A Tale of two MOOCs : Analyzing Long-Term Course Dynamics

Matthieu Cisel, Mattias Mano, Rémi Bachelet, Philippe Silberzahn

Ø  How do learner categories evolve over iterations in two MOOCs?

Ø  What share of the course activity do the different categories represent ?

Ø  How do sociodemographic variables impact course completion ?

Ø  How robust are those results over iterations ?

Research questions

q  A first categorisation inspired from Ho et al. 2014 / Anderson 2014

Ø  Completers: earn a certificate

Ø  Disengaging: do not complete, but submit at least a quizz

Ø  Auditing: Watch at least 10% of available videos, not a single quizz

Ø  Bystanders: Watch less than 10% of available videos, not a single quizz

An arbitrary classification of learners based on their levels of engagement

Evolution of learner categories over iterations

Evolution of learner categories over iterations

Share of the course activity and learner categories

Video consumption behavior among disengaging and auditing learners

Disengaging  

Auditing  

Course demographics and completion rates

Odds  ra'o  for  demographics  background  on  the  probability  to  earn  a  cer'ficate  

Take-away messages

Ø  Proportion of active participants tend to decrease over time

Ø  Course demographics and learners intentions remain quite stable

Ø  Most of the course activity is driven by the nucleus of completers

Ø  Most auditing learners explored a minor fraction of the course activity

Ø  Impact of demographics is more obvious in some specific contexts

Conclusion / on-going research

q  Can we find similar patterns in most MOOCs? Ø  Currently analyzing around 15 MOOCs (Coursera, FUN, Unow) Ø  Define more robust typology

q  How to interpret observed dynamics based on qualitative data? Ø  40 interviews with learners, 20 with MOOC instructors

q  How to measure the success of a MOOC based on learning analytics?