The present study focuses on a specific learner characteristic in the management of time - procrastination-, and its role in an online learning environment. More specifically, it was expected that procrastination would influence the successfulness of online learning and that this could be explained by the level of participation of learners in discussion forums. A study was conducted to test this hypothesis among a sample of learners taking a 10-week course on environmental and land use issues. As predicted, a negative relationship was found between procrastination and performance, and this relationship was mediated by the level of the learners' participation in discussion forums. In other words, it appears that if high procrastinators are less successful online learners than low procrastinators, it is partly due to their lack of participation in discussion forums during the learning process. Additionally, some behavioral differences between high and low procrastinators were found in the times they decided to (re)start working at a distance, felt motivated to work on their course, and felt like dropping out of the course. To conclude, some practical implications for tutoring online activities and for stimulating participation in online learning environments have been proposed.

Procrastination, participation, and performance in online learning environments

In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to accurately classify some e-learning students, whereas another may succeed, three decision schemes, which combine in different ways the results of the three machine learning techniques, were also tested. The method was examined in terms of overall accuracy, sensitivity and precision and its results were found to be significantly better than those reported in relevant literature.

Dropout prediction in e-learning courses through the combination of machine learning techniques

Using SERVQUAL to assess the quality of e-learning experience

Although online distance education provides adult learners with an opportunity for life-long learning, there are still factors challenging them to engage in educational processes. The purpose of this study is to explore the challenges faced by adult learners in online distance education through the analysis of the relevant literature. The articles (N=36) published in the key journals in the fields of open and distance education, instructional technology, and adult education were reviewed and analyzed through constant comparative analysis in the current study. The findings reveal that adult learners have challenges related to internal, external, and program-related factors indicating the interrelated nature of these challenges. The findings also show that the challenges experienced by adult learners vary depending on their age, gender, knowledge and skills as well as the context in which they study. The findings of this study, which has an exploratory nature, have several implications for distance education stakeholders such as administrators, instructors, instructional designers, and policy makers.

/pdf/challenges-faced-by-adult-learners-in-online-distance-4zxkmjdd33.pdf

Challenges Faced by Adult Learners in Online Distance Education: A Literature Review

International Journal of Self-Directed Learning

The current study examined four factors affecting retention in Web-based community college courses. Analyses were conducted on student demographics, student learning styles, course communication and external factors. The results suggest that Web-based courses are more attractive to busy students who are also more likely to fail or drop the course. The combined results from the four factors provided evidence that time management and procrastination are the primary reasons that community college students fail or drop a Web-based course. The study also found evidence that inability to get feedback from instructors may contribute to student dropout and failure in Web-based community college courses.

/pdf/an-analysis-of-multiple-factors-affecting-retention-in-web-1z9bduuokg.pdf

An analysis of multiple factors affecting retention in Web-based community college courses

The Efficacy of Providing Basic Computer Troubleshooting Skills to Pre-Service Teachers

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An analysis of multiple factors affecting retention in Web-based community college courses

The Efficacy of Providing Basic Computer Troubleshooting Skills to Pre-Service Teachers