Learners have a skyline indicating the maximum number of competencies they have in each facet across the set of facets of their interest. Drill-down from this would enable the learner to know their proficiency across domains of learning in a facet.
Learner vectors include not just proficiency indicated by the skyline, but also the progress, portfolio, performance, and preferences. To leverage the science of learning, Navigator computes values for attributes such as grit and self-confidence. We define these in terms of activities about a competency and measure the learner’s engagement on these.