Deadlines and MOOCs: How Do Students Behave in MOOCs with and without Deadlines

Abstract

Full research paper-Online education can be delivered in many ways. For example, some MOOCs let students to proceed with their own pace, while others rely on strict schedules. Although the variety of how MOOCs can be organized is generally well understood, less is known about how the different ways of organizing MOOCs affect retention. In this work, we compare self-paced and fixed-schedule MOOCs in terms of retention and work-load. Using data from over 8.000 students participating in two versions of a massive open online course in programming, we observe that drop-out rates at the beginning of the courses are greater than towards the end of the courses, with self-paced MOOC being more extreme in this respect. Mostly because of different starts, the fixed-schedule course has a better overall retention rate (45%) than its self-paced counterpart (13%). We hypothesize that students initial investment of time and effort contributes to their persistence in their course, meaning that they do not want to let their initial investment go to waste. At the same time, in both self-paced and fixed-schedule MOOCs, there are students who receive almost full points from one week but fail to continue to the next week. This suggests that the issue of dropouts in MOOCs may also be related to participants struggling to take up new tasks or schedule their work over a longer time period. Our results support scheduling student activities in open online courses and opens up new research directions in engaging students in self-paced courses.

Dropout Time and Learners’ Performance in Computer Programming MOOCs

“…However, activity is difficult to define. It may be that the learner is taking part in any activity, such as either just watching videos [19] or only completing mandatory activities [13]. Chen et al [20] and Fei and Yeung [18] have gathered definitions from different authors and divided them into three groups.…”

“…At the beginning of the course, learners may not know enough about the curriculum [23] and have different expectations for the course content [24]. They may discover that the course is not suitable for them [13,23,24], for example, learners realise that the course requires too much time to complete [13]. Learners may choose to only engage with the learning materials and never perform any mandatory activities [12].…”

“…In order to provide help to learners when they need it the most, and keeping in mind that course completion or dropout is often contingent on learners' performance in the course, this study seeks to identify the periods when learners are most likely to drop out, as well as an individual's performance before dropping out. Research concerning dropout rates has focused on the successive offerings of the same course [12] or different organisations of the same course [13] and has been based on one [9,14] or multiple different courses with different durations [11,15], and demographics [11]. It has also been studied how course length predicts completion rates [15] and how a learners' background data and organisation of evaluation, among other aspects, are related to dropouts in courses with different durations [11].…”

Development of a simple and effective online training for health workers: results from a pilot in Nigeria

“…Course design factors also influence learner engagement and retention. For example, shorter online courses and those with deadlines have higher completion rates [ 25 , 26 ].…”

To Opt in or to Opt Out? Predicting Student Preference for Learning Analytics-Based Formative Feedback

“…The nature of the interaction is often asynchronous, as learners and teachers may perform their tasks at different times. These self-paced settings afford learners more autonomy [5], [6] but increase the need for self-regulation and complicate teachers' chances to support and guide students.…”