Educators will be able to identify and sequence the best of granular open, proprietary, and commercial content for their learners. As they contribute, reuse, and remix content, they will build educational experiences that are fundamentally different from monolithic ebooks: dynamic online coursepacks that combine targeted and proven learning content with effective assessment and analytics.
Building on the power of data mining, crowd-sourcing and social networking, the platform will form, nurture, and support collaborative communities of practice with educators from around the world.
It will provide an end-to-end solution from digital library functions, digital rights management, e-commerce, recommendation and sequencing tools, all the way to the course management functionality required to immediately deploy the online coursepacks: streamlined, efficient, reliable.
Recommendations for your course
How do you find appropriate content in a large repository? The same way that you find things in an online bookstore.
Online bookstores can do this, since they know what other customers put into the same shopping basket, and they know what you bought in the past. LON-CAPA knows the same things: it knows what other instructors put into the same chapters and the same assignments, and it knows what you selected in the past.
In addition, for interactive resources, LON-CAPA can give quality and effectiveness measures, since the close integration of repository and deployment allows for efficient usage tracking, data mining, and analytics.
Does this work? Analysis of selection data from the LON-CAPA repository yielded some 2.8 million association rules, which lead to useful recommendations. Analytics of the 200,000 problems in the pool are based on 138,320,000 student transactions. An end-to-end solution allows for data to flow back.