Adaptive learning in Open edX will enable the platform to respond to a learner's interactions in real-time, automatically providing the learner with individualized support. Data analysis from earlier experimental attempts on edX.org and elsewhere show how adaptive learning mechanisms can significantly improve the learner's efficiency, engagement, and retention, while providing a more effective learning experience with metacognitive support for life-long learning.
The Adaptive Learning Presentation depicts a summary of our findings, culminating in a proposal for a common framework to integrate with external adaptive engines and services. We have held periodic adaptive learning workshops over the last few years. At this time, edX is investing in integration efforts and not native support of machine learning and adaptive engines. This may change over time. For a list of active (integration-focused) adaptive learning projects, see Adaptive Learning Projects.
Berkay Baykal (Deactivated), Scott Dunn (Deactivated), Nimisha Asthagiri (Deactivated), Marco Morales (Deactivated)
This space captures notes as we gathered information on Adaptive Learning, its usefulness, and formulated our design strategy.