The Bastardization of Bloom’s Two Sigma

The Bastardization of Bloom’s Two Sigma

Analytics, Learning
I'm really torn over this blog post.  One one hand, it can be an insightful commentary about how the goal of attaining benefits comparable to Bloom's two sigma findings has been a negative catalyst in the higher ed tech space.  On the other hand, it can be an AWESOME title for a Hollywood screenplay treatment.  "The Bastardization of Bloom's Two Sigma" is the story of an over the hill spy who comes out of retirement when he finds out the son he never knew he had has developed super powers as an adult.  The crafty old spy needs to work his magic to get his prodigy on the right track.  Starring Michael Douglas as Boris Von Bloom and Dustin Diamond (Screech from Saved by the Bell) as Charlie...the son who…
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Data Lessons From a Robotics Tournament

Analytics
I enjoy connecting events in my data & analytics work life with events in my non-work life.  There are often good lessons to be learned there. On the non-work side, I'm a huge fan of K-12 robotics programs. I was a coach of a FIRST Lego League robotics team for five years and now a mentor for a FIRST Robotics Competition team for the past two years. Non-humble brag -- the Chaparral High School Firebirds just qualified to go to the FRC World Championships in Houston! One aspect of the work the team has done this season has a direct crossover relationship with data. At FRC tournaments, there's a task called scouting.  While all of the different robots are competing on the field, your team needs to observe and rate…
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Blackboard + Caliper + AWS = LRS

Analytics, Architecture
No, this equation isn’t the foundation of the Grand Unified Theory.  It’s just a simple way of getting LMS activity data into a Learner Record Store where it can be analyzed.  Arizona State University is among institutions that are pushing the learning analytics envelope, and continuing down that path requires agility when it comes to accessing and analyzing data.  To address this agility, the Action Research Lab and the University Technology Office partnered to build a cloud-based LRS using the Amazon Web Services cloud platform.  The goal of this post is to illustrate the steps we took to get Blackboard LMS data loaded in to a cloud-based Amazon Redshift database. Blackboard has long since committed to the IMS Caliper standard, so extracting events from the LMS is easy.  Unfortunately, there…
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What Analytics Aren’t

Analytics
Analytics aren't a cure-all.  They don't solve your problems for you.  There isn't an instruction manual on how to properly use data.  Stop.  End of sentence. While you let that sink in, let's tangent into a fun piece of trivia.  There was a TV show in the early '80's called 'The Greatest American Hero', and its premise was about the lack of an instruction manual.  The main character gets a super power suit from aliens, but he loses the instructions.  Hijinks ensue as he tries to figure out his powers on the fly.  Anyway, the protagonist was a teacher named Ralph Hinckley.  Unfortunately for the show runners, halfway through the first season, John Hinckley Jr. tried to assassinate Ronald Reagan, so they immediately changed the TV character's name to Ralph Hanley.…
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Shapes

Analytics, Visualization
I think I'm the anti-Buzzfeed.  Instead of giving my blog post a title like "These 5 Shapes Can Predict Your Success in Life" or "The One Shape the IRS Doesn't Want You To Know About", I go with the most obscure and non-descript title I can..."Shapes".  That's why I'm not in Marketing.  On the bright side, though, there is a secondary meaning to the red, white, and blue 'shapes' logo at the top of the blog.  Read (or skip) to the end to find out what it is.  OK...on to the blog post. The meaning behind 'shapes' has to do with charts, visualizations, and storytelling.  If you've read my posts before, you know that I'm a bit of a data nerd.  My personal affinity/skillset around data is visualizations.  I enjoy…
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How Accurate is Your Model?

Analytics, Models
[caption id="attachment_1308" align="alignright" width="401"] https://pixabay.com/en/darts-dart-board-bull-s-eye-game-102919/[/caption] Since we deal with predictive models, one common question we get is "how accurate is your model"? First of all, I need to say that we LOVE to get that question. It signifies that the institution has some level of buy in -- that they aren't just taking our expertise on faith. Unlike the quality of brake pads, we don't want you to take our word for it. When responding to this question, though, there's a bit of a conundrum. On one hand, I want to give an answer. I hate evasive responses to questions, so I want to make sure I give a clear, concise response. On the other hand, there is a lot of nuance in the response. It depends on what the…
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Do You Want the Plumbing or the Sink?

Architecture
Here at Blue Canary, we've made a reference to being a 'Data Janitor' on more than one occasion.  There was this article/tweet from back in March: We've always called ourselves data janitors...great to see it highlighted. Thanks for the find, @johncwhitmer ! — Mike Sharkey (@mjshark) March 25, 2015 ...and also a mention on my last blog post about 'Free like kittens vs. free like beer'.  So, in the spirit of our somewhat self-deprecating janitorial duties, I figured I dedicate a whole blog post to it.  Here goes. The reference started out as a joke with a few of us in the company.  We would be working on a predictive model or some complex data analysis problem, and then read an article about how data scientists are the hot, up-and-coming,…
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Kittens vs. Beer

Analytics
[caption id="" align="alignright" width="342"] Credit: http://imgur.com/a/7ooe0[/caption] You've heard of the saying "it's free like kittens, not free like beer"?  I love it...it's a great way of telling someone that "free" may not be the kind of free they are thinking about.  In our role with higher ed data and analytics, we come across numerous ways of getting at data and analyzing the results to help improve student success.  One core concept that we keep coming back to is that nothing is free (free like beer, that is).  There are definitely ways of doing things more efficiently, but in the end, you have to pay the piper in some way (free like kittens). So, where does the kitten/beer schism come into play?  Turns out, there are many misconceptions about where the work is and…
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Don’t Hype Analytics

Analytics
What if you could know someone's GPA just by simply looking at their phone? That's the first line spoken in this Dartmouth College video about their StudentLife study.  The problem with that line is that it starts to look like hype.  Like marketing.  Like a Buzzfeed clickbait article (apologies to Buzzfeed...it appears they are trying to go legit...I'll say it looks more like a Clickhole article).  I wanted to write this post to do two things: Commend the Dartmouth team on the work they've been doing Warn them not to add to the mountains of hype surrounding analytics and predictive modeling in ed tech The description of the study is wonderful.  They say: StudentLife is the first study that uses passive and automatic sensing data from the phones of a…
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Regression vs. Machine Learning (ad infinitum)

Analytics, Models
I didn't invent statistics nor did I invent machine learning.  I'm not a published expert in either field.  However, I was on Jeopardy, so that's got to give me some street cred to be able to talk about the two techniques.  The discussion usually boils down to this -- regression is a more "pure" form of data analysis (where the causal relationship between the data and the outcomes are more clearly related) while machine learning is a more brute force approach to prediction (and other analyses).  I wanted to put my position out there and see what does or doesn't resonate with colleagues. There's a great Stack Exchange thread on this topic where many folks have chimed in with their take on the two approaches.  I've done a bit of…
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