Final keynote - Freeman Hrabowski

Why IT Matters: A President’s Perspective on Technology and Leadership
Freeman A. Hrabowski III - President, University of Maryland, Baltimore County

Rather than trying to write this up, I highly, highly recommend that you view it for real (I can't do it justice). There are undoubtly many reasons why Hrabowski has risen to be President of a university, many of which are on display here, but I think ABSOLUTELY that the main reason is demonstrated in how he deals with things going wrong in the middle of the presentation (36mins in)

Watch this!! ...if:

• you'd like to see a "less than typical" head of a university speech - start about 6mins in (or slide28) to get past the general Educause stuff
• you'd like to see what sort of presentation by a senior manager can get several thousand people to their feet for a standing ovation
• you are prepared to get through some very US-specific points to hear other interesting stuff
• you would like a masterclass in "how to deal with a presentation when things don't go your way" (36mins40secs in) - for info PeopleSoft is HR, CRM and student admin tool
• you like sentimental stories or just haven't had a good cry lately (49min30secs in)
• you are interested in how to influence senior managers to see your perspective - he talks IT but I think it transfers (Q&A session about 53 minutes in)
• you're curious how IT helps assholes (1hr,1min,45secs-ish in)
• you want to see how to close a session rather than leaving it just as Q&A fade out (1hr,2min,30secs in)

http://hosted.mediasite.com/hosted5/Viewer/?peid=60706773509a468985f07cd6e23b2609

Don't watch this...if you prefer cynical understatement to enthusiastic overstatement

Academic Analytics: Using Institutional Data to Improve Student Success

This was this morning's pre-conference workshop run by John Campbell and Kim Arnold from Pursue. The session was OK in many respects but sadly the basic premise was lost in translation. They did some very impressive statistical modelling to take a whole range of data sets to look for indicators of "at risk", identifying a particular model profile that was 80% successful in prediction "risk". They then applied this model (or a customised version of this model - more on this bit later) to a course weekly, giving students an early warning indicator (traffic lights) and using these to make interventions (email, sms, f2f) pointing them to additional support.

What was good - focus on actionable data, timeliness of interventions, proved (in their context) models were reasonably predictive, focus upon large first year modules.
What was more problematic - customised model for each course (ie module) - each one took approx 16hr per week, every week, in management, analysis and publication so 3 modules would be 1 FTE! (long-winded way of saying not scalable), not sure the very complex stats necessarily identified different students from those who might be identified through a couple of indicators (may be sledge-hammer to crack a nut), traffic lights - worked for them but I though yuck! likely to be very instrumental.

Their indicators were in 3 categories "educational prepareness" (another way of saying entry qualifications), "performance" (phase test results), "effort" (amount on time logged into VLE)
I'm gonna leave the last one for you to ponder cos most of you know my take on that sort of thing...except to say that they found it was the best predictive indicator of success, so my question would be thinking what we think and knowing what we know - how can that be?