A system for progressing learners through a plurality of electronic learning resources of an e-learning platform to effect mastery of one or more skills of a skill set, the system comprising:
- at least one non-volatile computer readable medium configured to store the plurality of electronic learning resources, each respective electronic learning resource having at least one logical skill-item connection of a plurality of logical skill-item connections accessible by processing circuitry, each logical skill-item connection of the at least one logical skill-item connection connecting the respective electronic learning resource to a corresponding skill of a plurality of skills, wherein
- the plurality of skills are logically arranged in a skills hierarchy comprising a plurality of skill families, each respective skill family comprising logical connections forming descendant and ancestor relationships between a respective set of skills of the plurality of skills belonging to the respective skill family,
- each logical skill-item connection of at least a portion of the plurality of logical skill-item connections is associated with a skill-item weight of a plurality of skill-item weights, the skill-item weight representing a relative impact of skill development in the corresponding skill imparted through interactions with the respective electronic learning resource, and
- at least a portion of the plurality of electronic learning resources are each logically connected to two or more skills of the plurality of skills, wherein
- each set of logical skill-item connections of the plurality of logical skill-item connections connecting a respective two or more skills of the plurality of skills to a same electronic learning resource of the plurality of electronic learning resources is associated with at least one skill-item strength of a plurality of skill-item strengths representing a relative relevance of each skill of the respective two or more skills;
- and
- the processing circuitry, configured to perform operations comprising
- automatically evaluating a plurality of interactions produced by a given learner of a plurality of learners engaging with a given electronic learning resource of the plurality of electronic learning resources, wherein
- the evaluating comprises assessing progress of the given learner in one or more skill families of the plurality of skill families according to each logical skill-item connection of the at least one logical skill-item connection connecting the given electronic learning resource to the corresponding skill of the plurality of skills, wherein
- each interaction of the plurality of interactions corresponds to at least one skill family of the plurality of skill families,
- the evaluating comprises applying evaluation rules for the given electronic learning resource to the plurality of interactions, and
- the evaluating results in at least one skill assessment of a plurality of skill assessments of the given learner, each skill assessment of the at least one skill assessment corresponding to a respective skill family of the one or more skill families,
- determining a particular learner group of a plurality of learner groups applicable to the given learner,
- accessing, based on the particular learner group, a set of mastery assessment parameters, wherein the set of mastery assessment parameters is one of a plurality of sets of mastery assessment parameters, each set of the plurality of sets of mastery assessment parameters corresponding to a different learner group of the plurality of learner groups, wherein
- the set of mastery assessment parameters comprises at least a first mastery assessment parameter related to the plurality of skill-item weights and at least a second master assessment parameter related to the plurality of skill-item strengths,
- using the set of mastery assessment parameters, automatically analyzing a set of skill assessments of the plurality of skill assessments of the given learner corresponding to a given skill family of the at least one skill family to produce a mastery assessment corresponding to a skill area of the given skill family, wherein automatically analyzing comprises applying at least one machine learning algorithm to a time series of interactions of the given learner with one or more electronic learning resources of the plurality of electronic learning resources related to the given skill family, to produce a predicted evaluation outcome corresponding to the time series of interactions of the given learner, as at least a portion of the mastery assessment, wherein
- the at least one machine learning algorithm is trained by the processing circuitry to forecast mastery assessment outcomes for interactions with electronic learning resources of the plurality of electronic learning resources, using a plurality of sets of historic time series of interactions with a portion of the plurality of electronic learning resources, the interactions being related to a given skill family of the plurality of skill families, and each set belonging to a separate learner of the plurality of learners, and
- selecting, based at least in part on the mastery assessment and for strengthening the given learner's mastery of the skill area, the one or more electronic learning resources of the plurality of electronic learning resources, wherein
- each respective electronic learning resource of the one or more electronic learning resources is selected based in part on having a logical skill-item connection connecting the respective electronic learning resource to the given skill family.