Abstract:

Studies investigating retention specific to online courses are scarce, and those extant generally fail to yield practical solutions aimed at curtailing attrition rates, either because they attempt to isolate and profile the individual characteristics of successful students or use registration data to compare those who completed their studies to those who discontinued them (Powell, Conway, & Ross, 1990; Dupin-Bryant, 2004). In so doing, the role of the institution in influencing its own retention rates has been marginalized, since the information gathered hinges solely on student characteristics. Furthermore, the definition of attrition and the way it is measured has seldom been made clear, and rare are the studies that have gathered data directly from the students who dropped out, thereby limiting one's ability to identify the factors that lead to the decision.

This presentation summarizes a study that employed a unique framework to investigate voluntary student attrition in undergraduate asynchronous online courses. In particular, this longitudinal exploratory study used a multi-analytic methodology to identify the students who were enrolling in the online courses, find out why they enrolled in them, and isolate the factors that were at the root of their dropout decision. Survivor analysis is introduced as an additional tool which offers the ability to pinpoint the times during the semester when the students are at the highest risk of dropping out.

A major goal of this study was to re-evaluate the role played by the educational institution in the learner's dropout decision, so as to empower institutions to identify avenues of action that could potentially curtail this behaviour. The results of the survivor analysis helped confirm that students were at the highest risk of dropping out of their course when a significant investment was required in order to maintain an acceptable level of academic performance. A student's decision to persist or discontinue in their asynchronous online course experience was ultimately an economic assessment in which a cost-benefit analysis was carried out to determine if their limited resources (i.e., time, energy, and effort) should be diverted to another activity, especially if their academic performance risked being compromised.

It was through a multi-analytic approach that combined data from multiple sources (e.g., the students who persisted, the students who dropped out, the registration database, the course instructors and teaching assistants, etc…) that it was possible to isolate the areas where interventions by the institution might be most effective to influence the retention rates in individual courses.

Using this framework, the results of this study suggested that the educational institution could improve its online retention rates by helping students set realistic expectations about the course, use timely measurement of student academic integration within the individual courses (to identify potential problems as early as possible), and through the adoption of more efficient customer-centred practices to its operations, particularly with respect to the quality and speed of learner feedback. In this increasingly competitive global marketplace, harnessing one's influence on attrition may not simply be a matter of good practice, but also of academic survival.

Keywords:

e-learning, on-line, courses, asynchronous, retention, attrition, dropout, survival analysis, evaluation, instructional, design, undergraduate.