A behavior model for persuasive design
Proceedings of the 4th International Conference on Persuasive Technology
Content analysis schemes to analyze transcripts of online asynchronous discussion groups: A review
Computers & Education - Methodological issue in researching CSCL
A Handbook of Statistical Analyses Using R, Second Edition
A Handbook of Statistical Analyses Using R, Second Edition
User models for adaptive hypermedia and adaptive educational systems
The adaptive web
Building Successful Online Communities: Evidence-Based Social Design
Building Successful Online Communities: Evidence-Based Social Design
Peer and self assessment in massive online classes
ACM Transactions on Computer-Human Interaction (TOCHI)
Teaching creative problem solving in a MOOC
Proceedings of the 45th ACM technical symposium on Computer science education
Understanding in-video dropouts and interaction peaks inonline lecture videos
Proceedings of the first ACM conference on Learning @ scale conference
How video production affects student engagement: an empirical study of MOOC videos
Proceedings of the first ACM conference on Learning @ scale conference
Student skill and goal achievement in the mapping with google MOOC
Proceedings of the first ACM conference on Learning @ scale conference
Monitoring MOOCs: which information sources do instructors value?
Proceedings of the first ACM conference on Learning @ scale conference
Demographic differences in how students navigate through MOOCs
Proceedings of the first ACM conference on Learning @ scale conference
Analysis of dynamic resource access patterns in a blended learning course
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
Visualizing patterns of student engagement and performance in MOOCs
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
Designing pedagogical interventions to support student use of learning analytics
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
Success, activity and drop-outs in MOOCs an exploratory study on the UNED COMA courses
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
Proceedings of the first ACM conference on Learning @ scale conference
Corporate learning at scale: lessons from a large online course at google
Proceedings of the first ACM conference on Learning @ scale conference
Visual analytics of MOOCs at maryland
Proceedings of the first ACM conference on Learning @ scale conference
What does enrollment in a MOOC mean?
Proceedings of the first ACM conference on Learning @ scale conference
Engaging with massive online courses
Proceedings of the 23rd international conference on World wide web
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As MOOCs grow in popularity, the relatively low completion rates of learners has been a central criticism. This focus on completion rates, however, reflects a monolithic view of disengagement that does not allow MOOC designers to target interventions or develop adaptive course features for particular subpopulations of learners. To address this, we present a simple, scalable, and informative classification method that identifies a small number of longitudinal engagement trajectories in MOOCs. Learners are classified based on their patterns of interaction with video lectures and assessments, the primary features of most MOOCs to date. In an analysis of three computer science MOOCs, the classifier consistently identifies four prototypical trajectories of engagement. The most notable of these is the learners who stay engaged through the course without taking assessments. These trajectories are also a useful framework for the comparison of learner engagement between different course structures or instructional approaches. We compare learners in each trajectory and course across demographics, forum participation, video access, and reports of overall experience. These results inform a discussion of future interventions, research, and design directions for MOOCs. Potential improvements to the classification mechanism are also discussed, including the introduction of more fine-grained analytics.