. al., 2009, 5), but this would be a disservice to not only the student, but would discredit those intuitions by deeming these degrees as worthless. Thus, these practices would in effect cause a university to lose accreditation, while gaining the reputation as a “degree mill”. Unfortunately, the practice of lowering educational standards, as a foremost mean of helping students to attain academic degrees, it now being perceived as thoroughly legitimate. Partially, this can be explained by the fact that, as of today, the dogmas of political correctness increasingly affect the deployment of different educational strategies in Western academic curriculum. In its turn, this results in the creation of a situation when students’ failure to cope with academic requirements is being commonly discussed as the consequence of teachers’ endowment with racist or sexist prejudices, especially when the concerned students happened to be the representatives of racial minorities. As it was argued by Scott (1991), “There has been a paradoxical relationship between political correctness and anti-intellectualism that has led to the consistent undervaluation of teaching as a profession… The result is a chronically impoverished educational system that prefers rote learning to the cultivation of critical thinking” (33). Nevertheless, given the fact that a web-based education even today is being commonly discussed as something rather supplementary to an education proper, its procedural matrix still remains largely unaffected by currently predominant socio-political ideologemes. Unlike what it is now being the case with conventional students’ academic progress, the academic progress, on the part of online students, is not being looked upon as such that reflects the full appropriateness of the ‘affirmative action’ implementation, for example. This is the one among many reasons why the educational medium of online learning continues to be strongly associated with the high rate of attrition. Given the fact that the population of online students is not being ‘visually representative’, the educational institutions that provide web-based learning do not apply much of an effort into trying to artificially ensure the high rate of online students’ retention.

With increasing demands being made on colleges and universities to become more accountable to students needs and to provide the educational resources that will serve the largest percentage of the population, institutions are trying to find ways in which these needs can be met with ever changing budget limitations (Ramsden, 1998). “With the growth of distance education has come the problem of exceedingly high attrition rates” (Parker, 2003, 1). “Unfortunately, the online learning experience has not been a positive one for a substantial portion of participating students. Thus a key issue for post-secondary institutions is that of trying to find ways in which student retention in online courses can be improved” (Herbert, 2009, 2). Nevertheless, the actual key to ensuring a high retention rate among online students appears being more of ‘metaphysical’ than of solely ‘technical’ nature. The reason why, as of today, many online students decide in favor of dropping out is that, due to the currently predominant conventional outlook on e-learning as having an essentially subservient status (as compared to what it happened to be the case with conventional learning), many online students do not fully realize the sheer importance of being in a position to continually expand the scope of their professional skills (Verduin & CIark,1991). This situation, however, can be amended by the mean of educators applying an additional effort into enlightening students on the fact that the very realties of post-industrial living create objective stipulations for even the individuals with more than one college/university diploma to never cease learning. This is because in the Globalized world, it is namely people’s intellect, reflected by their possession of as many professional diplomas as possible, which represents these people’s actual worth.

Independent learning style and isolation factors

One of the foremost characteristics of a web-based education is that its theoretical premise is based upon the assumption that online students are being thoroughly capable of proceeding with their studies in an unsupervised mode. In its turn, such students’ hypothesized capacity can be conceptualized within the theoretical framework of an independent learning style, which presupposes both: students’ endowment with the sense of academic responsibleness and the spatial/qualitative limitations to the role of teachers, “The student is encouraged to become more self-reliant; more their own teacher, with both the capability and motivation to learn when no teacher is present. The teacher’s role is more of a learning manager and resource person; a co-learner” (Belton & Scott, 1998, 899). Therefore, it will only be logical to assume that, in order for online students to remain thoroughly comfortable with their exposure to this particular learning style, they must be psychologically predisposed towards it. One of the major predisposition-factors, in this respect, can be defined the measure of students’ maturity. This is because students’ age has a direct effect on the integrity of their sense of academic responsibleness – the more mature is a particular student, the greater would the likelihood for him of her to remain thoroughly committed to studying. At the same time, however, it would be wrong to refer to the extent of students’ maturity in solely physiological terms – a mature person can be defined an individual capable of operating with abstract categories and capable of understanding of how these categories are being reflective of the surrounding reality’s manifestations.

Therefore, even though the age-factor does affect the subtleties of students’ academic behavior, the extent of a particular student’s physical maturation cannot be thought of as the only objective predictor of his or her educational commitment. After all, the very realities of post-industrial living create preconditions for more and more young people to undergo the process of intellectual maturation at much faster pace, as compared to what it used to be the case with their counterparts, even as recent back as a few decades ago. As it was noted by Halx (2010), “Because humans can develop the ability to ‘think abstractly’ between the ages of 15 and 20, most undergraduate students fall somewhere on an adulthood continuum that does not necessarily divide neatly by age” (521). Nevertheless, despite the fact that, as it was argued earlier, there should be no age-related obstacles on the way of online students remaining committed to the pursuance of a web-based degree, and despite the fact that this particular learning style’s practical utilization, as an integral element of the deployed learning strategy, should in theory make it easier for students to cope with studying (because they are not being supervised at all times), the practice points out that this is far from being considered the case, “The research has indicated that students leave traditional higher education for a myriad of reasons, but research indicates online students face a greater challenge to complete” (Parker 2003, 3). Apparently, even though that the extent of a particular online student’s cognitive maturation, reflected by his or her ability to exercise an academic self-discipline, is indeed being suggestive of his or her chances of academic success, this cannot be considered as the only predictor of such an online student’s ability to prioritize studying. Let us elaborate on this suggestion at length.

The majority of educators agree that the foremost qualitative characteristic of a web-based learning process is the factor of students’ isolation (Erichsen & Bolliger, 2011). Unlike what it is being the case with students in the conventional learning environment, online students are being usually required to proceed with their studies in an essentially solitary mode. The sensation of solitude, on the part of these students, is being increased even further in cases when the qualitative essence of their web-based academic course does not relate to the actual realities of these students’ everyday living. For example, it is not utterly unusual for many online students from India, who pursue degrees in computer science at geographically remote Western universities, to be exposed to the daily sights of horse-drawn carriages, passing in front of their windows, as they study, which in turn causes these students to experience the sensation of a cognitive dissonance.

What it means is that, in order for online students to be able to proceed with studying, without considering the possibility of dropping out, they would have to be innately comfortable with the idea of a solitary learning. The implications of this suggestion can be best discussed within the methodological framework of Jungian psychoanalysis. According to Jung (1971), “Besides many individual differences in human psychology there are also typical differences. Two types especially become clear to me; I have termed them the introverted and the extraverted type… We see how the fate of one individual is determined more by the objects of his interest, while in another it is determined more by his own inner self, by the subject” (3). Whereas; extraverts are known for their socially integrated existential mode and for their collectivist mindedness, introverts are best described as highly individualistic but socially alienated individuals, who prefer to study in the solitary environment, so that nothing may divert them from their academic pursuits, “Extroversion refers to the way a person prefers to tune in to the world. It is a preference for the outer world of people and things demonstrated by a practical, active, vocal, group orientation. Introversion refers to the preference for the inner world of concepts and ideas demonstrated by a subjective, reflective, individual orientation” (Mamchur, 1981, 95).

Therefore, it will only be logical, on our part, to assume that the paradigm of online learning suits especially those individuals who happened to possess an introversive psyche, because unlike what it happened to be the case with extraverts; introverts mostly rely upon intrinsic motivations, while proceeding with their studies. And, as it was illustrated earlier, these type of motivations often prove to be the only available ones to be provided by educational institutions that offer web-based courses. The validity of this suggestion can be implicitly substantiated in regards to what constitutes a difference between how introverted and extraverted students go about addressing the reading home-assignments in the learning environment of a conventional classroom. As it was noted by Rankin (1963), students defined as extraverts are much more likely to show the lack of academic enthusiasm, when presented with the task to indulge in home-based learning activities, such as being required to read designated materials from the textbook, for example, “The greater degree of extraversion, the smaller the reliability and validity appear to be. Therefore, greater confidence can be placed in predictability of reading test results for introverts than extraverts” (116). Rankin’s observation, in this respect, is being suggestive of the fact that it is namely the introvertedly minded online students, which are more likely not to succumb to dropout anxieties, while in the process of pursuing an online degree, because the bulk of web-based academic assignments, they are being put thorough, is in fact concerned with reading.

Myers and Briggs (1975) have also explored the legitimacy of a suggestion that students’ endowment with a particular psycho-type should have an effect on their learning capacities. While agreeing with Jung as to the fact that the process of designing learning strategies, on the part of educators, should never cease being observant of what appears to be the essence of students’ innate cognitive predispositions, they hypothesized that, while in the process, educators should also take into consideration the specifics of how students reflect upon the surrounding reality. Hence, authors’ conceptualization of students as such that belong to a judging type, on the one hand, and to a perceiving type, on the other. Students that belong to the first category are known for tendency to rely on their sense of rationale, while addressing life’s challenges – hence, these students’ strive towards a well-planned and thoroughly organized personal life, which in turn presupposes their heightened chances to succeed in academic pursuits where the factor of self-discipline plays a particularly important role. Alternatively, students that belong to the second category are more predisposed to engage with the obtained knowledge in a cognitively flexible matter, which in turn causes their personal lives to be disorganized to an extent and accounts for the fact that these students appear being more inclined towards practice-based rather than theory-based academic pursuits. Within the context of our study, Myers and Briggs’s insights appear being rather ambivalent, because the very paradigm of online learning cannot be solely discussed as such that gives a well-defined preference to either theory-based or practice-based learning methodologies. Nevertheless, just as it happened to be the case with Jung’s psychoanalytical insights into the qualitative essence of people’s cognitive inclinations, Myers and Briggs’s theory does provide us with the theoretical ground to hypothesize further that the high rate of attrition among online students may in fact be explored in regards to the varying strength of these students’ affiliation with the culture-based values of individualism, egalitarianism, hierarchism and fatalism, as defined by Hofstede (1980).

According to Hofstede, there are four distinctive categories of adult learners, whose cognitive and perceptional predispositions cause them to go about addressing educational challenges in qualitatively distinctive ways:

  1. Individualists – These learners tend to adopt a particularly active stance in life, while acting as ‘existential sovereigns’. Their foremost psychological traits are: intellectual flexibility, introvertedness, rationalistic mindedness and entrepreneurial industriousness. The possession of earlier mentioned psychological traits, on their part, causes them to feel particularly comfortable when exposed to the individual-centered learning strategies. The above description of individualistically minded learners points out to the fact that the paradigm online learning is being thoroughly consistent with the innermost workings of their psyche.
  2. Egalitarians – The majority of adult learners that belong to this particular group, are being endowed with collectivist mentality, which presupposes their lessened ability to address educational challenges, without being assisted by others. They tend to perceive educational opportunities in terms of a ‘constitutionally guaranteed right’ rather than in terms of a ‘privilege’. These learners prefer to study in groups and to maintain close and personal contact with teachers, while studying. In its turn, this points out to the fact that online students that belong to this particular category are likely to experience a wide spectrum of difficulties, while trying to handle web-based academic assignments.
  3. Hierarchists – These learners believe that it is namely their affiliation with a particular social/professional strata, which defines their sense of self-identity. Hence, these individuals’ lack of intellectual flexibility, often clearly defined inability to apply a circumstantial approach to addressing educational challenges and tendency to strive to be thoroughly supervised, while studying. On the other hand, hierarchists are known for their endowment with a strong sense of self-discipline and for their mental introvertedness. In its turn, this often makes it quite impossible to define hierarchists’ chances to persist with studying, after they decide in favor of pursuing a web-based degree.
  4. Fatalists – This category of learners tend to adopt a particularly inactive stance in life, while believing that the prospects of their educational advancement do not depend on the strength of their commitment to studying. Despite being predisposed towards mental introvertedness, fatalist learners often prove their inability to apply an additional effort, when it comes to reaching one or another academic goal. This, of course, substantially undermines fatalists’ likelihood of adopting a stoic attitude towards the challenges of a web-based learning.

There are a number of good reasons to believe that the essence of non-academic motivations, behind many online students’ tendency to drop out, may in fact be explored in regards to the matrix of adult learners’ culture-based mental predispositions, provided by Hofstede. After all, as it was pointed out earlier, the manner in which students address a particular educational challenge is being reflective of how they perceive the significance of surrounding reality’s emanations. Therefore, it will only be logical to evaluate the empirical data, which is going to be obtained later, in regards of whether it is being suggestive of the existence of dialectical links between the strength of online students’ educational enthusiasm and the particulars of their cultural background.

As it was mentioned earlier, the majority of today’s social scientists consider it is a well-established fact that there is a qualitative correlation between the specifics of an individual’s racial affiliation and his or her likelihood to benefit from being exposed to either individual-centered or group-centered learning strategy. In its turn, this explains why, as of today, it is specifically those students that exhibit the psychological traits of an extravert, which are being commonly referred to as the ones more adapted for studying in the conventional learning environment, “Students who are extraverts tend to adjust better to college life, possess a better sense of well-being, and have higher academic performance… introverts, however, have the highest retention rates” (Pritchard & Wilson, 2003, 20). It could not be otherwise – the overwhelming majority of ethnically diverse (non-white) students do end up being identified as extraverts, which in turn is being consistent with the qualitative characteristics of IQ-scoring, on their part. To suggest that, under certain circumstances (when exposed to the independent learning strategies, for example), ethnically diverse students’ cognitive inclinations may in fact be undermining their chances of academic advancement, would be deemed inappropriate. The considerations of political correctness, however, do not seem to affect the actual realities in today’s Western academic curriculum. This is the reason why the very concept of online learning, as such that is being strongly associated with the implementation of a specifically independent (isolated) learning style (which only applies to students endowed with Faustian psychological traits – introvertedness, self-discipline, high IQ), appears rather incompatible with students who may only benefit from being required to indulge in highly interactive but thoroughly supervised studying.

Partially, the validity of this statement can be illustrated in regards to educators’ awareness of African-American online students’ unnaturally heightened likelihood to drop out. According to Okwumabua, Walker and Hu (2011), “Our findings depicted a less than promising outlook for African American students in a growing technological age… The ease with which they (Black students) engage in computer activities did not transfer to their experiences with online learning opportunities” (247). What has been said earlier, invariably points out to the fact that, when it comes to designing learning strategies, meant to apply to online students, educators may never cease being thoroughly aware of the full spectrum of associative factors, which are being potentially capable of affecting the actual outcomes of a learning process.

Bailey (2002) believes colleges must move to the point where student-learning styles are matched with the delivery medium. Diaz (2002) hypothesizes that locus of control in addition to learning styles, should serve as a road map for potential online students. “It is not surprising that students who prefer independent, self-paced instruction would self-select into an online class. It may be that the distance education format appealed to students with independent learning styles, and that independent learning preferences are well suited to the relative isolation of the distance learning style” (Parker, 2003, Diaz and Cartnal, 1999, 4).

The key to successfully meeting the students need for involvement is to keep the student included in the academic environment by eliminating non-social periods where the student can become disinterested or distracted, resulting in their becoming disassociated. Tinto (1993) found that a student’s sense of academic and social belonging impacts on retention graduation. “This sense of belonging is increased or decreased through interaction with the academic and social environments of the university” (McLaughlin, et. al.,1998, 2). His finding have been extended to include students expectations and has shown that institutional characteristics and culture have both indirect and direct effects on a student’s propensity to become involved in both academic and non-academic activities and thus, gains in retention. One strategy is to keep the students continually engaged and actively pursuing their degree. Research conducted by Nettles and Millett (2006) indicates that from a sample of 21 universities, 9000 doctorial students, and five fields of study (humanities, engineering, social sciences, science and mathematics, and education), “the largest predictor of steady progress in every field was continuous full time enrollment” (171). Bean’s (1980) research on student retention indicates a causal relationship between organizational elements and student satisfaction that led to reassurance or withdrawal (Herbert, 2006, 11). Without interaction from the university (student, faculty or departmental) students become socially disassociated and often times become dissatisfied and drop out of online programs.

Theories behind giving up

A number of theories provide some insight on why students may leave online based programs. The most theoretically sound of the theories is Tinto’s Student Integration Model. This model correlates the student’s persistence in the online environment to their eventual success. This is primarily linked to two personality factors, motivation and the need for socialization. The theory speculates that an online student’s success can be based on the adaptation of these two factors while functioning independently in the online environment. In essence, the provisions of Tinto’s model are being consistent with how Durkheim conceptualized the foremost social predictor of suicide – namely the lessened extent of one’s integration into society and his or her consequential likelihood to disregard the conventions of societal ethics “One can reasonably expect, then, that social conditions affecting dropout from the social system of the college would resemble those resulting in suicide in the wider society; namely, insufficient interactions with others in the college and insufficient congruency with the prevailing value patterns of the college collectivity” (1975, 92). According to Tinto, in order for a particular student to remain thoroughly committed to studying, this student must possess a clear understanding of its actual goals and to be willing to adjust its behavior to the code of corporate ethics, prevalent in a particular college or university. In case when either of the earlier mentioned predictors of educational process’s continuation is being undermined, it becomes only the matter of time before a concerned student will come to a dropout decision.

Tinto’s model of the actual mechanics of how students decide to give up on studying is easy to understand. This model presupposes that, prior to their enrollment into a particular college/university; students are being fully committed to the goal of attaining a degree. Nevertheless, as practice indicates, throughout the course of their studies, they often fail to live up to the criteria of academic excellence, adopted by a particular college or university, which is usually being reflected by their low grades. In its turn, this lowers students’ chances of an academic integration – hence, undermining the strength of their commitment to the pursuance of the initial academic goal. As a result, students decide to drop out. Alternatively, students’ lowered commitment to observing the academic policies of a particular place of learning hampers their ability to interact with more successful students, which in turn undermines the integrity of their on-campus social integration. In its turn, this causes socially alienated students to grow continually less committed to their chosen educational institution. The ultimate consequence of such a development is a dropout decision. What is particularly noticeable about Tinto’s model is the fact that it establishes direct links between students’ likelihood to follow the path of dropouts and the specifics of their upbringing, their social status and the subtleties of their psychological makeup.

A second theory that can subsequently add insight to the phenomena of student attrition is found in the writings of Indiana University professor J.P. Bean. In Bean’s (1990) Model of Student Departure, it is additionally theorized that student persistence is the foremost factor in determining student’s success (177). More specifically, behavioral intentions, which are consequently determined by a student’s beliefs, motivations and attitudes, can determine if a student is persistent when faced with a conflict, which may have him questioning his continuing in a program. “Student’s experiences within the institution, but also factors external to the institution, can affect beliefs, attitudes, and decisions” (Ibid., 181). Even though that, just as it is being the case with Tinto’s theory, the one promoted by Bean implies that the phenomenon of student-dropouts is being of essentially longitudinal essence, it nevertheless places a much stronger emphasis on specifically environmental factors that contribute to students’ eventual decision to leave college/university. According to Bean (1982), the major variables that are being potentially capable of affecting a manner in which students tackle ‘drop out or not drop out’ issue, include “Intent to leave (the estimated likelihood of discontinuing one’s membership in the organization), Practical value (the degree to which one’s education is believed useful for getting a job), Certainty of choice (the degree to which the student is certain that the institution is the right choice), Loyalty (the importance of graduating from this institution, not another), and Grades (University grade point average)” (293). One of the most peculiar aspects of Bean’s theory is that, despite a clearly qualitative essence of the early mentioned contributive factors, which are believed to lead to attrition in academia; it does provide a quantitative matrix for these factors’ evaluation.

Kember’s (1989) theory of academic attrition is based upon essentially the same set of assumptions, as it is being the case with the theory promoted by Bean. Essentially, the foremost idea advocated by Kember is the fact that online students’ chances to integrate into the learning process have clearly defined longitudinal characteristics, “The student’s goals and the degree of commitment to them will have been influenced by the individual’s upbringing, edu­cational background, and current family and work circumstances… These same components essentially define the social and work environment and therefore strongly influence the necessary integration of the study pro­cess into the student’s life style” (292). According to Kember, it is not only that the extent of these students’ commitment to studying must be discussed in relation to a number of different ‘external’ variables, such as the qualitative aspects of their upbringing, their social status and their affiliation/non-affiliation with a particular subculture, but that it also must be viewed as having a spatially transformative essence. That is, in order for educators to be position of ensuring the effectiveness of a learning process, designed to correlate with online students’ cognitive characteristics and with the qualitative aspects of their attitudes towards studying, they must remain thoroughly aware of what may account for ‘environmental triggers’ of lessening the strength of online students’ educational commitment.

According to the conventions of Rovai’s (2003) ‘persistence’ model, which theorizes on what can be considered the objective preconditions for online students to choose in favor of dropping out, there are in fact two prior-to-admission variables and two after-admission variables, which have a strong effect on students’ likelihood to decide to drop out of the course. Among the first-type variables, Rovai lists students’ socio-economic characteristics and the level of their educational attainment, prior to enrolling into a particular web-based academic course. Among the second-type variables, he lists the level students’ social integration, the hours of their employment, the integrity of their sense of self-esteem, etc. Nevertheless, it is specifically online students’ ability to exercise self-discipline, while coping with web-based academic assignments, which Rovai considers one among the foremost predictors of such students’ retention, “Success in online courses typically requires a high level of discipline and self-direction, and enough time each week to complete all assignments… Because classes do not meet in the traditional sense, some students must be motivated to begin course work on time, keep up with assignments, and actively participate” (14). At the same time, however, Rovai’s theory does not specify what amounts to the objective prerequisites for online students to be endowed with the sense of self-discipline, in the first place.

A phenomenon of student attrition can also be addressed within the methodological framework of Abraham Maslow’s (1970) theory of motivation. According to this American psychologist, the spectrum of just about all human motivations appears hierarchically structured – hence, Maslow’s famous The Hierarchy of Needs conception. The foremost premise of this conception is based upon the assumption that people’s needs can be categorized as animalistic/physiological, on the one hand, and intellectual/metaphysical, on the other. After having satisfied their physiological needs (or first-order needs), concerned with ensuring a plenty of food, water and sex, people begin aspiring to satisfy their second-order needs, such as finding a well-paid job and securing their social positioning. After that, people usually move on to satisfy their third-order and fourth-order needs, such as striving to attain the sense of self-esteem and the respect of others. The top of Maslow’s ‘pyramid of needs’ features people’s longing for self-actualization.

Within the context of our study, the implications of Maslow’s theory are quite apparent. Given the fact, that people’s decision to pursue with attaining an online degree is being clearly fueled by their heightened desire to achieve a self-actualization, it will only be logical to assume that the phenomenon of student-attrition should be discussed as an extrapolation of the process of students growing increasingly indifferent towards the prospect of self-actualization. In its turn, this usually comes as a result of these students’ lower-order needs remaining dissatisfied.

Nevertheless, there is one more aspect of Maslow’s conceptualization of self-actualization, which appears especially relevant to this study’s subject matter – the fact that Maslow used to distinguish between ‘regular’ and ‘transcendent’ or ‘metamotivational’ modes of self-actualization. According to him; whereas, the majority of regularly motivated individuals tend to think of the concept of self-actualization as something rather instrumental (for them, being a self-actualized individual is synonymous to being socially prominent individual), ‘metamotivated’ individuals think of self-actualization in terms of a never-ending process, which represents a high metaphysical value as ‘thing in itself’. That is, they actually derive much more pleasure out of remaining on the path towards achieving a particular goal, then out of realizing the fact that their goal has been achieved. While referring to ‘metamotivated’ individuals, Maslow said “They spontaneously tend to do right, because that is what they want to do, what they need to do, what they enjoy, what they approve of doing, and what they will continue to enjoy” (1968, 45). Such Maslow’s idea is being fully correlative with what appear to be the existential emanations of one’s Faustian mentality, mentioned earlier. Therefore, it will only be logical to expect the attrition rate to be significantly higher among online students that, due to the specifics of their psyche’s functioning, are being incapable to enjoy the actual process of addressing web-based academic assignments.

The validity of Maslow’s thesis, in this respect, is being implicitly supported by the conventions of neo-compatibilism in philosophy. According to the proponents neo-compatibilism, in order for a particular individual to be considered as such that is being endowed with a free will, he or she must be capable of subjecting its first-order desires to its second-order desires. For example, one may be equally motivated to indulge in two mutually exclusive activities – drinking beer or studying. However, given the fact that, according to Maslow’s hierarchy of needs, the first activity can be best described as being the realization of one of many first-order/animalistic desires, such an individual will only benefit from choosing in favor of the second activity. The reason for this is apparent – by deciding in favor to proceed with studying, one will be consciously elevating itself above its own physiological limitations and its rationale-blind anxieties. As it was pointed out by Watson “Reason is an original spring of responsible action… It is appropriate to speak of the wants that are (or perhaps arise from) evaluations as belonging to, or originating in, the rational (that is, judging) part of the soul; values provide reasons for action” (1975, 208). This suggestion directly relates to our study’s subject matter. This is because; whereas, a good share of students in the conventional learning environment proceeds with attending lectures because they are being forced to do so by their parents, for example, there are absolutely no substantiated reasons to think that this may also be the case with students that pursue web-based degrees. As it was mentioned earlier, the bulk of online students consist of responsible adults. Therefore, the fact that many of them nevertheless end up dropping out may in fact signify these people’s lessened ability to exercise self-discipline, while facing life’s challenges. The validity of this suggestion can be illustrated further in regards to the fact that, as of today, the growing number of educators in Western colleges and universities make a deliberate point in referring to the concept of self-discipline as the byproduct of people’s euro-centric arrogance and therefore, as such that is being inconsistent with the provisions of political correctness.

Although there can be few doubts as to the fact that, while reacting to educational challenges, different individuals behave differently, the spatial characteristics of their learning-behavior may be well conceptualized along the lines of a behavioral model, provided by Nair (2010). This model stresses out the linear subtleties of a process of how adult learners, required to adopt a certain behavioral mode while exposed to a certain situation, go about formulating such a mode. According to the author, the consequent phases of individual’s behavior fit into the following conceptual framework – stimulus (input), sensation, perception, core cognitive process, decision making, action taking (output). Nevertheless, even though Nair’s model implies that learners come to choose in favor of a certain course of action in an essentially similar manner, which means that it is possible to work out a formula for predicting what would account for the circumstantial essence of their attitude towards studying, the objective reality points out to something entirely different. People often act in a way quite inconsistent with the predictions of how they should be acting. Apparently, ‘perception’ and ‘core cognitive process’ phases of a decision-making process are being greatly affected by the particulars of how a concerned person perceives the qualitative significance of an ‘input’. Therefore, it will only be logical to presuppose that the specifics of an individual’s ethno-cultural background play a rather substantial role in defining his or her attitudes towards studying, “The culture as a whole provides the members of any society with an indispensable guide in all the affairs of life” (Linton,1999, 13).

Nevertheless, the exact reasons students drop out of online programs cannot be determined with a high degree of precision, only theorized. Some factors can be pointed to, but no substantial research is available to pinpoint exactly why this occurs and often times occurs at a substantially higher rate than traditional residential based programs. Frankola (2001) hypothesizes that “no national statistics [exist], but a recent report in the Chronicles of Higher Education found that intuitions report dropout rates ranging from 20 to 50 percent for distance learners” (55). Again, this information is cited from an institution based source, the actual numbers of attrition may be higher when examining those not reported as officially being enrolled or admitted. She adds, “To date, no one has researched and published online student persistence rates and reasons for dropout in computer-conferenced classes, most probably because the computer conferencing format is so new” (Ibid.).

The Online and the Traditional Student

This case study indirectly involves the traditional, on campus students. Before exploring these students’ reasons they dropped out of the observed program, we must initially examine the online learner to determine if he exemplifies a type of “at risk student” who would be more amenable to withdrawing from an online program when faced with a conflict, or if they would be more likely to find alternative means of persistence when resolving the conflicts he faces. However, before we do that, we will need to identify the qualitative features of an online learning medium. These features can be outlined as follows:

  1. The separation of teacher and learner – Unlike what it is being the case with students that pursue their degrees in the conventional learning environment, the majority of online students are being deprived of an opportunity to actively interact with teachers. This is because the methodology of face-to-face lecturing, commonly utilized in the conventional learning environment, is being inconsistent with the very concept of distance education, in the first place. In its turn, this implies that, within the framework of online learning, there is always a possibility for the educational web-based content, conveyed to online students, to be perceived by them in a qualitatively different manner, as compared to what it is being the case with conventional students perceiving the educational content in the classroom-based learning environment, “In DE (distance education), media may transform the learning experience in ways that are unanticipated and not regularly available in face-to-face instructional situations… The use of computer-mediated communication means that students must use written forms of expression to interact with one another in articulating and developing ideas” (Bernard et al., 2003, 382). This, of course, implies that, while exposing online students to a particular learning strategy, teachers will benefit from remaining thoroughly aware of both: online learning’ conceptual advantages and disadvantages.
  2. The fact that, while in the process of learning, students’ attitude towards studying is being continually influenced by an affiliated educational organization – Even though that online students are assumed being in a position to enjoy much more academic freedom, as compared to what it is being the case with their peers in conventional auditoriums, they are still expected to conform to the enforced educational criteria and to the code of corporate ethics. This implies the sheer inappropriateness of drawing parallels between the matrix of distance learning and the matrix of private studying. After all, unlike individuals that indulge in private studying, the educational progress, on the part of online students, remains the subject of periodical evaluations.
  3. The extensive utilization of informational technologies – In order for distant learners to qualify for attaining a web-based education, in the first place, they need to possess computer-skills. This, of course, reduces the scope of potential candidates for enrollment in web-based courses. However, it also provides a number of educational benefits to online students. The foremost of these benefits is the fact that the factor of a geographical distance has absolutely no effect on online learners’ ability to successfully cope with academic assignments.
  4. The fact that the paradigm of distance learning is being inconsistent with the methodology of ‘group learning’ – Unlike what it is being the case with students in conventional classrooms; online students are being deprived of an opportunity to indulge in a group-based studying. The foremost detrimental effect, caused by this situation, is the fact that online students cannot measure the subtleties of their academic progress against the academic progress of their virtual classmates. Moreover, because of that, online students are also being unable to partake in so-called ‘brain storming’ group-sessions, which became an integral part of today’s educational curriculum in Western academia.

Thus, the very concept of distance learning establishes a number of objective preconditions for the population of online students to feature a number of distinctive characteristics. One of these characteristics is the fact that, on average, a good share of online students consist of already well-established individuals, who seek to attain an additional academic degree, “With the on line student population often being traditionally older with more ‘complex’ lives involving children, older relatives, spouses, careers and financial commitments it may be that external factors …has particular relevance for students” (Perry, et. al., 2008, 10).

These students, in most cases are hypothesized as perusing a degree for the purposes of career advancement. Therefore one reason being considered for a higher attrition rate would be the type of degree the student is seeking may not be contusive with their ultimate career aspirations. “Another common reason for students in the study to leave the program related to changes in their career paths, making their current course content not useful” (Ibid., 11). Students who pursue degrees, albeit online or in traditional classroom settings, will usually take several years while they continue to be employed. This factor alone may annul a student’s desire to attain the original degree they entered the program to obtain. Students in a career, over a period of time may change their career and/or responsibilities, or be offered new opportunities in other unrelated careers.

When explaining higher dropout rates of online students, Diaz (2002) points to, we as researchers, may have “mistakenly defined ‘drop rate’ as a characteristic synonymous with ‘academic success’(3). He theorizes that “because of the requirement of school, work, and/or family life in general, students may benefit more from a class if they take it when they have enough time to apply themselves to the classwork” (Ibid.4). His theory concurs with the student’s ability to withdrawal from a particular class if they are not meeting the appropriate grade progress at the time, and subsequently later ensuring a more successful academic career by not negatively impacting their grade point average or academic and financial aid eligibility (Ibid., 5). “When a voluntary decision is being made to persist or dropout, it is made by the individual student, influenced by his own personal circumstances. It is based on the student’s continual cost/benefit analysis of all social, organizational, economical and psychological factors like those resulting from perceived opportunity, relevancy, stress, responsibility and satisfaction within the educational context” (Berge & Yi-Ping, 2004, 14). Another distinctive characteristic of online students is the fact that many of them tend to apply a pragmatic/result-oriented approach to addressing educational challenges. The validity of this suggestion appears especially evident in regards to adult learners, who seek to improve the level of their professional qualification. Unlike what it is being usually the case with the majority of conventional students, adult learners that pursue web-based degree tend to ‘filter out’ the course-related educational information, to which they are being exposed while on the course. In its turn, this can be explained by these individuals’ endowment with analytical-mindedness – unlike students that enroll into colleges and universities after having attained their high school diplomas, adult online students are capable of distinguishing between relevant and irrelevant types knowledge, they are expected to obtain while pursuing web-based degrees. This is the reason why there are no good reasons to believe that online students, which already hold college or university diplomas, are likely to think of the newly obtained knowledge via the medium of Internet as such that represents an undeniable truth-value. This is being especially the case when online students do not perceive a web-based knowledge as such that constitutes any practical worth, or as such, that is being inconsistent with their prior life-experiences (Deggs & Miller, 2011). Within our study’s context, the earlier suggestion is being especially relevant as it provides us with insight into the fact that the spatial subtleties of a high attrition among online students may in fact be ambivalent. That is, there is always a possibility for what appear to be non-academic reasons, behind online students’ attrition, to be of essentially academic nature, and vice versa. Nevertheless, it is always the decision of the student whether to graduate, or drop out from an online program. As it was noted by Houle (1961), “Efforts to explore the reasons why some people become continuing learners has made it clear that there is no simple answer to this complex question. Each person is unique and his [or her] actions spring from a highly individualized and complex interaction of personal and social factors” (80). Even though that, as it was pointed out earlier, the very concept of e-learning establishes a number of objective preconditions for online students to consider dropping out with much greater ease, as compared to what it is being the case with conventional students, the factor of personal predisposition towards studying still appears to play a crucial role in this respect.


The goal of this case study is to provide an analysis of student reported reasons for attrition specific conflicts these students faced when determining to continue or leave this specific program. The student’s reasoning cannot be altered, and these reasons may be addressed through further development student support systems. The methodology section will describe the mythology to be used in this study. We believe that the empirical data, which will be obtained during the course of conducting this study, would substantiate the legitimacy of the earlier articulated preliminary insights as to what may be considered the de facto prerequisites for distant/online learning to continue being strongly associated with the high attrition rate among students.


Qualitative/Quantitative research

According to May (2002) the utilization of a qualitative research survey is being particularly justified in studies concerned with defining motivational factors behind people’s behavior and with analyzing these factors’ spatial subtleties. Partially, this can be explained by the fact that, even though the relevant data, obtained during the course of conducting qualitative research, cannot be easily quantified, the possession of this data nevertheless often proves crucial within the context of researchers making analytical inquiries as to the actual nature of a researched phenomena. Apparently, there are good reasons to think of the deployment of a qualitative research methodology, as being especially suitable within the context of conducting studies where the exploration of a significance of subject-related psychological aspects constitutes an important element of a research-process. As it was pointed out by Rubin and Rubin (1995), “Qualitative research methods emphasize the depth of understanding associated with idiographic concerns. They attempt to tap the deeper meanings of particular human experiences and are intended to generate theoretically richer observations that are not easily reduced to numbers” (25). Hence, qualitative research’s key features:

  • This type of research always stresses out the importance of assessing the studied phenomena through the eyes of those affected by this phenomena the most.
  • The methodology of a qualitative research allows researchers to identify the full scope of social circumstances, which affect the spatial emanations of a studied subject matter.
  • The utilization of a qualitative research’s methodology, within the context of researchers striving to gain a three-dimensional insight into the actual essence of an investigated phenomena, allows them to determine phenomena’s discursive subtleties.
  • Qualitative research allows the examination of social interactions, which determine the actual quality of their ‘end-products’. This, of course, ensures the academic validity of a concerned hypothesis under investigation.
  • The methodology of a qualitative research allows researchers to adopt an intellectually flexible approach towards conducting a social inquiry, which in turn allows them to modify the research-procedures as they see fit.

The earlier outlined features of a qualitative research are being suggestive of what may be considered such a research’s main advantages. These advantages can be listed as follows:

  • Methodological simplicity – qualitative research is being often concerned with reviewing easily accessible academic literature.
  • Cost-effectiveness.
  • A wide range of its implicational appropriateness – the deployment of a qualitative research methodology has proven its effectiveness within the methodological framework of both: social and natural sciences.

Nevertheless, there are also a number of drawbacks to this research-method. The main of these drawbacks is the fact that very often, the data obtained during the course of conducting qualitative research, can be interpreted from a variety of different perspectives. However, as of today, the qualitative research methodology continues to be extensively resorted to as an effective and valuable research-tool.

This study utilizes the distribution of survey-questionnaires, as an instrument for collecting responses from sampled respondents and analyzing these responses’ qualitative implications. Nevertheless, in order for us to be able to gain a three-dimensional insight into the factual significance of the collected data, concerned with determining the essence of non-academic motivational factors behind online students’ heightened likelihood to drop out, we will also need to supplement the deployment of a qualitative research-methodology with the deployment of quantitative research-methodology.

The main objective of a quantitative research is to quantify the implications of empirical data, collected during the course of study’s qualitative phase, by the mean of analyzing data’s significance within the framework of a certain mathematical or algorithmic framework (Franses & Paap, 2001). The foremost advantage of this particular research-method is the fact that, while being exposed to the quantified data, in regards to spatially transforming essence of a studied phenomenon, researchers are able to define the direction of such transformation’s vector. In this study, we will rely upon the utilization of quantitative research, as an instrument of obtaining study-related qualitative insights, when it will come to analyzing spatial implications of obtained responses to the questions contained in survey-questionnaires.

The foremost consideration behind our decision to utilize quantitative research methodology was the fact that the deployment of this particular methodology allows the establishment of dialectical links between empirical observations and the mathematical expressions of these observations’ discursive significance. In other words – the utilization of quantitative research in our study will aim to confirm the validity of previously obtained insights, as to the probable non-academic causes of online students’ attrition. The full appropriateness of a proposed approach to tacking this study’s subject matter can be further illustrated in regards to the fact that, despite the seeming incompatibility between theoretical premises behind qualitative and quantitative research-methodologies, these methodologies’ procedural adjunction often proves rather indispensible, “Indeed, qualitative and quantitative methods may be used in combination in single studies if this is adjudged to be an appropriate means of researching a given problem. Thus, in this position, emphasis is placed on the practical rather than the philosophical aspects of social inquiry” (Heaton, 2004, 56). Given the essence of this study’s research-subject, there are a number of reasons to expect the deployment of a proposed research-methodology to prove thoroughly effective.

The rationale for this research design is to provide insight into the method used for refining a theoretical explanation that makes the theory more general and applicable across a wide spectrum based on Creswell’s (2002) definition. The methodology discussed in this section will further explain how the theoretical hypothesis will be proven. This theory is that reasons students leave online programs because of more non–academic reasons then academic. These reasons are based on the facts that these students encounter conflicts that they choose to avoid than resolve, thus departing from online programs and consequently projecting an artificial negative attrition rate, that is often associated with pessimistic views of online learning. The earlier conducted review of the relevant literature is being suggestive of the fact that the bulk of non-academic reasons, behind online students’ attrition, may account for the specifics of these students’ mental predisposition affecting their attitude towards learning. In its turn, this explains the phenomenon of students adopting often opposite approaches towards addressing web-based academic assignments, even when their decision-making in this respect, appears being influenced by essentially the same set of circumstances.

The theory that I, have deliberated in this project is the proposal that online students are more likely to withdraw from online courses when they encounter non-academic conflicts that may deter degree completion, instead of managing through the conflict. The goal of this research is to identify what these conflicts are by surveying current professors in an online course taught extensively to new students who are, in most cases experiencing the on line environment for the first time. The focus of this research is to gain a perspective from a group of faculty, both fulltime and adjunct, who teach the same entry level course to determine what, if any, non-academic conflict they perceive their students encounter that could influence them to leave this online based program. The reason why this study will focus on analyzing questionnaire-based responses from teachers is that, unlike what it is being usually the case with online students, teachers are assumed to possess a spatial insight on what may account for the contributive factors behind online attrition. This is because, while on the line of executing their professional duties, educators are being often able to define the qualitative nature of educational behavior, on the part of different categories of students.

Purpose of Research

The resolve of this research is to assess the conflicts new students to the online format encounter when undertaking online programs. The objective is to examine their potential hindrances to continue and complete their goal, and gain an understanding of why they may choose to leave these types of programs, regardless of the study duration. To gain an understanding into these events, a survey will be developed and sent to professors, both full time and adjunct of a specific online course. By asking designed questions to instructors, about their class and experiences with their current and past online classes, a theoretical affirmation can be drawn as to what conflict these students encounter that may influence the decision to avoid the conflict rather than work through it and complete the prerequisite course.

The online director may wish to review both aspects of the data; therefore the researcher will offer the results back to the director for their individual dissemination of the results both on an overall and individual case study. This qualitative research will draw on Allen (2003) and Willging’s (2008) views to understand the requirements that work for online students as the study focus. According to Berg (2007), a qualitative research survey is an instrument that establishes an individual in an environment by identifying factors that influence the outcome from online students leaving their programs known to the observer, a fact concurred by Yin (Yin, 2009).

Yin (2009) adds another dimension to qualitative research to be interpretive in crystallizing a meaning. On the other hand, quantitative research assigns numerical values to observations on a given scale. An appropriate method for conducting this study, according to the National Center for Educational Statistics (2010), will use closed ended questions rating systems and “best fit” answers in the survey of questionnaires administered to online professors (McLaughlin, 1998). The questions will be designed in a manner to be perceived by the selected respondents as being ideologically-neutral. At the same time, however, survey’s questions will be formulated in a way to ensure a discursive relevance of the expected responses.

Once the instrument is established, I as the primary researcher will be sending the instrument (via website) to online, professors, who teach the same course in a specific university to the same demographical student base at different times of the year round academic calendar. This University, which has been identified by the regional accreditation body, the Southern Association of Colleges and Schools (SACS); employs these professors on a part time as well as full time basis. They will be the intended subjects of this survey. The data will be collected using a third party website. This information regarding this accreditation of this University is readily available from the SACS website, complete with the approximately eight hundred (800) universities that offer online programs, their directors, and their subsequent electronic mail addresses. The goal is to collect the data from the facilitators of this online course of generalizations of students enrolled in a degree seeking program during a current, or recently past (within one year) online semester. The data will be collected, focusing on the questions pertaining to the difficulties (conflicts) these professors’ students have experienced, over the course of their entry level online experiences. We expect that the obtained responses will shed light onto the qualitative nature of education-hampering conflicts, experienced by online students during the course of studying. We also expect them to provide a scientific legitimization to this study’s initial hypothesis as to the fact that the acuteness of non-academic motivations behind online students’ high attrition should be reflective of the particulars of these students’ ethno-cultural affiliation and of the qualitative essence of their mental predispositions.

An in depth analysis of the data collected will be organized and established patterns will be validated to further explain reasons deterring a particular population (new online students) from pursuing their degree programs in an online setting, a concept borrowed from Bailey’s (2002) studies. The survey will be designed to elicit confidential responses from these professors and will ensure their privacy by directing them to an outside, internet web based survey, where they will be able to respond freely and in confidence. The fact that, in this study we have made a point in ensuring the full confidentiality of an empirically obtained data, is being thoroughly consistent with the provisions of Family Educational Rights and Privacy Act (FERPA), “FERPA directs schools and higher education institutions to protect the rights of parents and students (age 18 or entering college) to inspect and review education records, to seek to amend education records, and to consent to disclosure of personally identifiable information from education records” (Hilton, 2008, 8). This, however, will not undermine the implicational soundness of an obtained data, because the extensive effort will be applied into ensuring data’s representational legitimacy.

This research will explore the phenomena that a group of students, defined as, “new” online students, who entered a program of post high school education, have over a course of time (the classroom experience) dwindled away to a minimal number who are continuing degree completion (Neale, 2006). It is my theoretical contention to further explain some of the reasons this departure exists by identifying nonacademic conflict these students may encounter that could incite the exodus of this identified group of students. Thus, measuring the effectiveness of online education by determining the non-academic conflicts this unique group (online students) and how these potential conflicts can deter degree completion in this non-traditional classroom setting.

Research Design

The methodology design for this study will be two parts. The case study methodology will be the primary method used to correlate the data collected to the aforementioned theory that outside conflicts are more likely to influence students to withdraw from online programs than internal conflicts, such as academic reasons. This research is reliant toward results of a survey designed and conducted by this researcher. I am confident that the postulation that online student would rather leave their intended goals rather than managing the conflict they face; can be identified by the instructors who understand the students and are subject to experiencing these occurrences within their courses taught. Further, when describing these circumstances, the professor can confirm the theory without violating any confidentially issue by not identifying students specifically, but give generalizations of reasons they encounter, or have encountered by personally experiencing these conditions.

The second instrument will be the survey. The results of the survey will be coded from forced answers by the respondents and then will be implied to show the results that correlate with the theory that external influences may persuade a student’s decision to discontinue their education in an exclusive online setting. The survey will be given to professors who teach the same entry level course on a rotating basis. These professors generally encounter up to twenty five (25) students per course at the beginning of a six week term. Generally, by the end of a course a significant number of students leave these courses. During the course of normal communication with the students, throughout the term, the professor will gain an understanding as to what conflicts a student may be encountering that could lead to their withdrawal of the course. The survey will inquire of the professors, as to some of the conflict these students are generally undergoing and correlate the attrition of this group of student with the conflict they are experiencing.

Appropriateness of Design

Creswell’s (2002) multipronged theoretical proposition provides a framework for inquiring into theoretical questions, issues, or problems associated with the decline in the number of students studying online. That is given further support based on the conflict theory I have pointed to, which explains why students may choose to leave university based on line programs (Bean, 1990). Yin (2003) borrows from Creswell’s (2002) theory and with further investigation finds a positive correlation of Creswell’s (2002) theory through a survey conducted by Neale et al, (2006) by relating several patterns to Creswell’s (2002) theoretical proposition using a pattern matching technique. I believe that this particular proposition does provide a procedural guidance as to how the researched subject matter should be handled. This is because Creswell’s proposition is being fully correlative with the foremost principles of a qualitative research, such as systemness (researchers are prompted to adopt a thoroughly systematic approach to assessing the significance of a studied phenomenon), reflectiveness (researchers are supposed to remain observant of the full scope of a studied phenomenon’s manifestations) and analyticalness (researchers are encouraged to apply an interdisciplinary approach, when evaluating the phenomenon’s social implications). Given the fact that, as it was hypothesized earlier, there are good reasons to think of a high attrition among online students as such that is being predetermined by essentially non-academic reasons, it represents a matter of crucial importance for those that tackle the issue of many online students’ reduced ability to persist with studying, to be able to distinguish between proper non-academic attrition-inducing triggers and seemingly non-academic attrition-inducing triggers. Therefore, the proposed methodological approach can be best described as thoroughly appropriate, as its provisions establish objective stimulants for the research to proceed in a full accordance with the very theoretical premise of a qualitative inquiry.

Research Questions

This study is to determine patterns that reflect the many variables that influence the new student’s decision to leave online courses. The primary goal of this research is to identify the non-academic reasons these students would rather quit than to work through these identified shortcomings. The primary research questions this study is designed to address are: What reasons do new students fail to persist in online education? Do more students leave for non-academic reasons then academic inadequacies? What is the effect of currently deployed learning strategies in the web-based educational environment on students’ varying likelihood to drop out? What is the qualitative essence of a relationship between the subtleties of online students’ psycho-type and the strength of their commitment towards studying? How do the specifics of students’ socio-economic and ethno-cultural affiliation affect their decision-making on whether to drop out or to persist with studying?

Secondary research questions are: What are these conflicts that students experience that deter them from completing online programs? How can instructors facilitate factors or barriers that deter the students from withdrawing from online course? What support systems can online instructors incorporate to deter these students from withdrawing from online course? How do negative factors relate to a student’s critical decision to withdraw from online courses?


The subjects have been identified as teaching on the SACS level one I and II category, to new (fewer than 12 semester hours) online students, who enrolled in a program with the aspirations of completing a degree as prescribed on the university’s timeline. According to Palys (n.d), the researcher will have to identify respondents based on the purpose of the study. The participants will be asked to partake in a brief non compensated, confidential internet based survey designed to solicit answers about their academic online experience and personal situations likely to cause them to recall the process. The instrument will be designed to gain specific information regarding the conflicts these professor’s students may face based on a framework that draws on the decision making theory. This may explain why these students decided it to be in their best interest to forego their desired outcome of the experience of completing an online degree. The instrument in form of a questionnaire will be sent by email to the online fulltime and adjunct faculty of the identified course. Along with being asked to answer the provided questions, the participants will also be asked to reflect on what they think may account for the most effective method of reducing the attrition rate among online students.

In order to encourage these professors to participate in this process, the anonymous results will be accessible to these directors of this course to gauge their student’s perceived overall satisfaction, success and potential concerns that their students may be encountering in order to understand their own programs in greater depth and detail.


The population ultimately being studied are the students of professors who participated in the on line experience. By surveying the people (instructors) who have the most, direct contact with these students, the goal is to identify the reasons these students leave (drop out) of online classes. The rationale for surveying the professors, is to understand this phenomena from the perspective of the teacher, who has the maximum contact with the student through the process of initial experience up to the time when then they (the student) leave the class. The instructor would have the most accurate information as to the conflict the student is experiencing albeit academic, or in this case, non-academic conflicts that influence the students decision to leave the course. The validity of collecting professors’ responses can be explored even further in regards to the fact that, unlike what it is being the case with online students; they cannot be personally affected by what may account for the practical implications of the collected data. There is also a practically validating aspect to the proposed research-methodology – the fact that online instructors are assumed to have an interest in increasing students’ retention rate, as the ultimate mean of advancing their professional careers. This will serve as an additional guarantee that the collected information will be as much value-free as possible. This, however, does not mean that we will adopt a thoroughly uncritical approach towards analyzing the obtained responses. After all, there are no objective reasons to consider teachers’ views on attrition-contributing factors in the web-based academic curriculum as being unbiased, by definition. As it was noted by Powell and Keen (2006), “Distance educators, almost exclusively educated in conventional educational systems and successful through them, are prone to invoke their own, romanticized, educational experience as a template for higher education in general. They tend to see distance education as successful to the extent to which it is as good as their own” (287). Therefore, before being subjected to quantification, instructors’ answers to the provided questions will be thoroughly scrutinized on the subject of whether they can be considered thoroughly unbiased.

Based on Palys’s (n.d) perspectives on purposive sampling, current facilitators participating in online learning from an identified university within the SACS (Southern Association of Colleges and Schools) will be the proposed respondents. The Southern Association of Colleges and Schools is responsible for over eight hundred (800) colleges and universities in eleven states. SACS is responsible for accrediting universities and colleges in the region that consist of the states of: Alabama, Georgia, Florida, North Carolina, Kentucky, Louisiana, Mississippi, South Carolina, Tennessee, Texas and Virginia. These are defined by SACS as, Level I –Associate Degree, Level II- Baccalaureate, Level III -Master’s Degree, Level IV – Master’s Degree and Education Specialist Degree, Level V – 3 or fewer Doctoral Degrees, Level VI – 4 or more Doctoral Degrees.

Informed Consent and Confidentiality

The participants will be assured that their participation will be voluntary and confidential, and in no way will their identity be compromised and no personal information, nor the personal information of any specific student will be included in the research, research instrument, or shared with any third party. This will be done by providing a confidential page to acknowledge and an informed consent imbedded in the web based instrument to inspire confidence in the participants. That will further assure the participants that they will not be susceptible to risks of exposure of the information they give and that they will be informed of the results of the study. The consideration of ensuring respondents’ anonymity is not being solely concerned with the observation of FERPA’s provisions but also with eliminating the factor of ‘conflict of interests’ out of this study’s procedural framework. While being provided with a guarantee that their identity would not be exposed to the affiliated and non-affiliated members of an academic community, the respondents will be more likely to offer expanded reflections on how their students’ existential modes affect their chances to obtain web-based degrees.

The survey will be hosted by an independent internet website, devoid of University affiliation. A brief purpose statement, describing the research and the goals obtained will preface the confidentially agreement in the survey. Once delivered to the instructor, they will have the option of participating voluntarily, or declining to participate.

Data Collection


The instrument will identify student’s potential conflicts that could ultimately lead to withdraw from online programs. Neale et al, (2006) takes the study a notch higher by stating that a survey is appropriate methodology, “when there is a unique story to be told, offering a more complete picture of what happened in the program and why” (4). The full appropriateness of a survey, as the method of collecting empirical data, relevant to this study’s subject matter, can be illustrated in regards to this method’s qualitative characteristics, listed as follows:

  1.  Survey provides a cross-sectional representation of studied populations, which in turn ensures the adequate extent of an obtained data’s academic applicability. This is why, the insights, gained by the mean of analyzing the significance of survey’s empirically obtained data, often serve as the basis for designing a wide array of educational policies.
  2. Survey ensures the elimination of incidental factors that may affect the legitimacy of a particular study’s hypothesis. In its turn, this can be explained by the fact that, for as long as survey’s quantified data is being deemed truly representational, there is always a possibility to define a central tendency about how this data exposes the spatial dimensions of a studied phenomenon.
  3. Survey’s data can hardly become a subject of manipulative interpretation, especially after being quantified. This is despite the fact that the method of survey is being commonly deployed in studies that tackle highly interpretative/controversial subject matters. The following is the example of a survey-based question:

In your opinion rank what would you feel is the most significant non- academic reason your students withdraw from your course to the least significant?

  1. Underestimated Time Requirements for online Curses.
  2. Personal Reasons (Family/ Job Commitments take precedent).
  3. Isolation/ Self Directed Work.
  4. Lack of Motivation.

In addition, the survey will also include questions about situations that may hinder their online experiences, thus producing the factors that are principal in this research.

An example of this type of question would be:

Do you feel most of your students are adequately prepared to begin online courses?

  1. Most
  2. Some
  3. Few
  4. None

If there are any suggestions you could make in student retention? What could be done to make improvements? Please rank the following in order you feel they would be most effective to least.

  1. Conduct exit interviews with students who withdraw to find out specific reason why this occurred.
  2. Remediation
  3. Earlier and more aggressive interventions to retain the student
  4. Give student more details and schedule of what are the expectations of their time


The data collected will be from this group of educators, defined as primarily teaching enrolled, current or recent (within one year) students admitted to accredited online, specific course. The criteria expectation is they are teaching students who are admitted to a University for the purpose of degree completion. Historically, the new student population has been observed to have a considerable dropout rate-define compared- from the time of registration to the end of online class completion (6 weeks).

The purpose of this sample is to examine a collective group of instructors who started work exclusively with students taking a course in an online program and to further explore the student’s perceived decline and the specific factors (conflict) that may influences their decisions to withdrawal rather than continue through the conflict. Ancillary concerns are based on a participant rate of a minimum of 33%, from this type of a response, there is a high confidence that a valid sample can be disseminated and applied to this research.


Participants in this study may live in various geographic areas of the United States, but are employed by the University in the SACS region. This effort will be facilitated by contacting the online director at this University via electronic mail and personal visit. Surveys will be administered through a third party web based platform ( ) to ensure standard application. Through the primary instructor, these online learners are the focus of this study (Nettles & Millett, 2006). The purpose of using this type of tool is to ensure the instructors’ and the students’ confidentiality, by using a non-university based internet survey, insuring the potential participants that the survey is from an outside source may lead to more confident participation. This type of instrument is also available to researchers to compile data and code this data by the parameters set forth when designing the survey. Thus giving a valid and comprehensive result based report to the researcher.

After initial contact, a time sensitive window for data collection will be used. Once participants reply to the instrument, data collected will be reviewed for patterns that are consistent to the types of conflicts that the participant’s students encounter that may influence the critical decision possibly leave the online programs for non-academic reasons. This information will be coded into categories for data transposition.

Creation of codes will be consistent with inclinations and discontent encountered while the students have participated in these online classes. This research will focus on the factors that are relative with nonacademic, life changing events, or general dissatisfaction that could perpetuate a decision to leave a program and will be correlated with decision making theories. Moreover, a particular effort will be applied in evaluating non-academic factors from a psychoanalytical perspective. This will ensure the analytical sounding of a discussion of why online students’ high attrition appears being dialectically predetermined. Coding this quantitative data will be necessary to convert the responses into unique descriptions to correlate the decision making theory to conflict theory criteria and thus authenticating the data collected.

The time line for this data is historical, so no future (anticipated drop out) rates will be considered. A data base management system (DBMS) using Statistical Package for Social Sciences (SPSS) will be used to organize the data collected using a coding system. The technique provides the mechanism for organization of data in logical structures, thereby allowing sharing of data for multiple applications (Talhouni, 1990). Following this, appropriate stored data were inputted into the input interfaces of the relevant tools used in the study. The processed data were retrieved from the output interface of the tools used accordingly.

Role of Researcher

The researcher will independently collect data by examining the defined professor’s attitudes, experiences and perceptions of students enrolled an in online course. The foremost purpose of this examination will be concerned with: outlining qualitative patterns in how study’s participants reflect upon the investigated subject matter, defining these patterns’ discursive significance, reducing the factor of uncertainty in the full scope of an analyzed data’s educational implications, and justifying the proposed methodological approaches for future investigations of a researched subject matter. The research will collect data using rigorous data collection instruments and other relevant information by conducting qualitative researches including literature reviews, examining documents, and participating in the administration of the survey instrument. In addition, the researcher will also play the role of reviewing and organizing collected data and other information in a form to be analyzed. The academic legitimacy of a proposed approach towards data-collecting will be ensured even further by the mean of subjecting the process of collecting data to periodic evaluations on the subject of whether this process proceeds in a full accordance with the foremost principles of a qualitative research, outlined earlier. The researcher will also identify research variables, assign numerical values to the variables, frame the data, and provide adequate details about the data.


In order to test the hypothesis of this research, that online students are more likely to withdraw from online classes when they encounter nonacademic conflicts that may deter degree completion, instead of managing through the conflict. The research will be collected from voluntarily participants (Instructors) who are, or have recently taught an entry level course at an acknowledged SACS accredited university to students for the purpose of degree completion. A survey will be the primary instrument used to identify what these conflicts are. By surveying these professors of new students to determine what, if any, nonacademic conflict they may encounter that could influence them to leave these on line based programs, the information gathered by this survey will then be the determining factor to support the hypothesis or the null hypothesis. This conclusion will be drawn from these coded survey responses to identify such factors that could support the hypothesis by drawing a logical conclusion. We expect the collected empirical data to support the validity of this study’s initial hypothesis as to the fact that the high rate of attrition among online students must be of essentially non-academic essence. We also expect to obtain evidence as to the fact that that the attrition-inducing factors may account for the following:

  • Online students’ poor skills in planning their daily, weekly and monthly schedules, which incorporate the pursuance of web-based degrees, as their integral element.
  • Online students’ psychological incompatibility with the procedural matrix of a particular e-learning strategy, to which they are being exposed while pursuing web-based degrees.
  • Online students’ inability to manage domestic/professional conflicts, which in turn derive out of these students’ lessened ability to combine qualitatively different existential pursuits within the behavioral framework of their lifestyle.
  • The factor of online students’ emotional uncomfortableness with the software-based e-learning applications.
  • Online students’ media-induced negative attitude towards e-learning as such that is only being capable of providing them with formally legitimate but practically devalued academic diplomas.

If proven legitimate, this study’s thesis will have the following implications:

  • The admission-criteria of a web-based learning should not be solely concerned with testing the extent of applicants’ overall academic adequacy, but also with testing the extent of their psychological compatibility with the medium of an online education.
  • Educators that specialize in providing web-based educational services must apply an additional effort into facilitating the strength of online students’ emotional attachment to a particular web-based academic course that they are taking.
  • Online educators must encourage their students to explore the full extent of an obtained knowledge’s practical relevancy.
  • Prior to enrolling in a particular web-based academic course, online students must be required to provide a monetary security deposit, which will be withheld, in case they decide to drop out.

Given the fact that, when compared to the recommendations of how the online students’ retention rate can be increased, available in the earlier reviewed relevant studies, our recommendations appear rather innovative, there would be a number of good reasons to consider this study as such that is being potentially capable of representing a legitimate academic value.


Adams, G. (1997). Racism, community, and democracy: The ethics of affirmative action. Public Productivity & Management Review, 20 (3), 243-255.

Allen, I. J. (2003). Sizing the Opportunity: the Quality and Extent of Online Education in the United States, 2002 and 2003. Needham, MA: Sloan.

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

Bandura, A. (1995). Self-efficacy in changing societies. Cambridge: Cambridge University Press.

Bean, J. (1982). Student attrition, intentions, and confidence: Interaction effects in a Path Model. Research in Higher Education, 17 (4), 291-320.

Bean, J. (1990). Why students leave: Insights from research. In J. B. D. Hossler, The Strategic Management of College Enrollment (pp. 170-185). San Francisco: Jossey-Bass.

Belton, V. & Scott, J. (1998). Independent learning and operational research in the classroom. The Journal of the Operational Research Society, 49 (9), 899-910.

Berg, B. L. (2007). Qualitative Research Methods for The Social Sciences (6th ed.). Boston: Pearson.

Berg, Z. &.-P. (2004). A model for Sustainable Student Retention: A Holistic Perspective on the Student Dropout Problem with Special Attention to e-Learning. DEOSNEWS, pp. 3-33.

Bernard, R. et al. (2004). How does distance education compare with classroom Instruction? A meta-analysis of the empirical literature. Review of Educational Research, 74 (3), 379-439.

Blakey, L. (2010). The proliferation, pitfalls, and power of online education. In K. Klinger (Ed.), Web Based Education (pp. 29-51). New York: Information Science Reference.

Brookfield, S. (2005). The power of critical theory: Liberating adult learning and teaching. San Francisco: Jossey-Bass.

Brown, K. (1996). The role of Internal and external factors in the discontinuation of off-campus students. Distance Education, 17(1), 44-71.

Bruner, J. (1974). Toward a theory of instruction. Cambridge, MA: Harvard University Press.

Bush, R. &. (2005). The Promise of Mediation, The Transformative Approach to Conflict. San Francisco: J.P. Wiley & Sons.

Carr, S., As distance education comes of age, the challenge is keeping students: Colleges are using online courses to raise enrollment, but retaining it is another matter. The Chronicles of Higher Education. Web.

Clark-Ibanez, M. & Scott, L. (2007). Learning to teach online. Teaching Sociology, 36 (1), 34-41.

Creswell, J. (2002). Qualitative Inquiry and Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. Upper Saddle River, NJ: Merrill Prentice Hall.

Cross, K.P. (1981). Adults as learners: Increasing participation and facilitating learning. San Francisco: Jossey-Bass.

Deggs, D. & Miller, M. (2011). Developing community expectations: The critical role of adult educators. Adult Learning, 22 (3), 25-30.

Diaz, D. &. (2006). Term Length as an indicator of Attrition in Online Learning. Innovate, 2-7.

Diaz, D. P. (2002). Online Drop Rates Revisited. The Technology Source Archives at the University of North Carolina, 1-7.

Erichsen, E. & Bolliger, D. (2011). Towards understanding international graduate student isolation in traditional and online environments. Educational Technology Research & Development, 59 (3), 309-326.

Fox, F. (1976). The recolored mentality-ethical lessons from science. Science Teacher, 43 (6), pp. 22-24.

Frankola, K. (2001). Why online learners dropout. Workforce, 53-63.

Franses, P. & Paap, R. (2001). Quantitative models in marketing research. Cambridge: Cambridge University Press.

Graff, M. (2003). Learning from Web-based instructional systems and cognitive style. British Journal of Educational Technology, 34(4), 407-418.

Greenwood, S. (2009). Anthropology of magic. Oxford: Berg Publishers, 2009.

Guri-Rosenblit, S. (1999). Distance and Campus Universities: Tensions and Interactions. A comparative study of five countries. Amsterdam, Netherlands: IUA Press Pergamon.

Hagen, F. E. (2002). Research Methods in Criminal Justice and Criminology. Boston: Allyn and Bacon.

Halx, M. (2010). Re-conceptualizing college and university teaching through the lens of adult education: regarding undergraduates as adults. Teaching in Higher Education, 15 (5), 519-530.

Heaton, J. (2004). Reworking qualitative data. London: SAGE Publications Inc.

Herbert, M. (2006). Staying the Course: A Study in Online Student satisfaction and Retention. Online Journal of distance Learning Administration, Volume IX, 1-23.

Hess, F. M. (2009). Diplomas and Dropouts: Which Colleges Actually Graduate Their Students (and Which Don’t). Washington DC: American Enterprise Institute.

Hicks, D. (1996). Contextual inquiries: A discourse-oriented study of classroom learning. In D. Hicks (Ed.), Discourse, learning, and schooling (pp. 104-141). New York: Cambridge University Press.

Hilton, M. (2008). Protecting student records and facilitating education research: A workshop summary. Washington: National Academies Press.

Hiltz, S. R. (1997). Impacts of college-level courses via asynchronous learning networks: Some preliminary results. Journal of Asynchronous Learning Networks, 1-19.

Hoag, C. (2006). The Atlantic telegraph cable and capital market information flows. The Journal of Economic History, 66 (2), 342-353.

Hofstede, G. (1980). Culture’s consequences: International differences in work-related values. Beverly Hills: Sage.

Houle, C. (1961). The inquiring mind: A study of the adult learner who continues to participate to learn. Madison, WI: University of Wisconsin Press.

Johnson, E. & Pitcock, J. (2010). Preparing online instructors: Beyond using the technology. In K. Klinger (Ed.), Web Based Education (pp. 277-292). New York: Information Science Reference.

Jones, M. & Harmon, S. (2010). Instructional strategies for teaching in synchronous online learning environments (SOLE). In K. Klinger (Ed.), Web Based Education (pp. 103-118). New York: Information Science Reference.

Jung, C. (1971). Psychology types. Princeton: Princeton University Press.

Kember, D. (1989). A longitudinal-process model of drop-out from distance education. The Journal of Higher Education, 60 (3), 278-301.

Klaus, T. & Changchit, C. (2010). Online or traditional: A study to examine course characteristics contributing to students’ preference for classroom settings. In K. Klinger (Ed.), Web Based Education (pp. 73-83). New York: Information Science Reference.

Kolb, D. (1984). Experiential learning: Experience as the source of Learning and development. Englewood Cliffs: Prentice-Hall, Inc.

Linton, R. (1999). Cultural background of personality. Florence: Routledge.

Lytras, M. & Pouloudi, N. (2001). Expanding e-learning effectiveness: The shift from content orientation to knowledge management utilization. In C. Montgomerie & J. Viteli (Eds.), Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2001 (pp. 1184-1190). Chesapeake, VA: AACE.

Mamchur, C. (1981). Determining cognitive style by systematic observation. Canadian Journal of Education / Revue Canadienne de l’Education, 6 (4), 92-104.

Marks, R., Sibley J. & Arbaugh B. (2005). A structural equation model of predictors for effective online learning. Journal of Management Education, 29 (4), 531-563.

Maslow, A. (1968). Toward a psychology of being (2nd ed.). Princeton, NJ: Van Nostrand.

Maslow, A. (1970). Motivation and personality. New York: Harper and Row.

May, G. & Short, D. (2003). Gardening in cyberspace: A metaphor to enhance online teaching and learning. Journal of Management Education, 27 (5), 673-693.

May, T. (2002). Qualitative research in action. London: SAGE Publications Inc.

McLaughlin, G. P. (1998). Changing Perspectives on Student Retention: A Role for Institutional Research. Research in Higher Education, 1-18.

McPherson, M. & Nunes, M. (2004). Developing innovation in online learning: An action research framework. New York: RoutledgeFalmer.

Misook, H. (2001). Communication privacy disclosure management: An empirical study of socialization support in a pseudo-online course. Journal of Interactive Online Learning, 10 (2), 76-95.

Mkabela, Q. (2005). Using Afrocentric method in researching indigenous African culture. Qualitative Report, 10(1), 178-189.

Molen, H. (2001). Virtual university? Educational environments of the future. London: Portland Press Ltd.

Myers, I. (1975). Manual: Myers-Briggs type indicator. Palo Alto: Consulting Psychologists Press.

Nair, S. (2010). Organizational behavior. Mumbai, IND: Global Media. National Center for Educational Statistics. (2010). Digest od Educational Statistics. Washington, DC: IES National Center for Educational Statistics.

Neale, P. T. (2006). Preparing A Case Study: A guide for Designing and Conducting a Case study for Evaluation Input. Watertown, MA: Pathfinder International.

Nettles, M. &. C. M. Millett. (2006). Three Magic Letters Getting to Ph.D. Baltimore: Johns Hopkins University Press.

Okwumabua, T., Walker, K. & Hu, X. (2011). An exploration of African American students’ attitudes toward online learning. Urban Education, 46 (2): 241-250.

Paas, F. et al. (2005). A motivational perspective on the relation between mental effort and performance: Optimizing learner involvement in instruction. Educational Technology Research and Development, 53 (3), 25-34.

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.

Parker, A. (2003). Identifying Predictors of Academic Persistence in Distance Learning. United States Distance Learning Association Journal, 1-9.

Perry, B. J. (2008). Why Do Students Withdraw from Online Graduate Nursing and Health Studies Education? The Journal of Educators Online, 1-18.

Pethokoukis, J. (2002). E-Learn and earn. U.S. News and World Report. Web.

Powell, R. & Keen, C. (2006). The axiomatic trap: Stultifying myths in distance education. Higher Education, 52 (2), 283-301.

Pritchard, M. & Wilson, G. (2003). Using emotional and social factors to predict student success. Journal of College Student Development, 44 (1), 18-28.

Ramsden, P. (1998). Learning to Lead in Higher Education. New York: Routledge.

Rankin, E. (1963). Heading test reliability and validity as a function of introversion-extraversion. Journal of Developmental Reading, 6 (1), 107-117.

Rovai, A. (2003). In search of higher persistence rates in distance education online programs. Internet and Higher Education, 6 (1), 1-16.

Rubin, H. & Rubin, R. (1995). Qualitative interviewing: The art of hearing data. Sage, Thousand Oaks.

Ryan, Y. (2002). Emerging indicators of success and failure in borderless higher edu­cation. London: The Observatory on Borderless Higher Education.

Schneider, S. & Clark, G. (1999). Technical communication on the web: A profile of learners and learning environments. Technical Communication Quarterly, 8 (1), 37-48.

Schuetze, H. & Slowey, M. (2002). Participation and exclusion: A comparative analysis of non-traditional students and lifelong learners in higher education. Higher Education, 44 (3/4), 309-327.

Scott, J. (1991). The campaign against political correctness: What’s really at stake? Change, 23 (6), 30-43.

Skinner, B. (1968). The technology of teaching. New York: Meredith.

Suprateek, S. & Nicholson, J. (2005). Exploring the myths about online education in information systems. Informing Science Journal, 8, 55-73.

Thomas, J. (2006). Teaching courses online: A review of the research. Review of Educational Research, 76 (1), 93-135.

Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent Review of Educational Research, 45 (1), 89-125.

Tinto, V. (1993). Leaving College: Rethinking the Causes and Cures of Student Attrition, 2nd Edition. Chicago: University of Chicago Press.

Verduin, J. & CIark, T. (1991). Distance education: The foundations of effective practice. San Francisco: Jossey-Bass.

Vygotsky, L. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.

Wan, N. & Howar, N. (2010). A progressive pedagogy for online learning with high-ability secondary school students: A case study. Gifted Child Quarterly, 54 (3), 239-251.

Watson, G. (1975). Free agency. The Journal of Philosophy, 72 (8), 205-220.

Willging, P. A. (2008). Factors That Influence Students’ Decision to Dropout of Online Courses. Journal of Asynchronous Learning Networks, 115-127.

Yin, R. (2003). Case Study Research (3rd ed.). Thousand Oaks, CA : Sage.

Yin, R. (2009). Case study Research: design and Methods (4th ed.). Thousand Oaks, CA: Sage.