Massive open online course completion rates revisited: Assessment, length and attrition
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
- Teacher spread
- 0.328 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
<p>This analysis is based upon enrolment and completion data collected for a total of 221 Massive Open Online Courses (MOOCs). It extends previously reported work (Jordan, 2014) with an expanded dataset; the original work is extended to include a multiple regression analysis of factors that affect completion rates and analysis of attrition rates during courses. Completion rates (defined as the percentage of enrolled students who completed the course) vary from 0.7% to 52.1%, with a median value of 12.6%. Since their inception, enrolments on MOOCs have fallen while completion rates have increased. Completion rates vary significantly according to course length (longer courses having lower completion rates), start date (more recent courses having higher percentage completion) and assessment type (courses using auto grading only having higher completion rates). For a sub-sample of courses where rates of active use and assessment submission across the course are available, the first and second weeks appear to be critical in achieving student engagement, after which the proportion of active students and those submitting assessments levels out, with less than 3% difference between them.</p>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- The International Review of Research in Open and Distributed Learning
- Topic
- Online Learning and Analytics
- Field
- Computer Science
- Canadian institutions
- —
- Funders
- Bill and Melinda Gates Foundation
- Keywords
- AttritionGrading (engineering)Distance educationMassive open online courseRegression analysisMedicineStatisticsMedical educationDemographyPsychologyMathematics educationMathematicsDentistry
- Has abstract in OpenAlex
- yes