These papers were basic introductions into the area and the use of analytics in academia. The Goldstein paper was from 2005, but gives a nice snapshot of where analytics where and possibly still now. The most important part of the paper was the introduction to the 5 stages of academic analytics (which was also covered in John Fritz's talk on Tuesday):
- Stage 1 - Extraction and reporting
- Stage 2 - Analysis and monitoring of operational performance
- Stage 3 - What-if Decision Support
- Stage 4 - Predictive modelling and simulation
- Stage 5 - Automatic triggers
Most organisation cluster around stages 1-3 and from John Fritz's poll during his presentation I think that most organisations are still at these stages.
Elias asks some good questions about the technology we are using. A question about the data captured on a LMS was brought up - is it good enough or should we consider a redesigned for learning analytics. This is probably going to become even more an issue and a challenge as a learners data gets more distributed with Personal Learning Environments (PLEs). How can we capture all this data and co-relate it together for the purposes of learning analytics (this was also a question brought up by George Siemens during John Fritz's presentation).
Two tools that I now need to go and have a look at from reading these papers is to look up CourseVis - a visualisation of web log data generated by WebCT and the Purdue University's Signals Project which gives real-time course progress in an intuitive format.
Okay with that done - I now need to start looking at what's going on in the forums!