LAK2013

Kicked off my reading with Simon's briefing on Learning Analytics. An excellent summary of the high-level concepts and potential use cases of LA, as well as notes on the aspects of LA that still require further debate. #LAK13

This article really has me jumping up and down because I can see how it could be applied in a business / large enterprise setting. #LAK13

https://docs.google.com/drawings/d/1wEsOLyiSO364yKtRkhkSRoOiQIPBW7MZfwu_rJvpfek/edit?usp=sharing #LAK13

""We know where Nick's going, we know what Nick looks like," Urch explains, "now we want to try to predict where he may be in the future"

It occurred to me earlier that LA is a little like The Machine from the the TV series, Person of Interest ... this article has reinforced my view! LA is like a more benign machine: watching learners, analyzing what they're up to, what they might be struggling with, and perhaps able to offer some coaching or guidance to the learner. Like The Machine, LA has significant privacy considerations relating to the monitoring of users and the collection and storage of data relating to their activities. #LAK13

University of Phoenix are on the right track here. "In an effort ambitiously dubbed the "Learning Genome Project," the for-profit powerhouse says it is building a new learning management system (or LMS) that gets to know each of its 400,000 students [ed. now reduced to 360,000] personally and adapts to accommodate the idiosyncrasies of their 'learning DNA.'" Elliot Masie put it nicely last week in a webinar I was on - he said self-directed learning is like a sandwich bar where customers make their own sandwiches. It is up to us to provide them with great ingredients and then stand back and let them go for it. LA enables that sandwich bar to observe its customers, analyse their needs and dynamically adapt itself to help them make a better sandwich. Cool! #LAK13

Now I just want to see a distribution of this LMS for corporate use!! #LAK13

"we need to worry more about which models and which data have been chosen in the first place, why that process is successful when it is, and - most importantly - who gets to decide what data is collected and what models are trained."

Yes! Who's getting to ask the questions, make the decisions, choose the models, all important aspects that don't often get discussed. Who isn't part of the dialogue and which questions aren't getting asked? Which data isn't being gathered? Thanks for emphasizing this.

:), I'm reading this book at the moment.