On May 9, 2013 I will have the pleasure of joining the crew at #Lrnchat for a session on the topic of learning analytics. You will find us on Twitter, Thursday, 8:30 pm ET/5:30 PT. Look for us at #lrnchat, follow along at @lrnchat.
#Lrnchat is a regularly scheduled event that takes place every Thursday evening. Participants using any number of tweeting tools (such as Tweetdeck and Tweedgrid) to keep track of the messages that fly around among the session participants. It is hosted and facilitated by a number of learning and development social media experts who shall remain nameless until I get their permission to drop their names. Questions get asked, responses get posted, conversations get started, friendships get launched. It's amazing how much one can pack into 140 characters!
The name of this particular post, in anticipation of tomorrow's #Lrnchat, comes from one of my favorite analytics parables. In March of 2009, the lead designer from Google resigned in protest to what he described as an engineering culture that was obsessed by numbers. Douglas Bowman offered his reasons for resigning in a blogpost entitled "Goodbye Google". In his explanation he gave the following examples of how data-obsessed Google had become:
"Yes, it’s true that a team at Google couldn’t decide between two blues, so they’re testing 41 shades between each blue to see which one performs better. I had a recent debate over whether a border should be 3, 4 or 5 pixels wide, and was asked to prove my case. I can’t operate in an environment like that. I’ve grown tired of debating such minuscule design decisions. There are more exciting design problems in this world to tackle."
In closing, he wrote that "I’ll miss working with the incredibly smart and talented people I got to know there. But I won’t miss a design philosophy that lives or dies strictly by the sword of data."
I remember being struck by that phrase as the perfect way to describe the double-edged benefits and risks that analytics bring to discussions of learning, achievement, progress, success. I offer this as something that each of us should keep in mind as we gravitate toward a greater use of enterprise data in our decision-making.
I know we will have 90 minutes to talk about this. In anticpation of the conversation can I just offer this observation - It helps to have an idea about the problem you are trying to solve before you dive into an analytics campaign. And once you DO know, you need to be prepared to respond. Problem identification, without taking action, is almost worse than not knowing at all.
Here are a few references that I hope you will find to be useful. Happy reading! See you on Twitter.
Background References
Goodbye, Google The blogpost written by designer Douglas Bowman when he resigned from Google in protest to the data culture around decisionmaking. http://stopdesign.com/archive/2009/03/20/goodbye-google.html
The Gawker story that picked up the story of event leading to Bowman’s resignation from Google http://gawker.com/5177144/googles-data-fetish-drives-away-its-top-designer
Articles I've written on learning analytics:
Recent tweets on Big Data –related topics by @edwsonoma
The Big Data Landscape http://bit.ly/12KXpvA
11 Big Data myths http://bit.ly/15CD26B
The Surprising Predictive Power of Analytics http://lnkd.in/M2VS9j
The Rising Costs Of Misunderstanding Big Data http://lnkd.in/fBGWVP
Ten things you need to know about Big Data http://tinyurl.com/cabxeam
What's the skillset of a talented #BigData Scientist? http://ow.ly/kNKw7
