During a learning session, the biological model decides what to do next, as a human teacher would do in one-on-one instruction. It is many advantages over traditional “inference models.”
At the heart of Area9 Rhapsode™ is the adaptive engine—the mechanism that decides what to do next, as a human teacher would do in one-on-one instruction. Area9’s “biological model” (so named because it mimics behavior found in biological environments and organisms) overcomes the limitations of “inference models” used elsewhere. Inference models require maps of content that are prohibitively expensive to develop, and ineffective in practice. Our research over decades has shown that making arrogant or top-down assumptions about what a student needs leads to negative outcomes for the student.
The fundamental premise of our biological model is that there are many pathways to the same learning objective, but the pathways are determined in real-time using learner interactions, rather than being pre-programmed. Our adaptive models are multi-dimensional and have sub-components that each “act” continuously, measuring and modeling knowledge, taking into account self-evaluation, motivation and time, and knowledge decay – among many other things.
This approach dramatically simplifies the content development process, makes the models work equally well for different subjects and audiences, and enables the best possible outcome for every learner.