Of That

Brandt Redd on Education, Technology, Energy, and Trust

26 September 2011

We Need an Energy Breakthrough

I haven't yet read The Quest by Daniel Yergin -- only this review. But it's nice to know that someone who has spent a career studying energy issues agrees with my conclusions. We need a breakthrough in energy technology. The environmental burden caused by fossil fuels is too great for us to rely on that source as we try to elevate the standard of living for the world's populations.

16 September 2011

Tackling Bloom's 2 Sigma Problem

Recently I wrote about the tyranny of the bell curve. Benjamin Bloom was working on this problem back in the 1980s. As an experiment, he and some of his grad students combined Mastery Learning with 1:1 tutoring. They discovered that average students in the program performed two standard deviations (two sigmas) better than their peers receiving conventional instruction. Using on John Hattie's scales from Visible Learning I equate that to more than four times the rate of learning.

In a seminal paper on the subject, Bloom wrote that that 1:1 tutoring is "too costly for most societies to bear on a large scale" and reported on their efforts to find more scalable solutions. This has become known as Bloom's 2 Sigma Problem.

Like many others working on education technology, I believe that Bloom's 2 Sigma results can be achieved and even surpassed by appropriate use of computer technology. From a number of initiatives, we're getting results that confirm this belief. While approaches vary, they have common elements:

Mastery Learning: That's what Bloom called it. Other terms are Competency Based Pathways and Proficiency Based Learning. There are nuanced differences but the basic premise is that students don't advance until they have demonstrated competency in the current topic.

Asynchronous Learning: Students advance from topic to topic independently. To do mastery learning properly, this is a requirement. However, it doesn't mean that there aren't sync points. For example OLI Courses support students spending variable amounts of time (according to their skills and background) learning the basic material. This way they arrive in class equally prepared for the live debates that are so critical to teaching certain subjects. Some classes resync every Friday with those students who are ahead assisting those who are taking more time. Results from the Khan Academy and School of One are showing us that individual students aren't consistently fast or slow. The slow and fast students trade places from day to day or week to week and overall variability tends to balance out.

Emphasis on Principles more than Facts: A student who has command of the underlying principles of a subject can often derive the facts. And in today's world, memorizing facts is of diminishing importance. It's too easy to look them up.

Strategic Intervention: The teacher is more important than ever. After all, learning is fundamentally a human-to-human process. Deploying online curricula in such a way that supports independent work frees teachers to spend more time one-on-one with students. They are enabled to focus on things only teachers can do: diagnosing misunderstanding, demonstrating the value of the subject, motivating and rewarding achievement and developing a personal relationship with each student. Paradoxically, technology has potential humanize the classroom. In a very important TED talk, Salman Khan says that we should move from measuring the student to teacher ratio to measuring the "student to valuable human time with the teacher ratio." (Quote is at 14:30 but watch the whole thing.) Teacher Dashboards are an important mechanism for informing teachers about where they need to apply their skills.

Posts in this series:
Breaking the Tyranny of the Bell Curve
Tackling Bloom's Two Sigma Problem
The Personalized Learning Model

14 September 2011

A Four Layer Framework for Data Standards

Recently I've been getting involved in a number of education data efforts. It's an alphabet soup of standards and specifications including CEDS, LRMI, SIF, PESC, Ed-Fi and more. As we've discussed these specs and how they fit together we developed a four-layer framework for how different data standards fit together. Our one-page outline of the framework has been used in ways we didn't foresee. I recently updated it with feedback from the CEDS team. Click here for the latest version. It's released under a CC0 license which pretty much means do what you want with it but don't blame me if something goes wrong. And see below for a graphic version.

12 September 2011

Breaking the Tyranny of the Bell Curve

If you take a random set of students, teach them all the same way and then give them all the same standardized assessment the results will follow a normal distribution or "bell curve" with a few excelling, the majority performing near average and a few failing. This is the tyranny of the bell curve.

There are all kinds of problems with this: Standardized tests result in normal distributions of scores because they are designed to do so. Not necessarily because human ability really follows a normal distribution. Indeed, human intelligence is malleable.

But let's set that aside for a moment and just go crazy theoretical. Suppose you had a large population of identical students. Then you put them in classrooms where instruction was delivered in identical ways. Then you gave them an identical assessment. The results would approximate a normal (or bell) curve. Why? Because a normal curve is what results when you average out a bunch of random errors. Instruction is naturally error prone. Students don't always pay attention. Even when they do, they don't always understand. Teachers make mistakes. People get sick or have bad days.

My colleague, Josh Jarrett, is fond of saying that high school graduates' knowledge is kind of like Swiss cheese with random holes in their understanding.

When looking at children, my natural inclination is to celebrate their differences. When they are dressed the same, in sports uniforms for example, I gravitate to the differences the color of their hair and their eyes, how they smile, who they cluster around, what grabs their interest.

Despite this diversity, our society needs all children to reach a certain standard of competency in core subjects of literacy and mathematics. Likewise, they need to have a basic understanding of the social and civic institutions and norms that are essential to prosperous society.
So, the challenge is achieving consistent results (academic achievement) while prizing the inconsistency of the inputs (our children). The obvious answer is that we adapt the education to the needs of each student. As a friend put it, "Every student should have an IEP."

But IEPs or Personalized Learning, as we prefer to call it, is prohibitively expensive, right? I believe that the principles of mass customization so successfully applied in other industries can also be applied to education. I'll be writing more on this in coming weeks.

Posts in this series:
Breaking the Tyranny of the Bell Curve
Tackling Bloom's Two Sigma Problem
The Personalized Learning Model

01 September 2011

Windows in Time

Last January we had to buy a new car for my wife. About five years ago I installed a bluetooth handsfree phone box in her previous car. We liked it so well that now we have them in all of our cars. Yes, I know that even handsfree phone conversations still distract drivers. But it still helps.

So, I had to decide what to put in the new car. These days car stereos often include phone capabilities so I thought that maybe we would upgrade the stereo too. And, wouldn’t it be nice if the stereo could play MP3s. Maybe GPS/nav capabilities would be good. One thing led to another and the unit we chose supports acronym city: MP3, WMA, CD, DVD, MP3, SD, USB, GPS, HD Radio. We’re in geek heaven. (Not a paid endorsement.)

Being new to Seattle, we’ve found the navigation feature to be really valuable. And, in case you’re wondering, It’s much more convenient to have it built-in than to stick a portable to the windshield. So, in the last six months I’ve done a lot of driving in which I followed the instructions of a computer voice.

It’s really a strange window in time. The car is smart enough to tell me where to turn, but not smart enough to make the turn itself. In his book, Evil Plans, Hugh MacLeod suggests that Television occupies another window in time, “a historical accident of the old factory-worker age meeting the modern mass-media age.” That people would willingly spend so much time with “passive, non-interactive media” is a temporary artifact.

What other "time windows" might we be in?