Why do open and distance education students drop out? Views from various stakeholders

Social networking website increases efficacy and engagement in a distance learning course about oral lesions

PURPOSE

Distance learning appears to be an attractive approach to continuing education courses, but one barrier is maintaining learner engagement throughout the course. The primary aim of this research was to evaluate the operational efficacy of a private Facebook™ group (FG) in serving as a support mechanism for distance learning courses, and its impact on three fundamental dimensions: the attrition rates of participants who did not complete the course (commonly referred to as dropout rates), the rates of course completion and approval, and the overall performance of the participants.

METHODS

The participants of this quasi-experimental study comprised 159 dental students and 565 dentists enrolled in an e-learning course on oral mucosal lesion diagnosis. Prior to the initiation of the course, all participants were provided with the option to join a private FG. Within this group, moderators shared motivational messages and provided reminders concerning deadlines. Moreover, participants had the opportunity to engage in interactive discussions pertaining to topics related to the course. The course itself followed a self-guided format, employing the flipped-classroom methodology, spanning a total of 50 instructional hours. In order to assess the effectiveness of the course, participants were presented with photographs illustrating 30 oral lesions and were asked to propose diagnostic hypotheses both before and after the educational intervention (pre-tests and post-tests).

RESULTS

Dentists who participated in the FG exhibited a significantly lower rate of discontinuation. As for dental students, their involvement in the group was positively associated with better performance, as determined by the percentage of accurate diagnostic hypotheses (a minimum of 70% correct responses was required for their approval in the course).

CONCLUSIONS

Facebook™ demonstrates promise as a supplementary pedagogical tool in distance education courses. The interactive nature of the platform has the potential to alleviate the inherent challenges of remote learning.

Self-directed learning skills and motivation during distance learning in the COVID-19 pandemic (case study: The university of Jordan)

This study aimed to assess the effect of distance learning on students' self-directed learning skills and motivation during the lockdown period of the COVID-19 pandemic. The study relies on a quantitative methodology. The data were collected using an administrative online survey distributed to 427 respondents with different majors (BBA) enrolled in the learning skills and scientific research skills course (obligatory course) in the second semester of the academic year 2020/2021 at The University of Jordan. Regression analysis was used to analyze the proposed hypotheses. The results showed that the independent variable (Distance Learning) positively influenced students' motivation and self-directed learning skills. The recommendations based on the outcomes of this research are useful for educational specialists to develop learning environments about the effects of distance learning on students' self-directed learning skills and motivation. In terms of limitations, the analysis was performed in one university only; therefore, attention must be paid when generalizing the results.

Student Dropout as a Never-Ending Evergreen Phenomenon of Online Distance Education

The research on student dropout demonstrates that there is no consensus on its definition and scope. Although there is an expanding collection of research on the topic, student dropout remains a significant issue, characterized by numerous uncertainties and ambiguous aspects. The primary aim of this investigation is to assess the research trends of student dropout within the distance education literature by employing data mining and analytic approaches. To identify these patterns, a total of 164 publications were examined by applying text mining and social network analysis. The study revealed some intriguing facts, such as the misinterpretation of the term "dropout" in different settings and the inadequacy of nonhuman analytics to explain the phenomenon, and promising implications on how to lessen dropout rates in open and distance learning environments. Based on the findings of the study, this article proposes possible directions for future research, including the need to provide a precise definition of the term "dropout" in the context of distance learning, to develop ethical principles, policies, and frameworks for the use of algorithmic approaches to predict student dropout, and finally, to adopt a human-centered approach aimed at fostering learners' motivation, satisfaction, and independence to reduce the rate of dropout in distance education.