Another blog entry by Knewton head honcho Jose Ferreira, this time explaining his latest thinking on what Knewton is trying to do by noting 3 types of what he calls infrastructure.
Small and mid size Ed Tech such as PSA, hopes Jose continues to develop the “adaptive learning service” for this market, in addition to their forays into enterprise level products.
Gets down and dirty with Ed Tech concepts, as Knewton defines them. Below, what he says Knewton is about:
Data Collection Infrastructure: Collects and processes huge amounts of proficiency data.
- Adaptive ontology: Maps the relationships between individual concepts, then integrates desired taxonomies, objectives, and student interactions.
- Model computation engine: Processes data from real-time streams and parallel distributed cluster computations for later use.
Inference Infrastructure: Further increases data set and generates insights from collected data.
- Psychometrics engine: Evaluates student proficiencies, content parameters, efficacy, and more. Exponentially increases each student’s data set through inference.
- Learning strategy engine: Evaluates students’ sensitivities to changes in teaching, assessment, pacing, and more.
- Feedback engine: Unifies this data and feeds results back into the adaptive ontology.
Personalization Infrastructure: Takes the combined data power of the entire network to find the optimal strategy for each student for every concept she learns.
- Recommendations engine: Provides ranked suggestions of what a student should do next, balancing goals, student strengths and weaknesses, engagement, and other factors.
- Predictive analytics engine: Predicts student metrics such as the rate and likelihood of achieving instructor-created goals (e.g., how likely is a student to pass an upcoming test with at least a 70%?), expected score, proficiency on concepts and taxonomies (e.g., state standards), and more.
- Unified learning history: A private account that enables students to connect learning experiences across disparate learning apps, subject areas, and time gaps to allow for a “hot start” in any subsequent Knewton-powered app.