Understanding e-dropout.

The purpose of this article was to investigate the factors that affect the dropout of adult learners in e-learning through an in-depth literature review on the dropout of adult learners in e-learning. Based on the variables identified from the literature review of dropout in e-learning area the five constructs were categorized: individual background, motivation, academic integration, social integration, and technological environment.

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Introduction: Knowledge-Based Economy and E-Learning

  Our society is continuously moving towards a knowledge-based economy--
  an economy in which the application of knowledge replaces capital, raw
  materials, and labor as the main means of production. The synergy of
  combining new information and communication technologies with human
  skills has dramatically altered job content and skills requirements at
  the workplace (The Canadian Vocational Association and UNEVOC-Canada,
  2002, [paragraph] 1).

The so-called information revolution triggered by advanced communication technologies such as the Internet has had a significant influence on our daily lives. The arenas of education and training are no exception. The rapid rate of change demands an ability to learn to adjust quickly and assimilate large amounts of conflicting information. In this environment, an ability to learn continuously is becoming imperative. The learning environment for today's learners is no longer set within the walls of a school, but rather is everywhere, especially the Web and email. These advanced information technologies allow learners to access a variety of learning activities beyond the limitations of time and place. Responding to the potential of anytime, anywhere learning, education and training stakeholders have made considerable technology investments in recent years (The Software & Information Industry Association [TSIIA], 2001). "Most now recognize the power of technology to transform learning into a more flexible, personalized and accountable endeavor required by today's knowledge-based economy" (TSIIA, 2001, [paragraph] 1). Whiteman (2001) asserts that today's workplace environment necessitates knowledgeable, flexible, efficient, and adaptable workers who are lifelong learners. He continues that "adult learners need to be updated on the latest changes in the structure of the business environment" (p. 1). E-learning has the potential to meet the demand of today's business environment for skilled workers who are lifelong learners. E-learning provides many potential benefits to both companies and workers (National Alliance of Business, 2000).

Although e-learning has some advantages as an efficient and effective learning delivery media, the big problem of e-learning is learner dropout. While e-learning seems to answer a lot of learners' needs, drop-out rates are higher than those for face-to-face course campus-based learning (Knowledgenet, 2001). Svetcov (2000) claims:

  It is generally agreed that attrition rates from online schools are
  higher than from traditional schools ... the online student dropout
  rate [is] around 35 percent, [which is] 15 percent higher than
  traditional schools.... The fact is, much of what passes for online
  education today would put most of us to sleep (p. 3).

More skeptically, Murphy (2001) argues that e-learning courses without face-to-face classroom training have low success rates--only about 10 percent of employees complete online-only courses. The "anytime, anywhere" nature of at-your-laptop learning all too easily becomes "no time, nowhere." The average dropout rate for online courses can run as high as 50 or 75 percent, depending on the source (Ganzel, 2000). Although many studies related to e-learning have been conducted in the field of adult education or human resource development (HRD), relatively little concern has been given to why adult learners dropout. In addition, there is not any research-based evidence about how and why the learners in e-learning programs drop out. This study will provide an understanding of the dropout phenomena by clarifying the dynamic process that results in the dropout of adult learners. We investigate the affecting factors through an in-depth literature review.

Studies of the Dropout of Adult Learners in E-Learning

Although many studies related to e-learning have been conducted in the field of adult education or HRD, relatively little attention has been paid to why adult learners drop out. There is no broad-based quantitative study pointing to evidence of a widespread dropout problem for online training in the corporate world (Zielinski, 2000). In addition, there is not any research-based evidence about how and why adult learners in e-learning programs drop out. Of those studies of dropout of adult learners in e-learning reviewed in this section, only a few provided a comprehensive, theoretically-based, and explanatory framework from which to analyze the problem of dropout. Opinion papers based on the authors' live instructing or managing experiences of e-learning are reviewed and are discussed here as well as several theory-based studies because of their relevance to the conceptual framework and findings of this research.

The Learning Technology Acceptance Study: "If We Build It, Will They Come?" (2001), by the American Society for Training & Development (ASTD) and The MASIE Center reveals the fact that dropout rates for online training are high when learners are put off by one or more of several factors. These factors include poor incentives to learn, lack of accountability for completing classes, problems with technology, and the inability of poorly designed courseware to hold a student's attention. Based on its own experience as an e-learning provider, Frontline Group (2001) also provides five reasons why adult learners drop out in e-learning programs: poor design, failure to understand the new medium, not considering a variety of learning styles, lack of supporting systems, and ignoring the self-selecting content needs of learners.

Based on studies conducted by e-learning providers and the opinions of e-learning experts, Frankola (2001b) argues that adult learners drop out in e-learning courses due to the following reasons: students don't have enough time, lack of management oversight, lack of motivation, problems with technology, lack of student support, individual learning preferences, poorly designed courses, and substandard/inexperienced instructors. Interestingly, NYUonline found that "e-learners who took only the asynchronous course were much less likely to complete it than e-learners who also participated in live sessions" (Frankola, 2001b, [paragraph] 20).

On the other hand, crucial interactivity with faculty and among other students can be important for the success of a course. Studies conducted by Sun Microsystems Inc. show that "only 25% of employees finish learning content that is strictly self-paced, but 75% finish when given similar assignments and access to tutors through email, phone or threaded discussions" (Frankola, 2001b, [paragraph] 18). Hossein Arsham, a Wright Distinguished Research Professor of Statistics and Management Science at the University of Baltimore, also points out that interactivity with students is a key factor in explaining students' retention, based on the experience of teaching two courses of the first all-online accredited Web MBA program (Elearningpost, 2001).

This fact is also supported by a study (Towles, Ellis & Spencer, 1993) conducted in the field of distance education. This study sought to evaluate the effect of faculty initiated contacts on students' persistence within a large video-based distance learning program, and showed that faculty-initiated efforts seem to have the greatest effect on improving course persistence among freshmen students. Vrasidas and McIsaac (1999) examined the nature of interaction in an online course from both teacher and student perspectives. They find that the structure of the course, class size, feedback, and prior experience with computer-mediated communication (CMC) all influenced interaction. In particular, findings showed that some elements of structure, such as required activities, led to more interaction, and students who were new to CMC were not comfortable participating in the online discussion. In addition, "when students do not receive feedback, they do not continue to post messages. Unless they receive feedback immediately, they feel they are posting to the network without any response" (Vrasidas & McIsaac, 1999).

According to Gilroy (2001), the CEO of the Otter Group, low enrollments and high attrition rates stem from user dissatisfaction and the cause of this problem is the separation of people in time and space; but it can be overcome by building environments where people talk to one another, build relationships, and teach one another. She continues, "While there is no simple answer, there is one key idea that has been overlooked in the design and implementation of many of the e-learning programs on the market today" ([paragraph] 3). That is, "learning is fundamentally both social and experiential. It is the context of the learning--all of the elements that comprise the experience around the content--that is most important" ([paragraph] 3). Based on the Otter Group's model of how best to teach and learn online, she presents many elements that must be managed to create e-learning programs: not too much content and too little context, valued learning experience, course as learning communities, personalization, and an open technology source.

A study titled, "Student support services and success factors for adult online learners," conducted by Greer, Hudson, and Paugh (1998) examined a variety of student support services and four areas for student success from the viewpoint of web-based learners in the University of Central Florida College of Education, Vocational Education area. They point out that the most common theme in terms of students' perceptions of success factors were budgeting time, being self-motivated, and having supportive friends and family.

Shepherd (2001) argues that the reason why learners dropout is a simple one of motivation. In addition, motivation has two determining factors. The first factor is a desirable outcome, whether this is the achievement of a personal goal, recognition from others or some form of tangible reward such as money or promotion. There is a flip side to this, in that the learner may be seeking to avoid some penalty, such as a reprimand, disapproval or some financial disincentive. The second factor in motivation is the learner's perception of the likelihood, given that learners put in sufficient effort, of the learner obtaining their reward or avoiding the penalty. If the means to the end is too tortuous, the motivation will drop regardless of how desirable the outcome may be. Shepherd maintains that "even if the incentives are sufficient to get learners started, e-learning can place many obstacles in the way of successful completion. Removing, or reducing the effect of these obstacles is essential to curing the drop-out problem" (Shepherd, 2001). These obstacles are inappropriate or inadequate content, lack of time and/or inadequate time to learn, no support for their learning by peers and training mangers, and the assessment of the learner's learning process by tutors or managers.

Based on a case study, Chyung (2000, 2001a, 2001b) finds some reasons for dropout in online distance education. Chyung, Winiecki, and Fenner (1998) found that the satisfaction of adult learners in an online program during the first or second courses was the major factor, which determined learners' decisions about whether or not to continue in the program. Forty-two percent of the students who dropped out expressed dissatisfaction with the learning environment as the reason. Another reason given was a discrepancy between professional or personal interests and course structure. In a study by Lim (2001) to develop a predictive model of satisfaction of adult learners in a web-based distance education course and their intent to participate in the future, she found that computer self-efficacy was the only predictor variable that was statistically significant out of variables included in the predictive model. The variables included in the model were computer self-efficacy, academic self-concept, age, gender, academic status, years of computer use, frequency of computer use, computer training, Internet in a class, and participation in a workshop for web-based courses.

Some e-learning experts present many strategies or tips for the success of e-learning. Interestingly, Augusto Failde, Senior Vice President of Global Development at NYUonline, proposes 11 strategies that companies can use to help ensure high course completion rate (Frankola, 2001a). These strategies are as follows: (1) develop a culture that takes online learning just as seriously as classroom training, (2) do individual comparisons, (3) hold managers accountable for the success of their employees, (4) use managers as role models, (5) create a social dimension to e-learning, (6) make expectations clear up front, (7) provide formal rewards, (8) track performance, (9) get personal, (10) hold a team competition, and (11) launch a communications campaign. He articulates, "Good companies that recognize the importance of human capital must motivate and support employees as they develop a commitment to life-long learning" (Frankola, 2001a). Broadbent (2001) also gives e-learning engagers some tips for e-learning success. These tips include: (1) focusing on a clear business objective, (2) don't set very high expectations, (3) hire consultants or a service provider to handle all of e-learning needs, (4) don't force e-learning on resisters, (5) don't evaluate. Black (1998) emphasizes the following: (1) offer short classes, (2) make graphics simple and easy to read, (3) foster collegiality by asking students to contribute information about themselves and their interests, (4) vary the way you interact with learners, (5) avoid superfluous media, and (6) use a combination of synchronous and asynchronous instruction to reinforce new material, design assignments, and improve learner retention. Horton (2000) contends, "Successful virtual classroom courses usually depend more on human interaction than on technological infrastructure." Hence, he points out that selecting a qualified instructor, keeping the class small, and responding promptly and reliably are important in planning a Web-Based Training (WBT) course. In addition to this, he suggests holding a pre-class get-together to overcome initial hurdles, publishing a comprehensive syllabus, preparing learners to participate (e.g., the etiquette for online meetings), managing collaborative activities, teaching the class-rather than just letting it happen (e.g., contact participants individually, help classmates get to know one another, stay on the published schedule, keep office hours, pace learners, do not spend too much time teaching the course software), conducting live events, making participants visible, and staying in touch after the class. Khan and Vega (1997) contend that the Web design should be "logical, user-friendly, and meaningful."

As many researchers point out, motivating learners is a very important factor to retaining them in e-learning courses. "Successful WBT courses rely on the self-discipline and focus of motivated learners" (Horton, 2000, p. 418). He suggests some techniques that designers and instructors can use to keep learners interested, energized, and enthusiastic. These techniques are: (1) set clear expectations, (2) require commitment, (3) feature the WIIFM (What's in it for me?), (4) make WBT fun and interesting, (5) offer bribes, (6) pace and prompt learners, (7) provide encouraging feedback, (8) build a learning community, (9) intervene with unmotivated learners, and (10) redeem troublemakers.

Driscoll (1998) contends, "Designing effective WBT requires knowledge of the unique characteristics of adult learners and an understanding of the facilitator's role" (p. 13). He outlines the characteristics of adult learners as: real-life experience, problem centered learning, continuous learners, varied learning styles, responsibilities beyond the training situation, and meaningful learning.

Like Tinto's model (1975), the two dimensions of integration, academic and social, form the core of Kemper's open learning model (1995). This model was developed through the process of validation of the model, utilizing both quantitative and qualitative data from a diversity of sources. This model consists of several constructs that affect outcome of students in open learning courses. The construct of entry characteristics that influences integration variables consists of demographic status, educational qualifications, family status, and employment. Kemper (1995) articulates that entry characteristics are not good predictors of final outcomes, because they are just a starting point in determining how much difficulty a student is likely to face in coping with a course. He continues, "Many students with apparently adverse circumstances do succeed" (p. 77). The social integration construct consists of enrollment encouragement, study encouragement, and family environment and examines the degree to which students are able to integrate their academics with the often conflicting employment, family and social requirements. Kemper (1995) asserts that "social integration can be achieved, even in the face of an inhospitable social environment, if a time and space for study are negotiated" (p. 88). The external attribution construct consists of insufficient time, unexpected events, and distractions. The lower levels of social integration affect the negative academic integration of students. In the model, academic integration is spilt into the positive (academic integration) and negative (academic incompatibility) tracks. Each construct consists of four indicators such as study approach, motivation, course evaluation, and language ability. Academic integration is understood as "encompassing all facets of a course and all elements of contact between an institution and the students whether these are of an academic, administrative or social nature" (Kemper, 1995, p. 99). In addition, GPA functions to some extent as an intervening variable between academic incompatibility and dropout. At the final step of the model, a cost/benefit analysis, the student has to make a decision about either dropping-out or completing study. This final step includes a recycling loop that provides a mechanism for switching from one track to the other.

Factors Identified from the Literature Review of Dropout in E-Learning

Based on variables (see Table 1) identified from the literature review of dropout in e-learning and the models of dropout, five constructs were categorized: individual background, motivation, academic integration, social integration, and technological environment.

Some Implications for the Study of Dropout of Adult Learners in E-Learning

Year after year, e-learning is becoming more popular because it allows training to be available on demand, to be delivered remotely, and to keep up with the rapid pace of economic change. The flexibility of time, place, low delivery cost, and program contents provided via e-learning is very appealing to workers who are trying to improve their careers related to job performance or individual development as well as to training mangers. Undoubtedly, e-learning based on today's advanced technologies has been considered as the best learning delivery media for this purpose. At this point, it needs to understand the dropout of adult learners in e-learning for more effective and efficient e-learning operation.

The literature review has at least two significant implications for the study of dropout of adult learners in e-learning. First, it needs to build a holistic model that accounts for the phenomena of adult learners' dropout in e-learning. Whatever the setting, it is difficult to comprehend the reason for the learners' dropout in adult education and training programs because the reasons for dropout among learners are numerous and complex. Theory in the area of learner dropout supports a multivariate framework to account for the complexity inherent in analyzing the learners' participation in multiple spheres of activity (Osborn, 2001). Second, in addition, there is a need for practical contributions of the new model of dropout in the field of adult education, especially e-learning. This means that any new model based on or including a variety of perspectives should have the power to provide practical contributions to the field of adult education. For instance, if adult learners drop out of a course due to motivational factors, some prescriptive strategies developed in terms of a motivational aspect could be provided for adult education practitioners of e-learning programs. Also, e-learning program designers and instructors could use it to prevent or decrease the dropout rate in e-learning practice.

Table 1 Factors Identified from the Literature Review of Dropout in
E-Learning

Constructs Studies             Individual              Motivation
                               Background

ASTD & MASIE Center (2001)                             * Incentives
                                                       * Lack of
                                                         accountability
                                                         for completing
                                                         classes
                                                       * Poorly designed
                                                         courseware
Augusto Failde                                         * Extrinsic
(as cited in Frankola, 2001a)                            motivation--
                                                         formal reward,
                                                         team
                                                         competition,
                                                         clear
                                                         expectations,
                                                         etc.
Broadbent (2001)                                       * Clear
                                                         expectations
                                                       * Satisfaction
Black (1998)                                           * Challengeable
                                                         expectations
                                                       * Clear business
                                                         objective
                                                       * Short classes
Brown (1996)
Chyung (2000, 2001a, 2001b)                            * Attraction
                                                       * Confidence
                                                       * Relevance
                                                       * Satisfaction
Chyung et al. (1998)                                   * Satisfaction
Driscoll (1998)                * Characteristics of
                                 adult learners
Frankola (2001b)               * Individual learning   * Lack of learner
                                 preferences             control of
                                                         content
                                                       * Poorly designed
                                                         course
Frontline Group (2001)         * Learning styles       * Poorly designed
                                                         course
Greer et al. (1998)                                    * Self-motivated
Gilroy (2001)                                          * Satisfaction
                                                       * Poorly designed
                                                         course
                                                       * Personalization
Horton (2000)                                          * Live event
                                                       * Incentive
                                                       * Pre-class
                                                         meeting
                                                       * Staying on the
                                                         published
                                                         schedule
                                                       * Pacing learners
                                                       * Making
                                                         participants
                                                         visible
Hossein Arsham (as cited in
Elearningpost, 2001)
Kemper (1995)                  * Entry                 * Intrinsic/
                                 charateristics          extrinsic
                                                         motivation
                                                       * Positive/
                                                         negative course
                                                         evaluation
Khan & Vega (1997)                                     * Poorly designed
                                                         course
Lim (2001)                                             * Self-efficacy
NYUonline                                              * Live session
(Cited in Frankola, 2001b)
Osborn (2001)                  * Educational level     * Computer
                               * Number of credit        confidence
                                 hours taken in the    * Lower
                                 current semester,       motivation
                                 and number of
                                 previous distance
                                 learning courses.
Shepherd (2001)                                        * Incentive
                                                       * Learner's
                                                         perception of
                                                         the likelihood
                                                         of the learner
                                                         obtaining their
                                                         reward or
                                                         avoiding the
                                                         penalty
                                                       * Inadequate
                                                         contents
                                                       * Assessment of
                                                         learner's
                                                         learning
                                                         process by
                                                         trainers
Sun Microsystems Inc
(as cited in Frankola, 2001b)
Towles et al (1993)
Vrasidas and Mclsaac (1999)    * Prior experience      * The structure
                                 with computer-          of the course
                                 mediated
                                 communications

Constructs Studies              Academic Integration  Social Integration

ASTD & MASIE Center (2001)
Augusto Failde                                        * Social dimension
(as cited in Frankola, 2001a)
Broadbent (2001)
Black (1998)                    * Interaction
                                  between tutors and
                                  learners
Brown (1996)                    * Support from tutor
Chyung (2000, 2001a, 2001b)
Chyung et al. (1998)
Driscoll (1998)
Frankola (2001b)                * Lack of management  * Lack of time
                                  /support
                                * Inexperienced
                                  instructor
Frontline Group (2001)          * Supporting systems
Greer et al. (1998)                                   * Budgeting time
                                                      * Supportive
                                                        friends and
                                                        family
Gilroy (2001)                   * Learning community
Horton (2000)                   * Qualified
                                  instructors
                                * Interaction
                                  individual contact
                                * Prompt feedback
Hossein Arsham (as cited in     * Interactivity with
Elearningpost, 2001)              learners
Kemper (1995)                   * Poor/good language
                                  skills
                                * Deep/surface
                                  approach
Khan & Vega (1997)
Lim (2001)
NYUonline
(Cited in Frankola, 2001b)
Osborn (2001)                                         * Less-stable
                                                        study
                                                        environments
Shepherd (2001)                 * No support of peer  * Lack of time
                                  and training
                                  managers
Sun Microsystems Inc            * Crucial
(as cited in Frankola, 2001b)     interactivity;
                                  faculty and
                                  learners
Towles et al (1993)             * Faculty-initiated
                                  interaction
Vrasidas and Mclsaac (1999)     * Interaction
                                * Class size
                                * Feedback

Constructs Studies              Technological Environment

ASTD & MASIE Center (2001)      * Problems with technology
Augusto Failde
(as cited in Frankola, 2001a)
Broadbent (2001)
Black (1998)                    * Superfluous media
Brown (1996)
Chyung (2000, 2001a, 2001b)
Chyung et al. (1998)
Driscoll (1998)
Frankola (2001b)                * Technical hurdles
Frontline Group (2001)
Greer et al. (1998)
Gilroy (2001)
Horton (2000)                   * Technical hurdles
Hossein Arsham (as cited in
Elearningpost, 2001)
Kemper (1995)                   * Family environment
                                * Enrollment encouragement
                                * Study encouragement
                                * Insufficient time
                                * Unexpected events
                                * Distractions
Khan & Vega (1997)
Lim (2001)
NYUonline
(Cited in Frankola, 2001b)
Osborn (2001)
Shepherd (2001)
Sun Microsystems Inc
(as cited in Frankola, 2001b)
Towles et al (1993)
Vrasidas and Mclsaac (1999)

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JUSUNG JUN 

The University of Georgia, USA

[e-mail]