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
The who, what, when, and why of lecture capture
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Scrutable adaptation: because we can and must
AH'06 Proceedings of the 4th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
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This paper considers the issue of the locus of control in adaptive e-learning environments from the perspective of a new stakeholder; the instructional expert. With an ever increasing ability to gain insight into learners based on their online activities, instructors and instructional designers are poised to add value to the process of adaptation, a process normally reserved for either systems designers or the end user. This work describes the design of an e-learning system which provides automated analytics information to these experts for consideration, and then leverages the insights these experts have made as the basis for content and feature adaptation.