Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Detecting Significant Events in Lecture Video using Supervised Machine Learning
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Research Methods in Human-Computer Interaction
Research Methods in Human-Computer Interaction
OpenCast Matterhorn 1.1: reaching new heights
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Pros and cons for teaching courses in the classroom and online simultaneously
Proceedings of the 17th ACM annual conference on Innovation and technology in computer science education
Using an instructional expert to mediate the locus of control in adaptive e-learning systems
Proceedings of the 2nd International Conference on Learning Analytics and Knowledge
Proceedings of the Third International Conference on Learning Analytics and Knowledge
Analytics of the effects of video use and instruction to support reflective learning
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
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Video lecture capture is rapidly being deploying in higher-education institutions as a means of increasing student learning, outreach, and experience. Understanding how learners use these systems and relating this use back to pedagogical and institutional goals is a hard issue that has largely been unexplored. This work describes a novel web-based lecture presentation system which contains fine-grained user tracking features. These features, along with student surveys, have been used to help analyse the behaviour of hundreds of students over an academic term, quantifying both the learning approaches of students and their perceptions on learning with lecture capture.