SYSTEMS AND METHODS FOR LEARNER GROWTH TRACKING AND ASSESSMENTS

Systems and methods for conducting automated skills mastery assessments in an e-learning environment may include assessing learner engagements with learning resources to produce mastery assessments, using historic interaction data derived through the engagements to train machine learning algorithm(s) to forecast evaluation outcomes of engagements based on engagement patterns indicative of skill fading, imparting learning, initial level of mastery, and/or a difficulty of acquiring mastery, applying the learning algorithm(s) to historic user interactions with learning resources to produce predicted evaluation outcomes, and, based on any differences between predicted outcomes and actual outcomes, refining parameter(s) of a mastery assessment parameter set used in calculating the mastery assessments, where a portion of the parameters correspond to attribute(s) of connections between the learning resources and skills of a skill hierarchy. The connections may be represented by logical indicators of relationships defined between the learning resources and the skills.