Learning Analytics – Afternoon (post 2 of 2)
January 13, 2012 by Sheryl Barnes
Malcom Brown:
3 Waves:
1- LMS
2- social media
3-analytics
We like analytics because they tell stories, help us make decisions, reassure us (sometimes falsely so),
What is it? Analysis of data, presentation of info, decision support.
New things-the amount of data available, breadcrumbs & social media, analyzability.
$64k question is how do we know what good or good enough analysis is.
Characteristics:
- uses data (esp learner generated info)
- performs analysis
- discovers info
- enables intervention
- Social Networks Adapting Pedagogical Practice (SNAPP) (UOW), connectivity between students as proxy for engagement
- Signals, Purdue (traffic light metaphor)
- U of Saskatchewan, lecture capture system & analysis
- UMBC Check My Activity
- Open University, blooms taxonomy, using Mercer’s work on dialog types.
First week of course engagement is strong predictor of student performance.
(sooner, scalable, actionable info)
(analytics can engage some faculty in analysis in ways they are not engaged with more traditional methods.)
Team sport, engines extracting meaning from unstructured content, rubrics, privacy (need collective campus discussion).
Herding cats, arts of intervention (ie what do you do once you have this info), caution-this will not necessarily be cheaper.
Potential to help us make better decisions faster.
Tinyurl.com…. White paper
ELI 2012, online focus session april 11 & 12.
