Analytics

Because Scholar has no documents or files, we can do deep analytics on the life of communities and the work of scholars. These analytics are not about surveillance—their focus is on formative evaluation, offering learners and creators constructive feedback that contributes to their final work. Knowledge making and learning are essentially social processes, and Scholar facilitates this, making organizational simplicity out of social complexity.

Scholar has three main measures of knowledge: Know! or the quality of the knowledge work; Focus! or the effort contributed; and Help! or community contributions. Scholar represents a new generation of “learning analytics” destined, we believe, to replace traditional tests (retrospective and judgmental) with embedded formative assessments (prospective and constructive). The measures of knowledge have not changed, just our orientations to them.

We have developed these ideas elsewhere in our e-Learning Ecologies book, our Coursera MOOC, and our writings on "big data."


Analytics Features:

  • Data mining hundreds or thousands of datapoints in the development of a work in a project and the life of a knowledge community.
  • A progress synthesis is presented as a learner or a community member moves towards performance expectations (topic mastery in learning, or scholarly publishing standards).
  • Help credits acknowledge community contributions (and we have it in our development agenda to make these tradable, for a time when a contributor may themselves need help).