Academic analytics resources from Educause

Educause (http://www.educause.edu/ ) is a strong source of material relating to the use of ‘academic analytics’ to support student success, which is available from their Academic Analytics page http://www.educause.edu/Resources/Browse/Academic%20Analytics/16930
What Educause calls academic analytics is very similar to what we are calling activity data, with emphasis on the tools, presentation and use. ‘Academic Analytics: The Uses of Management Information and Technology in Higher Education’ (below) locates academic analytics at “the intersection of technology, information, management culture, and the application of information to manage the academic enterprise.”
Here we highlight five resources.
Seven Things You Should Know About Analytics
http://net.educause.edu/ir/library/pdf/ELI7059.pdf
Educause produces a series of ‘7 Things’ reports. These are very brief and include a story / case study, definition and some of the key issues. They can be very useful introduction to those who do not already know about what you are doing, and come from an independent authoritative source.
2011 Horizon Report
http://www.educause.edu/Resources/2011HorizonReport/223122
The Educause Horizon report is produced annually and looks at technologies that are going to have an impact over the next year, two to three years and four to five years. Of course, not all the candidate technologies make it from important in four to five years to important now.
The report is part based on survey and part expert discussion and provides a very broad brush overview of the technology. The 2011 report picked out Learning Analytics for the four to five year time frame (pp28- 30). It provides a two page overview and some examples and further reading.
Signals: Applying Academic Analytics
http://www.educause.edu/EDUCAUSE+Quarterly/EDUCAUSEQuarterlyMagazineVolum/SignalsApplyingAcademicAnalyti/199385 or http://bit.ly/c5Z5Zu
This is a fascinating case study from Purdue University, indicating that the use of analytics has improved results, and led those in greatest danger of failing to switch courses earlier. They ran the trial using a control group (although they don't say how the outcome compares with the control group) and courses were sufficiently large for the results to be meaningful. Here is an extract:
“Over the succeeding weeks, 55% of the students in the red category moved into the moderate risk group (in this case, represented by a C), 24.4% actually moved from the red to the green group (in this case, an A or B), and 10.6% of the students initially placed in the red group remained there. In the yellow group, 69% rose to the green level, while 31% stayed in the yellow group”
Academic Analytics: The Uses of Management Information and Technology in Higher Education
http://www.educause.edu/ers0508
This book discusses analytics in HE and whilst dated 2005 it is still of interest. Among the things to note is the sources of data people were using in their analytics (N = 213). Note that there is no mention of Library systems of any type and the strong emphasis on administrative systems rather than academic systems.
Source
Percentage
Student information system
93.0%
Financial system
84.5%
Admissions
77.5%
HR system
73.7%
Advancement
36.2%
Course management system
29.5%
Ancillary systems (e.g., housing)
28.2%
Grants management
27.7%
Department-/school-specific system
22.5%
Comparative peer data
20.2%
Feeder institutions (high schools)
9.4%
How the ICCOC Uses Analytics to Increase Student Success
http://www.educause.edu/EDUCAUSE+Quarterly/EDUCAUSEQuarterlyMagazineVolum/HowtheICCOCUsesAnalyticstoIncr/219112
This Case Study reports on the use of analytics to improve student retention, raising it from 77% to 85%. However, it is not clear is how much of the improvement relates to the analytics and how much derives from other work to improve student success.