Abstract: A combination of knowledge representation and retrieval, assessments and personalization for a tutoring platform that provides an automated phased word exposition method for vocabulary learning and enable learners to learn words (or any learning objective) with sufficient proficiency and without excessive repetition. The phased learning objective method implements a moving average model that models the learner across multiple dimensions (e.g. reading, listening, writing, speaking) such that the platform is confident of the learner's understanding, while using minimal assessment doses, and such that the understanding transfers across experiences. The method implemented provides for multiple learning and assessment activities for a learning objective and leverages the same learner model for each learning dimension. Each word of a word set passes through learning and assessment-only phases for statistically significant evidence of learning.

Abstract: Personalized video interjections based on a learner model and a learning objective. A method for adding interjections to a video includes analyzing the content of a plurality of videos based on a set of learning objectives, selecting a video based on a learning objective, determining types of video interjections using an analytics engine that compares a learner model and the learning objective, determining a location for the video interjections using the analytics engine, generating a video interjection for each video interjection type and inserting the video interjections into the video at the determined locations.