A smart education investor called me yesterday and asked a good question, “Can adaptive learning can be productized and sold as a service?”
Customization holds the promise of increasing learning productivity by targeting educational experiences by level, interest, and modality. Teacher judgment will increasinly be aided by smart recommendation engines that help to create individualized learning pathways.
The growth and acquisition of Carnegie Learning is a positive early signal about adaptive content. A recent research report about Dreambox use at Rocketship will boost adoption and bolster investment in adaptive content. Growth of game-based content like MangaHigh (a Learn Capital portfolio company) demonstrates the dual benefits of engagement and adaptive learning.
With active investment (impact and return seeking), it seems clear that adaptive curriculum sequences will flourish in English, math and science. The big question is how and when recommendation engines will be developed that do a great job queuing big libraries of heterogeneous content. It’s likely that improvements will be made in three approaches
1) Proprietary content: digital courseware providers including Connections, K12, McGraw, Pearson, and Time to Know are adding learning objects and improving the ability to individualize pathways to mastery.
Similarly, Wireless Generation queues open source reading content based on regular assessment results.
Proprietary (or bounded OER like FreeReading.Net and HippoCampus.org) offer curation, navigation, organization compared to mashup playlists.
2) Search: several efforts are attempting to improve search particularly across open content but they are currently hampered by a lack of common tagging standards.
The benefit of search as recommendation engine is the world becomes one big learning repository. The downside is no curation and a lot of garbage.
3) Monitoring and mining. Platforms like Edmodo (a Learn Capital portfolio company) make it easy to grab and mash up free content and drop it into an instructional stream. Behind the scenes, Edmodo is tracking the use of instructional materials and will soon have the ability to make informed recommendations.
A bit further out (i.e., 2-3 years) we’ll see next gen LMS that combine performance data and user feedback to make recommendations
These developments bring me back to yesterday’s blog about textbooks and the benefit of curation, organization, and narration. Without a table of contents these new playlist systems will add coherence to the learning experience with standards-based gradebooks, achievement dashboards, and recognition systems (e.g., badges).
Customized learning, driven by adaptive engines and comprehensive learner profiles, will accelerate achievement and boost completion rates. Philanthropic and private equity investment is driving innovations in adaptive engines and that, with the ocean of keystroke data to come, will lead to important breakthroughs in learning and motivation sciences.