Navigator uses highly curated Open Education Resources in conjunction with offline tasks to index a full spectrum of learning activities. Learners can interact with digital content, labs, simulations, and a multitude of formative assessment items (from machine graded items to offline rubric graded projects). Metadata collected for each assessment item helps to determine a learner’s depth of knowledge on that competency, skills developed, common struggles, and the current location of the learner.
The OERs in the system are entered into the system and are tagged by content experts or educators for standards, accessibility, and depth of knowledge. Relevance, efficacy, and engagement are automatically generated using activity stream data and a Bayesian Knowledge Tracing technique.
Learning activities are organized into lessons with assessments to enable learners to gain proficiency in the related competencies. To conform with local norms the lessons for these competencies can be structured into units and courses.
The search engine for learning is distinguished based on the structuring of the learning space, the curated catalog of learning activities and an understanding of the user as a learner and as a teacher. We use all of these signals in query rewrites and ranking to keep the search results pedagogically aware and personalized.