Data frameworks are an extension to Realizeit to allow the collection and analysis of data in the system. They provide opportunities to gather data from learners at various points throughout a course. They can either be deployed on a learning node or be triggered by a learner doing something in the system – for example, opening a course, completing a lesson, or answering a question. This flexibility allows clients to enable surveys in a huge variety of scenarios. 

The purpose of this document is to introduce Realizeit customers to the feature, and to outline use cases that can be employed or adapted by customers to create their own data frameworks. 

Examples and use cases 

  • An institution might want to run a survey at the end of a course to gather information about user satisfaction. Data frameworks can be used to present questions to be asked on completion of the course. 
  • An institution might be interested in collecting affective data about the learner, for example how they are feeling at particular points in the learning process. 
  • Realizeit may apply data gathered using data frameworks to influence the learner profile; for example, to find out whether learners self-regulate their learning, and what techniques they use to do so. 

It is important to note that responses to data frameworks do not contribute to the evidence about the learner’s ability; data frameworks exist in parallel to learning. They may be used to investigate learner attitudes, or how the learner works, but they do not impact the system’s beliefs about how much the learner has learned.