10 June 2016 | haikara team In order to establish a level of granularity of learning for MyLK’s tracking we have decided to focus on learning episodes. A learning episode is a set of one or more periods of time during which a learner is engaged in learning. It can have a larger or smaller granularity: one greater learning episode may comprise several lesser learning episodes e.g., a MOOC may have a designed structure and outcomes, a playlist on YouTube, a video , etc. A learning episode is defined by the combination of the identity of the learner, and either or both of the learning outcomes identified, and the period or periods of time spent learning. For best definition, all three will be specified. A future learning episode may not have firmly fixed dates and times. A past learning episode may not have the learning outcomes fully defined. Learning episodes range from formal experiences, as arranged and managed by a learning institution, as in a course of study leading to a qualification; to informal experiences documented and identified by a learner as having intended or actual learning outcomes. A continuous learning episode is a single experience with no interruption. Examples of continuous learning episodes would be a lesson, a lecture, an experiment, a training session, or one session of a game. A composite learning episode is a set of learning episodes where the learning outcomes are related, whether by intention or by accident. Examples of composite learning episodes would be a course of study, a project, the creation of a creative work, a period of employment. For a composite learning episode to exist, there must be some reason to believe that the learning outcomes of the constituent learning episodes are related. There could potentially be other aspects of relationship between the constituent episodes.