Tutorial

Welcome!

This tutorial get you going quickly with Evidence Hubs. The examples are taken from the SoLAR Hub on learning analytics, but the principles are the same for all hubs. Note that there is a Test Hub you can play in if you want to experiment there without worrying about making mistakes or messing other people’s stuff up (of course everything you contribute to any Hub you can edit or delete).

Objectives

  1. Understand that the Evidence Hub is a collaborative knowledge-building (specifically evidence-building) web platform with analytics designed to provide information about users’ activity
  2. Experience the Hub by contributing a range of material via the main site and the browser bookmarklet, and explore the different visualizations of data
  3. Reflect on the Hub as a medium for learning, and in particular, the visual analytics it provides

Tools and technical setup

Any mainstream web browser with a broadband connection will work with the Evidence Hub. There is a network visualization which uses an applet requiring Java 7 (Mac reqts). It’s not a show-stopper if you can’t get this working so don’t worry too much, but you’ll miss out on an interactive, self-organising network view.

Since there are other analytics projects using other tools, we can’t all use the same forum in Canvas or it’ll get rather confusing. So if you like threaded forums, join the Evidence Hub Google Group, which has an RSS feed coming off it if you want to track it.

Alert! You are contributing to Hub open analytics…

Everything you do on a Hub is public, and all content is covered by the Creative Commons Attribution 2.0 UK: England & Wales license.

Evidence Hubs are also an experimental platform developed at the Open University’s Knowledge Media Institute, for researching new kinds of learning analytics. These are generated from users’ activity traces for each Hub as a whole [example], and for each user on their Hub homepage [example].

Moreover, on the SoLAR Hub, to benefit learning analytics research as widely as possible, the data will not be locked inside the Hub, but will be published following the course, in machine-processable form to enable further analysis using other tools. (Note: we’re only publishing an open dataset for this Evidence Hub). Check out the Hub’s conditions of use and privacy policy for details.

>>> Part 1