The next generation of transformative learning platforms will include personalized instruction, social learning, and related services. They will integrate the functionality of learning management, student information systems, and longitudinal data systems. They’ll take advantage of the explosion of data that will come along with assessment embedded in digital content (e.g., score from a learning game). Deploying these powerful platforms will require a series of data agreements related to privacy and disaggregated content.
Some of these platforms will be limited to proprietary content. Others will be entirely open content. The best and most widely used and supported ones will be a mixture of the two.
As I’ve discussed previously, social learning (e.g., portfolio company Edmodo.com) will become as important an organizational element as classroom. Students building the same subskill or exploring the same problem will form learning communities for peer-to-peer learning, team projects, content sharing, etc.
A comprehensive learner profile will drive a smart recommendation engine that will queue content by level, interest, modality, popularity, performance with similar students, and sequence (ie, learning objects designed primarily to be used in sequence as opposed to independent learning objects). This capability will begin to approach AI
capability in a few years.
Key to making this all work will be a robust service economy. In addition to premium content, platform will be monetized by student, teacher, school and district services (as well as new school development).
This picture is expensive enough that foundations and the feds will need to provide some risk mitigation capital. If states and consortia can frame big enough markets, vendors will invest, and aligned support services will be developed.
This could start as a design prize.