Comparing the Factors That Predict Completion and Grades Among For-Credit and Open/MOOC Students in Online Learning

Abstract

Online education continues to become an increasingly prominent part of higher education, but many students struggle in distance courses. For this reasonFor this reason, there has been considerable interest in predicting which students will succeed in online courses , achieving poor grades or dropping out prior to course completionn). Effective intervention depends on understanding which students are at-risk in terms of actionable factors, and behavior within an online course is one key potential factor for intervention. In recent years, many have suggested that Massive Online Open Courses (MOOCs) are a particularly useful place to conduct research into behavior and interventions, given both their size and the relatively low consequences/costs of experimentation. However, it is not yet clear whether the same factors are associated with student success in open courses such as MOOCs as in for-credit course -- an important consideration before transferring research results between these two contexts. While there has been considerable research in each context, differences between course design and population limit our ability to know how broadly findings generalize; differences between studies may have nothing to do with whether students are taking a course for-credit or as a MOOC. Do , this body of literature has been split into two-subcategories: research on success in MOOCs and research on success in For-credit courses. Few studies Few studies have attempted tohave attempted to understand how students and their learning experiences differ between these contexts, bypassing an opportunity to synthesize findings across different student populations who engage in online education. Do bypassing an opportunity to synthesize findings across different populations who engage in online education. To address this issue, we Do learners behave the same way in MOOCs and for-credit courses? AAre the implications for learning different, even for the exact same behaviors? In this paper, we study these issues through developing models that predict student course success from online interactions, in an online learning platform that caters to both distinct student groups (i.e., students who enroll on a for-credit or a non-credit basis). Our findings indicate that our models perform well enough to predict students’ course grades for new students across both of our populations. Furthermore, models trained on one of the two populations were able to generalize to new students in the other student population. We find that features related to comments were good predictors of student grade for both groups. Models generated from this research can now be used by instructors and course designers to identify at-risk students both for-credit and MOOC learners, towards providing both groups with better support.

Retention in MOOCS: some key factors

“…However, given the low levels of student retention in the Moocs mentioned above, it was considered pertinent to discern whether there is any difference in these levels between the cMoocs and the xMoocs, a matter that to date is not easy to establish. For this purpose, it is necessary to consider the need to consolidate the lessons learned from various investigations that have addressed dropout in Moocs from different perspectives (ALMEDA et al, 2018;GARDNER;BROOKS, 2018;VITIELLO et al, 2017) but also that they have not been able to specify this phenomenon based on the differences between cMoocs and xMoocs, beyond what they can report from a specific case such as the one described in Dawson et al (2015). Such an approach would make it possible to generate practical knowledge for those who design this type of learning experience, for which reason it has been proposed to carry out a systematic review of literature on studies conducted on attrition in Moocs in order to identify possible differences in this matter between two most recognized types of Mooc.…”

The social dimension of participation and completion in MOOCs

“…Nonetheless, consensus over alternative definitions and measurement of success in MOOCs has not been reached yet. Nonetheless, despite contrasting views, the certificate of completion and the share of activities done in the course is still considered a valuable piece of information about learners' behavior and success (Almeda et al, 2018;Reich, 2014;Wang & Baker, 2018).…”

“…Empirical literature on the type of participation to MOOCs online forums and the social characteristics of people engaged in such activity is still limited. Most of the research available points to a positive association between participation to forum discussions and positive outcomes in MOOCs (Almeda et al, 2018;Zhang et al, 2017). However, by far little is known about the social characteristics of learners posting on the MOOC forum and its mediating role on SES and completion.…”

Socializing on MOOCs: Comparing University and Self-enrolled Students

“…Thus, whether a MOOC student is self-enrolled or compelled to enroll might play a critical role in their learning behavior. Only one study so far has compared MOOC vs. for-credit courses but it did not consider the fact MOOCs could be included in for-credit courses [2]. Of course, one would expect a much lower dropout rate (i.e.…”

“…, when comparing (1) university-enrolled students (UES) to(2) other MOOC participants (OMP) in GdP6 for the basic certificate, a Mann-Whitney test indicated that for ForUseful (1) (med=3, mean=2.81) was inferior to (2) (med=4, mean=3.34), U = 62209.0, p < 0.001 ; for ForUsed (1) (med=1, mean=1.09) was inferior to (2) (med=1, mean=1.17), U = 76731.5, p = 0.021, however this result was not statistically significant after correction for multiple tests ; other tests were not statistically significant when comparing these two samples.…”