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An update on Datapalooza at the U.S. Department of Education

Susan Ohanian - August 03, 2014

Although I posted information about the Datapalooza on January 11, 2013, I now offer an update, with more links to the actual presentations. Some have both text and video because I found the text first and then decided to leave it.

As I noted one and a half years ago, I torture myself by subscribing to the e-mail Daily Digest Bulletin from the U. S. Department of Education. At 6:12 p.m.. on Jan. 11, 2013, someone there sent a hot link to Datapalooza: Unleashing the Power of Open Data to Help Students, Parents, and Teachers, the brainchild of Homeroom, the official blog of the U. S. Department of Education.

Secretary of Education Arne Duncan. This Datapalooza took place at the White House, and look at who attended: 150 of America's entrepreneurs, software developers, education experts, and policy makers. They came together to show off their wares. The Big Sell at the US Department of Education.

According to the blogger, The gathering was a chance to celebrate new products, services, and apps--all built with freely available data from the government and other sources--that have the potential to help American students succeed and that empower students and their families to make informed educational decisions.

You can watch the Data-philes' YouTube 'sells' here. I was so alarmed by Jose Ferreira that I've included the text below. His past work experience includes Kaplan Inc, Goldman Sachs, and strategist for the John Kerry presidential campaign. And if 1/1000 people involved in education decision-making believe 1//10 of what he says is true, it's really really scary. In a super rapid-fire delivery he presents a lot of misinformation about how children learn, but, as we know, this doesn't matter in the ed biz promoted by the U. S. Department of Education.

Ferrira talks a lot about mathematics and about his company's connection with Pearson.

Grants awarded by the Bill and Melinda Gates Foundation TO: Pearson Education Foundation Date: February 2011 Purpose: to support the development of open access courses for 6th and 7th grade mathematics as well as 11th and 12th grade English language arts Amount: $2,999,047 See the Press Release About the Pearson-Knewton partnership. I like the part about the product "taking student forgetfulness into account." All done in the name of psychometrics.

Arne Duncan kicks the party off with his canned spiel: The quality of education so many of our children are receiving is desperately under par. . . .We need a game change. . . . Using data in a very different way may be the game-changer we need. . . .

Data as game-changer turned out to be the theme of his remarks. He closed with "Can this be the game-changer? Can this be the game-changer?" Duncan ties his Data Button to the "positive step" of so many states adopting the Common Core State (sic) Standards. All these outfits offer "individualized learning solutions for the education industry"--through data collection. Jonathan Harber, CEO, Pearson K-12 Technology spoke about data allowing schools to go from textbook learning to personalized learning. . . "dynamic, engaging content showing up in(a child's) pocket. . . " And so on and so on. Harber pointed out that "Pearson is the largest trustee of student data." (Pearson PowerSchool Student Information System) Are you reassured? Or scared out of your mind. Some of the open data material IS interesting and even useful. But consider why datapalooza is probably a good term for the whole deal: Urban Dictionary Palooza

1. an all-out crazy party; partying at one place with a ton of people like there's no tomorrow

2. The art of throwing a very drunken extravagant party with a plethora of friends. Whoever is throwing the palooza usually adds their name as a prefix to the word. Paloozas are usually held on Wednesday.

3. A crazy f_ _ _in party whose purpose is to re-release an individual back into the world of dating when their significant other dumps them, ending a long term relationship.

It turns out this U. S. Department of Education was following in the footsteps of a White House-sponsored Health Datapalooza and Energy Datapalooza. I'm waiting for the White House extravagant party where a plethora of concerned citizens talk about the dangers of the overweening government worship of data.

Complete list of speakers at the White House Education Datapalooza:

Todd Park, U.S. Chief Technology Officer

Arne Duncan, U.S. Secretary of Education

Ross Santy, Deputy Assistant Secretary, U.S. Department of Education

Brandon Busteed, Executive Director, Gallup Education, the people who poll 1,000 Americans every night. Presentation at Datapalooza. [Why it's on the Honda Motorcycle Videos Gallery, I don't know.]

Curt Allen and Mark Luetzelschwab, CEO and SVP, Agilix. I didn't find their Datapalooza remarks, but while looking found this headline: Agilix Labs Taps into Inbloom to Give Louisiana Course Choice Ready Access to Major Data. Wonder how that's working out.

Adam Wenchel, Chief Technology Officer, EverFi. Jeff Bezos' Bezos Expeditions is investor. Text of Datapalooza presentation. But Wenchel has since moved on to Govolution and then EndGame. Love these names! EverFi. EndGame.

Marina Martin was the first "Entrepreneur in Residence" at the U.S. Department of Education, appointed by Arne Duncan after he had eliminated the last teachers with classroom experience from the department.Marina Martin, Head, Education Data Initiative, U.S. Department of Education (first Entrepreneur-in-Residence at the US Department of Education and author of Business Efficiency for Dummies), Presentation at Datapalooza,

Robert Swiggum, Chief Information Officer, Georgia Department of Education ( Using Race to the Top funds to enable teachers to get five years worth of data on their students. Presentation at Datapalooza.

Shawn Bay, CEO, eScholar>/a>. Here's a Press release about participation in Datapalooza. And here's presentation at Datapalooza. Shane Green and Jenny Abramson, CEO and SVP, Personal. Presentation at Datapalooza. Richard Culatta, Deputy Director, Office of Educational Technology, U.S. Department of Education. Presentation at Datapalooza. "As we transfer from print to digital, we have lots of exciting opportunities. . . the problem is these resources are scattered. . . ." And if the Feds centralizing resources doesn't sent chills down your spine, what will? Katie Garrett, Utah Education Network. Presentation at Datapalooza. Jonathan Harber, CEO, Pearson K-12 Technology. Presentation at Datapalooza. Why is this man smirking so much? Eric William, Superintendent of York County Schools, Virginia (now at Loudoun County Public Schools). Presentation at Datapalooza. Sue Khim, CEO, Alltuition. Presentation at Datapalooza. Craig Carroll, CEO, Rezolve Group. Text of Datapalooza presentation. Video. Christina McIntyre, CEO, BecomeAlum.com ( Presentation at Datapalooza, shows how the tool she created is helping college students have more meaningful, more effective interactions with their college counselors.) Jim Shelton, Assistant Deputy Secretary, U.S. Department of Education. ( Presentation at Datapalooza). Jose Ferreira, CEO, Knewton. Presentation at Datapalooza presentation: Must watch! Available in text at YouTube. Text of Remarks (from YouTube) So the human race is about to enter a totally data mine existence and it's going to be really fun to watch. It's going to be one of those things where our grandkids are going to tell our kids I can't believe you grew up in a world like that just the way our kids complained that we went to record stores. When Tom Cruise walks through the mall in Minority Report and the ad beams right to his eyes and say "Hey Mr. Cruise you should you go on that Caribbean vacation you've been thinking about." I know some entrepreneurs who work on that technology right now. And I'm still waiting for the day when my refrigerators going to know when I'm running out of milk and it's ordered for me automatically on Fast Track. I think that day's coming in a few years it's not far off. The world in 30 years is going to be unrecognizably data mined. So what does that man for education? Well education happens to be today the world's most data minable industry by far and it's not even close. So maybe one day healthcare will be up there when they have little nanobots that are in your bloodstream that are doing real time analysis, but until then it's not close, education beats everything else hands down. So let's look at other big data industries. The really big data industries in the world right now are not surprisingly on the internet because that's where it's easy to grab the data and that's also where the congregation of talent that understands data. So well let's just look at it by the numbers because the name of the game is Data Per User. So one of the things that fake us out about data and education is education because it's so big, it's like the fourth biggest industry in the world that produces incredible quantity of data. But data that just produces one or two points per user per day is not really all that valuable to an individual user. It might be valuable to like a school district administrator, but maybe not even then. So let's just compare. Netflix and Amazon get in the ones of data points per user per day. All this delivered in 1 minute 33 seconds. Onward! Google and Facebook get in the tens of data points per user per day. So you do 10 minutes of messing around in Google you produce about a dozen data points for Google. Okay great. So Newton today gets five to ten million actionable data per student per day. Now we do that because we get people, if you can believe it, to tag every single sentence of their content so publishers, we have a large publishing partnership with Pearson, and they tag all their content. And we're in open standard so anyone can tag us. If you tag all your content and you do it down to the automatic concept level, down to the sentence, down to the clause, you unlock an incredible amount of trapped hidden data. (emphasis added) Why do you do that? Well if you use programmatic taxonomy models and item response theory and I think at the bottom, we haven't given that a name yet, what you figure out is everything in education is correlated to everything else down to the concept. Now this is where education's different from search and social networking. If someone tagged every single line, every single sentence of all the world's web pages for Google, or every single line of dialogue from Netflix, which no one's done, but even if they had they're not really a whole lot of interesting correlations there. Everything in education is correlated to everything else. Every single concept is correlated in a predictable way to everything else using psychometrics right. So if you do 10 minutes of work in Google you produce a dozen data points for Google. Because everything that we do is tagged at such a grandeur level if you do 10 minutes of work for Newton you cascade out lots and lots of other data, and here's why. When you took the SAT there might be 40 different concepts about equal auto triangles that are tested on all the SATs ever given in any one year. But you didn't get all 40 questions you got two questions on equal auto triangles because they figure if you're in the Top 14th percentile at those two questions, 13th percentile on this one and 15% on that one, if you're in the Top 14% percentile on those two questions in equal auto triangles the odds are 98% percentile chance that you're in the Top 14% percentile at every concept and equal auto triangles. And there's a 96% chance that you're in the Top 15% percentile about all triangle concepts, three, four five, 30%, 60%, 90%, asceles (sic),etc., etc. You did a little bit of work for Newton and we used just established signs of psychometrics to cascade out hundreds of other data. So we can produce incredible quantities of data per user per day. It's really, really hard to get that, but if you can get all that tagging done Ð and that's one of our tags is on Ð that's a small part of our overall taxonomy, that's just part of one course and we h have dozens of taxonomies, then you can do this. What you can do with the data if you actually do all that work is you can figure out exactly what students know and how well they know it. You can figure it out down to the percentile versus the rest of the population. So Knewton students today we have about 180,000 right now, by December it'll be 650,000, early next year it'll be in the millions and the next year it'll be closer to 10 million, and that's just through our Pearson partnership. (emphasis added_ So for every one of the students we can figure out within a few hours what they're strong at and what they're weak at, at the beginning of the course. So we can produce a unique syllabus for each student each day, literally unique. There's not enough time in the universe for any two students to have the same syllabus on any one day, that's how many there are. So it's optimized for each kid down to the atomic concept. (emphasis added) And then we can figure out things like well here's your homework tomorrow night, you're going to struggle with that homework or you're going to fail it, because concepts in that homework that we know you haven't mastered the previous concepts for that build up to that. Or there's concepts in that homework that [inaudible very highly concepts always have trouble with. So we know you're going to fail, we know it in advance and we can prevent it in advance. We go grab some content from somewhere else in the portfolio and going to seamlessly blend that into your homework tonight. So every kid gets a perfectly optimized textbook, except it's also video and other rich media dynamically generated in real time. And it also uses the combined data power of the entire network. So here's what I mean by that, like I said next year we'll have close to 10 million students, a few years from now we'll have a 100 million. A 100 million first shows up to learn something like rules of exponents or subject per agreement, whatever. We take the combined data problem all hundred million to figure out exactly how to teach every concept to each kid. So the 100 million first shows up to learn the rules of exponents, great let's go find a group of people who are psychometrically equivalent to that kid. They learn the same ways, they have the same learning style, they know the same stuff, because Newton can figure out things like you learn math best in the morning between 8:40 and 9:13 am. You learn science best in 42 minute bite sizes the 44 minute mark you click right [inaudible 05:47], you start missing questions you would normally get right. You learn social studies best with video clips or 22% video to 78% taxed (sic) or whatever your optimal cocktail. We can tell when we should return content to you for optimal retention. We literally know everything about what you know and how you learn best, everything because we have five orders of magnitude and more data about you than Google has. We literally have more data about our students than any company has about anybody else about anything, and it's not even close. That's why we can do all that stuff right. So then what we can do is take that profile the 100 million kids, next it'll be 10 million. We can go figure out okay whose exactly like that kid? Whose learning styles up and down the line are just the same? Who knew the same stuff at the same level of mastery when they had [inaudible 06:24]? Great. Statistically speaking it has to be the case that some 5% or 10% through shared bad luck did the absolute wrong thing for themselves without knowing it. They did questions that were too hard, that got discouraged, they bounced. They accessed text they should have gotten the video, whatever. It also has to be a fact or statistics that through pure blind luck, some Top 1% the absolute perfect thing for themselves without realizing it. And we go take the whole combined data power that network of millions, soon to be tens of millions, eventually it'll be hundreds of millions of people. And for every single concept that your child learns 2000 concepts in a particular semester along math course, for every single autonomic concept we take the combined data part, that vast network and use it to fund perfect plan forward for that kid for that concept. So that's what we do right now. Let me give you a couple of examples. This is one student. There's a few hundred learning clusters there, there's a few tens of thousands of autonomic learning objects there. That's one student's path, this is a real student in a US college right now. And you'll see that each student has a totally different path. Some students have short paths, some have long paths, in this particular course there were students who finished it in 14 days, there were students who finished it in two semesters. This is a course at ASU they had to change their semester structure to a modulate semester structure because we were suddenly telling them things like if you give this woman here the final right now she'll get an A, it's only 14 days into the course. I promise you she'll get an A. You can keep her in that seat if you want, and that's what we've always done now we don't have to. So let's show you this. This is a 150 student's one class and they kind of all look like fleas but that's all an individual learning path. Notice that some of them are going really fast, some of them are going really slow, and then they'll all kind of speed up when the test comes. It's kind of like organic and so those different color coded things are like concept clusters. Like some test obviously just happened, that's why they all started working. And you can look at some of those students and think boy that pure schmuck is really in a lot of trouble because they're going too slowly. So where we think we're going with this obviously it's in market right now. We're going to be in K-12 starting next year and it's an open platform anyone can plug it in and use it by APIs. And where we think we're going with the data side of it, which is the really fun stuff for today, is we think within a few years we'll be able to start predicting great performance. So teachers grade persistently year in andyear out, if that teacher grades consistently we can match up the student profiles down to the autonomic concept levels versus great performance. We can tell you you're on track to get a B- in this course right now. Either that or if your teacher gets totally inconstant we can't tell you that, but that's another problem. If your teacher grades consistently we can tell you what your grade's going to be based on what you know and how fast you're learning it. But if you do another 30 minutes a day for three days a week you can get it up to an A-. We can tell you things like that. We're really excited to correlate with other people's datasets by open API things like, something we've talked about as kind of a joke but it really should work, is like the food diary. You tell us what you had for breakfast every morning at the beginning of the semester, by the end of the semester we should be able to tell you what you had for breakfast because you always do better on the days you have scrambled eggs or whatever. And more importantly we should be able to tell you what you should have for breakfast. (emphasis added) So the power of data when you unlock millions of data points per user per day you can accomplish things that people aren't even conceiving of right now. But that world is coming we're trying to bring it to you and we're going to be an open system to allow anyone to just plug that data, take it out, and then plug it back in. Thanks very much. Delivered at a hectic page in 9 minutes, 40 seconds. Zac Katz, Chief of Staff, Federal Communications Commission. Editor-in-Chief of The Yale Law Journal Text of Datapalooza presentation Anthony Swei, COO, Education Superhighway. text of Datapalooza presentation. Video Swei has returned to the private sector. Sunny Lee, Mozilla Foundation Presentation at Datapalooza Jacey Wilkins, Manufacturing Institute Presentation at Datapalooza. "Human capital most important item on the balance sheet" for manufacturers. . . and then spiel about "shortage of qualified talent whey they look to hire." Karen Cator, Director, Office of Educational Technology, U.S. Department of Education presentation at Datapalooza.

— Susan Ohanian

blog

July 30, 2014

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