Here’s a new word for you: Learning Analytics (LA)
- According to Wikipedia, LA is “the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on learning.”
- According to EDUCAUSE’s Next Generation learning initiative, LA is “the use of data and models to predict student progress and performance, and the ability to act on that information.”
George Siemens explained that the EDUCAUSE definition is intended to work within the existing educational system, rather than to modify it, where his definition (=Wikipedia) has to do with using (data and analysis results gleaned from) LA to restructure the process of teaching, learning, and administration.
In George’s mind, LA is very much related to Web analysis, (educational) data mining and tools like Google Analytics.
LA begins by collecting data off-put by users (typically, data trails generated through mouse-clicks, click-through, recommender systems), and storing that data for drill-down analysis. The LA approaches try to make sense of learner activity (through attention/focus heat maps, social network analysis, and so on) and using the findings to take actions for curriculum mapping, personalization and adaptation, prediction, intervention, and competency determination. Put in another word, it involves some kinds of (learning) traits profiling, so that we can better understand the learners to affect their learning.
It is the same for Performance Trails. Except that in Performance Trails, the learning system in question is neither the existing education system, nor the Intelligent Learning Systems (ILS). It is the 3D virtual environments so commonly found in games and virtual worlds.
