Wednesday, December 3, 2014

Going Vertical with Differential Steering

In Teaching a Robot How to Dance, an introductory computer science course for high school students, we ask students to program a robot to dance to unknown music and with an unknown robot dance partner. To do this, the robot has to be able to track its dance partner and move accordingly. One of the sub-tasks that we ask students to complete while developing this dance behavior is to first figure out how to program their robot to track and simply follow an infrared (IR) beacon.

The robot in Teaching a Robot How to Dance uses differential steering. It has two wheels, one on the left and the other on the right. To move forward, you program the two wheels to rotate at the same velocity. To turn to the right, you program the left wheel to rotate at a greater velocity than the right wheel. In this video, Daniel (the instructor) explains how the drive system on the robot works:

And in this video, Amalia and Ariana (the two high school students) figure out how to use the drive system to turn the robot to the right:

Altogether, it takes less than a minute for Amalia and Ariana to understand differential steering well enough to complete the task of programming a robot to track and follow an IR beacon. By the end of the session, they are comfortably adjusting wheel velocities as they improve their design.

When we first started working on Teaching a Robot How to Dance, we had a number of discussions about how the students would drive the robot. In most introductory robotics courses, students program the robot to “move forward” or “turn right,” where “turn right” is a pre-programmed subroutine that turns the robot in place 90˚ clockwise. When Daniel worked at iRobot, they developed an application programming interface (API) for driving the Roomba using subroutines that drove the Roomba in arcs.

An API is helpful because it is much easier to think in terms of angles and distances when driving a robot than left and right wheel velocities. But for Teaching a Robot How to Dance, we wanted to stress that the robot is essentially sensors and actuators, with behaviors linking those sensors and actuators. In this case, the wheels on the robot are the actuators, and we did not want to abstract that away.

Once we agreed that students would drive the robot by setting left and right wheel velocities, we started to discuss how to build differential steering into the curriculum. I did not want to spend a couple of days focused on differential steering, asking students to just drive their robots around. Since this was a project-based course, I wanted to dump the students into the deep end and have them start working on complex behaviors, such as follow-the-leader, right away. I felt that differential steering was something that students could learn just-in-time as needed.

Now, Amalia and Ariana only scratched the surface of differential steering. Their robot might be rolling forward at 200 mm/s when it suddenly needs to turn to the right. When that happens, the left wheel continues moving forward at 200 mm/s, but the right wheel is thrown abruptly into reverse, moving at -200 mm/s. The robot basically comes to a full stop in order to turn in place… and the transition between moving forward and turning can easily happen dozens of times a second. That might be acceptable for follow-the-leader behavior, but it doesn’t look very smooth for a dance partner.

At some point, students are going to want to program smoother and more complex movements into their dance steps, and they aren’t going to want to do it by setting wheel velocities. When that happens, the students will begin designing their own API for driving the robot, and the design of that API will be informed by the kind of movements they want their robot to do.

Imagine that we want our robot to have a dance step where it spins 360˚ in place. If that spin move happens in four beats, it needs to be programmed so that the speed of the robot adapts to the tempo of the music. If our robot’s dance partner moves away in the middle of the spin, our robot may want to drift slowly in the same direction while spinning instead of spinning in place. And if the dance partner gets too far away, our robot may want to break out of the spin after one, two, or three beats, and transition to a different dance move that will close the gap between it and its dance partner a little faster.

By the end of the course, the drive system of the robot would consist of multiple layers of software and hardware, and we wanted the students to design as many of those layers as possible. Sitting above the wheels, there would be an API for setting wheel velocities that we would provide. Sitting on top of that, there would be an API for driving the robot that would be designed by the student. This basic driving API would then be used by the student to program the robot with a repertoire of dance steps, and the design of the API would be informed by the kind of dance steps the student wanted to implement, and it would be redesigned as needed. Each dance step would share a common interface so that the robot could select and use dance steps interchangeably, and there would be a layer for choosing which dance steps to take. Ultimately, there could even be layers for learning which dance steps are better for a given piece of dance music or dance partner, or for tweaking parameters in the dance steps. Sitting below the wheel velocity API, there could be a layer for dealing with wheel slippage. If the wheels are set to rotate at 200 mm/s but they are slipping on the dance floor, the robot’s dance steps might be thrown off.

A key feature of Teaching a Robot How to Dance is that students are constructing and then climbing up and down their own abstraction ladders. You don’t want to have to think in terms of wheel velocities when designing dance steps, so you build an abstraction layer on top of that. You don’t want to have to think about custom interfaces for each dance step, so you modularize them and add another abstraction layer. The more well-designed the abstraction layer, the easier it is to build on top of it and make your own life easier. Are you running into some unexpected behavior in an edge case? You may want to drill down to a lower abstraction layer to see what is really happening. This design encourages students to apply and appreciate computational thinking.

Differential steering represents a tiny fraction of the content in Teaching a Robot How to Dance, but we had to make dozens of design decisions on how to implement it in the course. The decisions we made are highly case-specific; we would have designed things differently if we were implementing differential steering in a different context. But constructing and then climbing abstraction ladders is something that I am passionate about, and it is part of what I mean when I talk about vertical learning. This is something that all kids (and adults) can and should be doing.

Tuesday, December 2, 2014

Teaching a Robot How to Dance: A Case Study

In 2011, I began working with a small team to develop an introductory computer science course for high school students with little prior experience or interest in technology. Daniel and Tim were experts in robotics and software engineering who had come together to design a marine robotics course at M.I.T., and Lee was a professor teaching computer science and doing research in computational biology.

When I joined the group, I suggested that we engage in a backward design process and start by articulating the objectives of the course. While we shared a common desire to encourage more students to pursue careers in STEM, we were all coming at the problem from different directions and operating with different assumptions. To get on the same page as a group, we had to clarify our own thinking as individuals.

We agreed that the focus of the course should be on computational thinking. We wanted students to develop a conceptual foundation and habits of mind that would enable them to apply advanced computation in any field. Daniel and Tim wanted the course to involve robotics, but they didn’t want to focus on mechanical design and programming. They wanted students to experience robotics as a rich and engaging problem space driven by the interaction of hardware, software, and the environment. Finally, it was important for students to drill down to some form of ground truth when engaging in the engineering design process; we wanted them to have to consider and eventually learn about underlying mechanisms: what happens when the wheels in the differential drive system slip, the charge in the battery gets low, or you are limited by the sampling frequency of the sensor data and behavior arbitration system?

Designing a task aligned with our objectives took discipline. We needed a project where students would have to meet our objectives in order to complete the task. It would have been simpler and faster to design a fun and engaging task, and then layer our objectives on top of it, but it also would have been far less effective. After a great deal of thought and brainstorming, we came up with the idea of teaching a robot how to dance. Teaching a robot how to dance isn’t the same as programming a robot to follow a pre-scripted choreography to music. Students needed to figure out how to teach a robot to dance to unknown music and with an unknown robot dance partner, which means detecting the tempo of the music and the position and movement of the robot dance partner, and reacting appropriately. It is the kind of rich, complex problem that would engage and challenge an expert roboticist.

Once the task was defined, I began designing the course, breaking the task into sub-tasks and creating sequences of lessons to develop skills and concepts. I introduced the group to Moodle, a learning management system (LMS). We planned to deliver the course using face-to-face instruction, but we wanted to post assignments and materials online. I also often use threaded discussions to increase accountability, enable students who like to process their thoughts longer or need more wait time to participate more actively, and make it easier to follow up and build on earlier points in the discussion.

The group was impressed with how I developed skills and concepts in a logical and cohesive progression, but they had concerns that students would be unable to progress at the rate that I anticipated. Even though we had agreed that the course would be project-based with a constructivist approach, there was some desire to pull back and spend more time constructing foundational skills before getting to the heart of the project. We decided to test components of the course with small groups of high school students to see how they responded.

We challenged students to program a robot to track and follow an infrared (IR) beacon, which is one of the critical sub-tasks in Teaching a Robot How to Dance. We recorded the second session, and I documented it through a series of videos on the Computing Explorations website. (I also posted a short introductory video on YouTube.) Initially, the two students in the session, Amalia and Ariana, spend more time trying to get through questions than answering them. But later, they begin reasoning things out and using the tools and strategies modeled by Daniel, their guide and instructor. By the end, as their capabilities and understanding have expanded, they are visibly more confident and engaged in the task, and they are even questioning and answering each other.

I enjoyed the development of Teaching a Robot How to Dance on multiple levels:

  • I had the opportunity to immerse myself in a new discipline and to view the world through the eyes of a roboticist.
  • Starting with a blank slate, I was able to take risks and push myself to design innovative curriculum based on constructivist learning principles.
  • We took the time to design a course that was cohesive and fully aligned with our objectives.
  • I learned about new technologies and was able to share what I knew about curriculum design and instruction.
  • By collaborating, we designed a course that none of us could have designed on our own, and we developed common understandings that will impact our thinking moving forward. We also built a level of trust that enabled us to uncover our own assumptions, take risks, and challenge core beliefs.

I believe that this is the kind of process that all educators should be going through in order to develop the curriculum and instruction our students need and deserve.

Wednesday, November 19, 2014

The Joys and Tribulations of Thinking Different

The Land of Zero Convergence: The Keystone XL Pipeline

I’ve been curious about the Keystone XL pipeline recently. Every once in a while, something is in the news and I realize that I don’t know as much about it as I should. This bugs me and I want to learn more.

However, once I started digging deeper, I realized that the Keystone XL pipeline lives in two worlds: a pro-pipeline world and an anti-pipeline world. Depending on your political leanings, one of those is the real world and the other is some bizarro world where logic has no meaning. Both worlds have their own set of facts, experts, and published reports backing them up, and there is little to no overlap.

Whenever there is a program on the Keystone XL pipeline with a panel of experts, the same arguments and disputed facts are trotted out again and again. Even if a point is eventually conceded by the panel after exhaustively examining and evaluating all of the evidence, that same point is magically un-conceded in future debates and we have to start over again from the beginning.

If you go to the Wikipedia article on the Keystone XL pipeline, it dispassionately documents both worlds without trying to find any ground truth. It lays out the events that have occurred and the statements made by both sides, while pointing out how every independent, third-party report has been “debunked” by one side or the other because the report’s authors have received funding from one group or expressed support for another group in the past. It tells you what has happened, but it doesn’t help you figure out what will happen if the pipeline is or isn’t built.

Toward a New Normal: Reframing the Discussion

Trying to formulate an opinion on the Keystone XL pipeline is next to impossible without a body of facts that represent the ground truth. You can embrace one of the existing ground truths (pro or anti), spend months sifting through primary sources to curate your own ground truth, or sit on the sidelines. I suspect that most sensible people choose the latter, and our political system is the worse for it.

A few years ago, I began to think about systems for driving discussions forward. I realized that there had to be mechanisms in place to reach consensus. I don’t seek consensus just to get along; I do it because we will never get to the heart of an issue if we can’t even agree on some basic facts. And agreeing to some basic facts may just give us the skills to create a more substantial meeting of the minds.

We start by identifying what we know and don’t know. How many jobs will be created during the construction phase of the pipeline? How many once the pipeline is operational? What would happen if there is an oil spill in the Ogallala Aquifer? What percentage of the oil passing through the pipeline will be used domestically versus sold overseas? How will the pipeline affect oil production and what will this do to oil prices? Where would the oil go if the pipeline isn’t built and where would we get our energy instead?

We would publicly debate each of these questions and hammer out an answer. Comments that are insightful, informative, clarifying, synthesize multiple comments, or pose thought-provoking questions would bubble up to the surface. When consensus has been reached on a specific point, debate on that point is locked and the discussion continues with that point established as a given. If someone wishes to re-open debate on a point that has been locked, that can happen on a side thread, but not in the main discussion. Over time, consensus is developed around a set of key points and the discussion moves into new territory. It’s fairly obvious that the debate over the Keystone XL pipeline is a proxy for more serious debates… debates that we aren’t equipped for right now. Is it sensible policy to keep oil prices high to encourage the development of renewable energy sources? What is the right balance between short-term economic growth and long-term environmental sustainability?

Who decides which comments bubble up to the surface, which questions are debated, and when consensus has been reached? The community does, but your level of input is based on karma/reputation points that you acquire for the quality of your participation. Ask thoughtful questions, help others synthesize opposing viewpoints into a coherent viewpoint, uncover your own assumptions, provide expertise, help someone express themselves more clearly by reflecting back what they are saying… and those comments will be highlighted and receive more discussion, and you will gain reputation points that enable you to have greater input in the community. Be rude to others and continue arguing points that are considered settled… and you can keep posting those comments but they will be buried for few to read.

Why This Is Important: Obamacare

This level of discussion is labor-intensive. Without constant curation from highly skilled facilitators, the feedback loop breaks down and the discussion stalls. In order for the model to scale, discussions need to advance far enough to generate more facilitators. It’s similar to compressing mass-energy to ignite a sustained nuclear fusion reaction. Is the effort worth it?

At some point, the debate on the Keystone XL pipeline will end when one side “wins,” but that kind of resolution comes at a cost:

  1. Resolving an issue only after it has grown into a crisis is costly and often results in sub-optimal solutions.
  2. Letting a winner emerge instead of hammering out a compromise that both sides can live with can also result in sub-optimal solutions.
  3. We never debate the underlying issues.
  4. Ideas that don’t conform to the two-sided debate are never considered.

When President Obama laid out his initial proposal for healthcare reform, he did something interesting. He framed it outside of the existing two-sided debate. Instead of focusing on universal healthcare and providing healthcare to the uninsured, he focused on the rising cost of healthcare, which is rising much faster than inflation. The cost of healthcare is a huge drag on the economy. Individuals and businesses have to spend a greater fraction of their income on healthcare. In that context, most individuals and business leaders would agree that controlling the rising cost of healthcare is a top priority, and one that virtually everyone agrees on.

Rising healthcare costs is a much bigger problem than social security. Most business leaders would happily raise the minimum wage if it meant healthcare costs could be reined in. But we aren’t discussing healthcare costs at all! Why is that?

The Democrats and the Republicans are so far apart and their best ideas (single-payer healthcare and health savings accounts, respectively) are so unpalatable to most Americans, that any real discussion is impossible at the moment. President Obama hoped to changed that with a radical new approach.

In certain regions of the country, Medicare was able to drive down costs and improve the quality of healthcare (as measured by patient outcomes) at the same time. Better care for less. There were small scale experiments with preventive care and how doctors were billed. President Obama wanted to unleash this creativity on a wider scale. Think of charter schools, but where charter schools are intended to compete with public schools, “charter” health insurance companies would compete with private health insurance companies. But who would sign up for a new and unproven kind of health insurance? Health insurance companies need large subscriber bases to negotiate costs down. The solution was to subsidize and provide this health insurance to nonconsumers: the uninsured.

Unfortunately, to Republicans, the creation and funding of these charter health insurance companies was simply a ploy by Big Government to expand Medicare and get into the health insurance business. They couldn’t see it as an attempt to create competition for health insurance companies and use market forces to hold down costs. When this happened, President Obama chose to retreat and that portion of the bill was gutted. The only thing that was left was subsidizing healthcare for the uninsured, which fit neatly into the existing narrative of Democrats trying to expand entitlement programs. The most interesting part of the bill, using competition to hold down healthcare costs, was never discussed. And frankly, I suspect that President Obama was right to back down: we lack the tools to think out-of-the-box and have any kind of real debate as a community.

Thinking Different: The Joys and Tribulations

I don’t know if President Obama’s approached would have worked. I’m skeptical, but I would have liked to have discussed it and for our collective brains to study it. That didn’t happen and isn’t happening in many other areas. President Obama thought differently, but he couldn’t get enough people to do the same.

I’ve thought differently my whole life. On one level, it is very cool and kind of fun to see solutions where everyone else sees a lost cause. But it can be disheartening and lonely, too. I’ve chosen education as my battleground. I see potential in us and I genuinely believe that we can have the kinds of discussion that I dream about… and that those discussions can make us understand others better and think more deeply. More importantly, I have tested those ideas and I have seen them work on small scales. Would I love to test these ideas on a larger scale? Yes! Would I love to have a circle of friends to hash out new ideas, people who would push and challenge me to understand and think deeper myself? Hell, yes! I guess this is me putting the call out… if this resonates with you, if you yearn for the things that I yearn for, drop a line and say hello. It’s awfully nice to meet you.

“There are those that look at things the way they are, and ask why? I dream of things that never were, and ask why not?”
—Robert F. Kennedy

Tuesday, November 4, 2014

Moving the World

A few weeks ago, I thought about writing an article on Apple Pay and posting it on one of the tech-site forums that I frequent. People were using the forums to discuss the merits of Apple Pay, but these discussions were filled with both missing information and actual misinformation. This made it difficult to draw any conclusions, and arguments ended up going in circles.

I hate when arguments go in circles and nothing ever gets settled. It happens in tech-site forums. It happens in education. It’s an incredible waste of energy that can stall forward progress. My plan was to write down what I thought I knew and then crowd-source anything that I had wrong or didn’t know. We would debate issues in the comments until we reached a level of consensus, and then I would update the original post with the new information.

When I shared this plan with my friend Daniel, he was less than enthusiastic. He asked me why I didn’t just research Apple Pay on my own and then post what I had learned. Why did I want to crowd-source the article?

This got me thinking. I wasn’t motivated by a desire to write a comprehensive and meticulously-researched article. I enjoy reading those articles, but not enough to research and write them on my own. I also wasn’t motivated by a desire to organize and harness a community effort to write a comprehensive and meticulously-researched article. I like the idea of sharing resources to build something together that would be difficult for any one person to build alone, but that level of sharing and community-building isn’t enough for me. No, I was motivated by a desire to transform individuals through the process of organizing and harnessing a community effort to write a comprehensive and meticulously-researched article.

Tech sites compete to improve along a specific trajectory. Their goal is to attract and retain eyeballs so that they can sell those eyeballs to advertisers. Some sites compete by writing well-researched articles. They attract and retain eyeballs by being authoritative and highly credible. Other sites compete by trying to be your one stop shop for all your tech news or the site with a community of like-minded readers. But either way, they measure success with the same metrics: How many readers do you have? How engaged/loyal are they?

Many tech sites would like to improve the quality of their comments and forums, but they can’t afford to do it unless it also attracts and retains eyeballs. Unfortunately, circular and never-ending arguments are a great way to fire people up and get them coming back for more. This is why many sites end up adopting clickbait headlines and goosing their readers to argue back and forth. It’s reached the point where many readers and tech-site editors just assume that any attempt to clean up comments and forums is a hopeless battle.

Why do people post comments on articles and in forums on tech sites? I think most people do it to connect with other people and win points for being clever. Being clever can mean being informative, but it can also mean the perfect put-down. Forums are fairly well-designed for these jobs, but some people would love to hire forums for other jobs: learning things, having thoughtful discussions, or pontificating. Since most tech-site forums aren’t well-designed for those jobs, those people end up as nonconsumers.

As a crowd-sourcing site, Wikipedia competes on a different set of metrics. It looks at the number of people who use it as a source of information and the number of active editors and contributors. I’ve read that Wikipedia has been struggling to attract and retain contributors. There have been complaints that a small group of longtime editors have been driving new contributors away. Unfortunately, that same small group of editors is the backbone of the site, so Wikipedia faces a serious dilemma. Do they try to make editing more inclusive and bring in fresh blood (but risk killing the site by losing their most active editors) or do they stay on course and hope that small tweaks will turn things around (but risk killing the site as the pool of contributors continues to slowly shrink over time)?

If I ever created a site to crowd-source articles, I would compete on an entirely different set of metrics: I’d measure the growth of my readers.

On a recent Apple Pay article, two readers were arguing back and forth. They exchanged over two dozen comments in an hour. A few other people tried to jump in, but they weren’t able to help. The first reader was wrong; he was basing his entire argument on a single misconception. Since you linked your credit card to Apple Pay inside of an Apple app, he assumed that Apple generated the token that is stored on your smartphone. What he didn’t realize is that Apple’s app establishes a direct connection to your specific bank, and the bank that issued your credit card generates the token, not Apple. It was an honest, and perfectly reasonable, mistake. The second reader was correct, but he never identified why the first reader was mistaken. Instead, he kept repeating his argument over and over again. He actually did explain that Apple did not generate the token, but there was so much cruft around that statement that the first reader couldn’t hear it. If the two of them could have identified the source of the token as the source of their disagreement, then they could have either resolved their disagreement then and there or at least parted company agreeing to research that one specific issue further. Instead, both of them parted company pissed off and convinced that they were right and the other was wrong.

Now, imagine if someone had jumped in and helped the two men identify the source of their disagreement. With a little research, they would have found a credible source explaining that the bank, and not Apple, issues the token. With consensus achieved, an editor would then add that information to the article so that other readers would not have to debate the same point. If this happens enough times, the first reader will learn not to be so sure of himself when he doesn’t actually know something, and that he can learn more by asking questions instead of arguing. In fact, if he asks enough questions, soon he’ll be the one helping the new guy out. Meanwhile, the second reader will learn that he can contribute more if he listens to people who are mistaken and can identify the source of their confusion. Instead of endless arguments, the forum provides an opportunity for growth.

My crowd-sourcing site is fundamentally different than Wikipedia because we compete on different metrics. At Wikipedia, people contribute to articles. When there is a disagreement, an editor comes in and makes a final decision. There is no attempt by the editor to help the contributors resolve their own conflicts. At my site, an editor is a mediator. They model how to resolve conflicts so that contributors can resolve more of their own conflicts, and many of those contributors will eventually begin mediating for others and become editors themselves. The debate has value; it’s not just a necessary step on the path to a well-sourced article.

Is there a business model for the kind of site I’m describing? I have no idea. I do know that there are nonconsumers who would love to hire the kind of website forum I’m describing. It’s also potentially disruptive because it changes the metric for performance. I also know that it is possible. I can envision it, even if I don’t know how large the market is. Imagine a site where people learned to resolve their differences, and then applied what they learned to other sites, to their face-to-face relationships, and then in the public arena. Instead of discussions about Apple Pay, we could grow to discuss global warming, universal healthcare, immigration, and sensible tax policy. Just imagine it. That’s the world in which I’d want to live.

Friday, October 31, 2014

Removing Our Blinders

When reading Disrupting Class, I detected four anomalies that might cause Christensen’s prediction that schooling will be disrupted by student-centric technologies in the form of computer-based learning to fail. The first anomaly is that the technology of public schooling is immature. Since schooling in this country is over two hundred years old and it has been steadily improving, that should not be the case. The second is that educational research is descriptive, but not predictive. Once researchers have described schools, they should automatically move to the next stage, which is to test and improve their models through predictions. That is not happening. Third, schooling may be improving, but instruction is not. According to Christensen, personal tutoring represents the state-of-the-art in student-centric instruction, but personal tutors today are no more effective than personal tutors twenty years ago. And to raise test scores and meet targets established by No Child Left Behind, schools are changing everything but instruction. Fourth, instead of studying outliers who may be doing something different to get extraordinary results, we assume they have a ‘secret sauce’ that cannot be codified and will not scale.

Just because these anomalies exist, it doesn’t mean that disruption won’t occur; it just means that disruption may have to proceed a little differently. It may be possible for schooling to continue improving without ever improving instruction. It may be that we are all playing a giant game of chicken, and once all other avenues have been exhausted and improving instruction is the only way forward, then we will improve instruction. But I’m skeptical. Personally, I believe that, to disrupt schooling, we need a disruptive innovation in the technology of instruction, and we won’t develop that innovation until we have identified and addressed the root cause that is causing these anomalies.

In earlier posts, I have postulated reasons why instruction may not be improving (core beliefs about what we can learn and getting stuck at local maxima). I don’t know if those are root causes or only additional symptoms of a deeper root cause, but for some reason, it is common in education to see what we believe to be true instead of what is happening right in front of us.

For example, many educators believe that the key to improving schooling is to motivate students by appealing to their interests. Christensen writes, “When there is high extrinsic motivation for someone to learn something, schools’ jobs are easier. They do not have to teach material in an intrinsically motivating way because simply offering the material is enough. Students will choose to master it because of the extrinsic pressure. When there is no extrinsic motivation, however, things become trickier. Schools need to create intrinsically engaging methods for learning.” Motivation is essential to learning. There is no question about that. But is motivation on its own enough? Sometimes I think that people fixate on motivation because it allows them to not think about the other components in learning.

Christensen writes: “We believe that a core reason why so many students languish unmotivated in school or don’t come to class at all is that education isn’t a job that they are trying to do. Education is something they might choose to hire to do the job—but it isn’t the job. While we continue our research to understand this crucial issue, we hypothesize that there are two core jobs that most students try to do every day: They want to feel successful and make progress, and they want to have fun with friends.” “Furthermore, when we use the phrase ‘want to feel successful,’ we do not mean the kind of surface-level idea of success that constitutes praising a child no matter how she performed on a given activity under the mistaken idea that building ‘self-esteem’ in this vein is a good idea. Instead we mean true success, where the student in fact accomplishes and achieves something real and makes progress.” If you listen to and work closely with children, you will know that this is exactly right.

Imagine that you have a medical issue, but your doctor doesn’t listen to you and appears to be utterly incompetent. To get what you need, you end up scouring the internet for information, performing your own diagnosis, and essentially telling the doctor which treatment you’d like to be prescribed. This may be better than nothing, but if you were paying for these doctor visits out of pocket, you’d be very angry and very unhappy. You hire the doctor to guide you as a medical expert, not to function as an expensive prescription pad and referrer. Students don’t hire schools to purse their own interests and engage in pastimes. Schooling is way too expensive for that. We can do that in our own time and there are other activities that can do that job much better than schooling can. We hire schools to help us be successful and to prepare us for the future, and we expect schools to have some expertise in those areas and to give us expert guidance. Students may settle for pursuing interests in school because it is better than nothing, but in the long term, it is de-motivating. “All students are likely to be equally motivated to feel successful. For some, school is a viable candidate to hire for this job. This group likely includes those whose parents provide a clear link between academic achievement and career success; those whose intellectual capacities were honed through repeated, sophisticated verbal interaction with adults before the age of three; and those whose way of learning or passion matches that of their particular teachers. The students who do not hire school to feel successful are not unmotivated to feel successful. They just don’t or can’t feel successful at school—often it makes them feel like failures.”

The evidence that students want to be successful and not only pursue their interests is right in front of us, but too many people ignore it. Christensen sees it, but then he has his own blinders on. Christensen starts by building the case that “schools need to create intrinsically engaging methods for learning,” but then he leaps to the conclusion that student-centric technologies will make that happen. “When prosperity has removed this source of [extrinsic] motivation, the solution must be to make learning intrinsically motivating. Student-centric learning will play a key role in addressing this challenge. If children are motivated to learn, and if we enable each one to learn effectively, we will have an education system with a great performance record.” How does student-centric instruction—teaching students according to how their brains are wired—cause an activity to be intrinsically motivating? It is certainly plausible that, if an activity is more accessible to our way of thinking, it will be more interesting and engaging to us and we will be more successful at it. Instead of proposing a mechanism that only increases a student’s motivation (appealing to student interests), Christensen is proposing a mechanism that increases a student’s motivation and makes it easier for that student to learn. That is certainly a step forward, but it is still only a theory without any supporting evidence. Student-centric technologies may enable more students to learn, but will they enable every student to learn?

Is there an activity that enables every child to learn and be successful? Christensen believes that there is. “When a parent engages in extra talk—speaking 48 million words to an infant in its first 36 months of life—many, many more of the synaptic pathways in the child’s brain are exercised and refined. This makes subsequent patterns of thought easier, faster, and more automatic. This means that children who have been lavished with extra talk have an almost incalculable cognitive advantage compared to those who have not been. Their brains have been ‘wired’ to think in much more sophisticated ways than those of children whose synaptic pathways have not been extensively developed and lubricated through use.” And “when children whose cognitive capacities have been expanded as described above confront and succeed at the initial academic challenges they encounter in school, their sense of self-efficacy—their excitement and confidence in their ability to succeed at difficult intellectual tasks—can blossom.” The correlation between extra talk and cognitive development is strong enough to suggest that children in every demographic can be successful in school if they are exposed to enough extra talk at an early age.

What else does the evidence suggest? That interest and student-centric models are not the primary drivers for learning and success. Extra talk had the most impact in the first twelve months of a child’s life, before the child can verbally respond to the extra talk. This indicates that the content of the extra talk was irrelevant. Extra talk appears to be successful because the child and the parent are both highly engaged by it. Children strive to connect with their caretakers as an evolutionary survival mechanism. That connection makes it more likely that a caretaker will care for and protect the child. A second crucial factor in extra talk is its level of sophistication. “Hart and Risley observed two sorts of conversations occurring between parents and their infants in their study. Parents they described as ‘taciturn’ often limited their conversations with their children to ‘business.’ Business conversations with infants are not rich or complex; they are simple, direct, here-and-now conversations. The words that truly matter are spoken in a posture that Hart and Risley term ‘language dancing,’ where the parents engaged face to face with the infant and speak in a fully adult, sophisticated, chatty language—as if the infant were listening, comprehending, and fully responding to the comments. It is deliberate, uncompromised, personal adult conversation.” This suggests that learning is most effective when it fulfills the job that it is hired to do and when it is rich enough to establish new sophisticated pathways in the brain, leading to increases in intellectual capacity, self-efficacy, and curiosity.

It almost doesn’t matter what we do to improve schooling if we don’t give children tasks that cause them to create new pathways and think more sophisticatedly. Right now, schools aren’t doing that. Some project-based schools are trying, but if you look at their curriculum, you will see that tasks are sophisticated for children, but not sophisticated for adults. That won’t work either. Vertical learning is the approach that I’ve been developing for the past two decades to enable students to work on increasingly sophisticated tasks and feel successful. I describe this type of learning as vertical because thinking, performance, and achievement build and accelerate over time. If you’d like a hint of what this kind of learning looks like, take a look at a 90-minute learning session we did at Computing Explorations. If we are going to make meaningful improvements in schooling and instruction, then we need to take off our blinders and focus on what really works instead of fixating on the things we believe should work.

Wednesday, October 29, 2014

Gazing Into the Crystal Ball

Christensen predicts that, through the development of student-centric technologies, computer-based learning will soon disrupt public schooling in the United States. So far, “computers have not increased student-centric learning and project-based teaching practices. The implementation of computers has not caused any measurable improvements in achievement scores. And, most important for the purposes of this book, computers have made almost no dent in the most important challenge that they have the potential to crack: allowing students to learn in ways that correspond with how their brains are wired to learn, thereby migrating to a student-centric learning environment.” “But as is the case with all successful disruptions, if you know where to look—competing against nonconsumption—computer-based learning is methodically gaining ground as students, educators, and families find it better than the alternatives—having nothing at all.” “The data suggest that by 2019, about 50 percent of high school courses will be delivered online. In other words, within a few years, after a long period of incubation, the world is likely to begin flipping rapidly to student-centric online technology.”

Why is Christensen betting on computer-based learning when its track record has been so poor? “First, online learning will keep improving, as all successful disruptions do. It will become more enjoyable and take full advantage of the online medium by layering in enhanced video, audio, and interactive elements. Currently, according to reports, online learning works best with more motivated students; over time, it will become more engaging so as to reach different types of learners. A second driver of this transition will be the ability for students, teachers, and parents to select a learning pathway through each body of material that fits the learners’ needs—the transition from computer-based to student-centric technology. The third factor that will likely fuel the substitution is a looming teacher shortage. The fourth factor is that costs will fall as the market scales up.” Christensen knows that current models of computer-based learning are not very good and “largely mirror the dominant type of learning method in each subject.” But in the industries he has studied, products inexorably improve.

Since Christensen made his prediction in 2008, we have seen the growth of massive open online courses (MOOCs). In the case of MOOCs, “online technology provides accessibility for those who previously would not have been able to take the course. It provides convenience for a student to fit the course into his or her schedule at the time and place that is most desirable. To varying degrees, it is simpler because it offers comparatively greater flexibility in the pace and learning path. And when it is software-based and online, it can scale with ease. Economically, it is often less expensive than the current model, even at today’s limited scale.” But the completion rate of most MOOCs is less than 10%. Most students who sign up for a MOOC never finish it. Christensen believes that “layering in enhanced video, audio, and interactive elements” will make online learning “more engaging so as to reach different types of learners,” but there is no reason to believe that multimedia is going to make these courses intrinsically motivating to most students. Students don’t hire schooling to be entertained; they hire schooling to “feel successful and make progress.” The students who are most successful in MOOCs are those who are already most motivated to learn. To be disruptive, computer-based learning cannot just improve average performance and be more cost-effective, it has to help those who are least motivated to study core academic subjects be successful at them.

Christensen is essentially asking us to do something in software that we don’t know how to do in person. If we assigned every child a personal tutor, and every tutor was an expert in instruction and had access to the best instructional resources in the world, many children would continue to struggle and feel unsuccessful. Average performance would go up and the United States would be more competitive, but we would not be any closer to the goal of every child in every demographic becoming proficient in all core academic subjects. This is not something that we can do with the instruction we have today.

Unless there is a disruptive innovation in the technology of instruction, computer-based learning will be a sustaining innovation that improves schooling, but does not disrupt it. There is actually little or no resistance to computer-based learning in schools, and once it becomes good enough, schools are likely to hire it for four different jobs. First, many courses will include some form of blended learning, where teachers integrate online coursework into an existing course. This is how schools will plug computer-based learning into their interdependent systems. Second, schools will offer online courses in place of electives and other specialized or advanced courses that they can’t afford to offer themselves. Third, schools will convert some existing courses into online courses for their most motivated students. By hiring computer-based learning for these two jobs, schools will be able to channel more resources to core academic subjects and their neediest students. Fourth, schools will use computer-based learning to provide additional instruction to struggling students. Note that, in my prediction, schools are not using computer-based learning in place of teacher-led instruction for struggling students, but to increase the total amount of instruction these students are receiving.

Schools have responded to No Child Left Behind not by improving instruction, but by giving students more of it. If math class used to be 50 minutes a day, it is now 70 minutes a day. On top of that, struggling students go to a “math lab” or “intervention block” twice a week where they work with a math teacher in small groups. The use of small groups is not to provide customized instruction, but to increase extrinsic motivation through heightened accountability. This is basically the same model we have been using for special education for decades. Since there have been no innovations in instruction for two hundred years, schools have had to find other areas in which to innovate. If computer-based learning is simply a platform for delivering the instruction we already have, then it will be crammed into the same role.

Monday, October 27, 2014

Anomalous Readings

When physicists applied Newtonian mechanics to planetary motion in the Solar System, they found an anomaly: Mercury’s orbit did not match up with the orbit predicted. This led to the development of Einstein’s theory of relativity, which extended our understanding of the Universe. When Christensen applies disruption theory to public schooling in the United States, similar anomalies are also detected. Some of these anomalies are detected by Christensen himself, but are not examined or commented on; other anomalies appear to go unnoticed. If the goal is to improve the U.S. public education system or schooling in general by disrupting it, then an understanding of these anomalies is crucial.

The Technology of Public Schooling Is Immature

Christensen notes that schooling’s architecture “is highly interdependent.” “Because there are so many points of interdependence within the public school system, there are powerful economic forces in place to standardize both instruction and assessment despite what we know to be true—students learn in different ways. The problem is that customization within interdependent systems is expensive.” For example, “although an innovative teacher might see a way to teach algebra in the context of chemistry, it would be nearly impossible to do it because the structure of what can be taught in the classroom depends on how the district headquarters carves up and defines the curriculum; and changes in the curriculum would also require changes in standardized tests and admission standards. Even more problematic, this kind of change in practice would require changes in the way prospective science and math teachers are trained and certified.”

But Christensen also states that, “The level of interdependence found in a product is a function of the underlying technology’s maturity. In the early days of most new products and services, the components need to be tightly woven together to maximize the functionality from an immature technology that is not yet good enough to satisfy customer needs.” This implies that the technology of public schooling (how we teach and design schools) is immature. How can that be possible when we’ve been operating public schools for over two hundred years, and schooling has existed in the world for millennia? It is possible that interdependencies in public schooling have persisted despite the technology being mature because public education is a virtual monopoly, but the system has been disrupted three times and “schools actually have been improving—moving up the vertical axis of their industry just like the companies in all the industries we have studied.” So schools have not been stuck or complacent. “In the face of enormous hurdles, and despite changing demands on schools, teachers and administrators have constantly improved public schools in the United States and navigated the disruptions imposed upon them. The latter is something almost no manager in private industry has been able to do.”

Educational Research Is Descriptive, But Not Predictive

According to Christensen, “there is lots of education research. Some is filled with mountains of statistical evidence, whereas other research examines case studies of randomized control trials. But the statistically valid research too often leads nowhere. Much of it is contradictory.” “Although correlative studies such as these are preliminary steps on the road to robust bodies of understanding, most education is trapped in this stage and does not progress beyond it. This causes paralysis because correlative studies, or descriptive bodies of understanding, cannot tell specific people whether following the average formula will lead to the hoped-for outcome in a specific situation.”

“Why is that? Other fields have bodies of research that allow people to predict with great certainty the results of actions. Many people in education—from teachers to researchers—say that it is impossible to build models of this sort in education because education is unique. It is not a science, they say. It is an art. Certainty is impossible.” But “researchers can build the same rigorous understandings in education. Doing so, however, will require a shift away from the prevailing paradigm. No longer will research on best practices or what works best on average across education suffice. Just as researchers in medicine are working to understand disorders by their causes as opposed to their symptoms in order to move toward precision medicine, education research must move toward understanding what works from the perspective of individual students in different circumstances as opposed to what works best on average for groups of students or groups of schools.”

Christensen does not attempt to explain why educational research is trapped in the descriptive stage. Does this happen in other fields? Proponents of Intelligent Design remain in the descriptive stage, but only because their goal is to support a pre-determined conclusion, and any anomalies would undermine that. I would assume that any field that takes the pursuit of science seriously would naturally move from the descriptive to the predictive. What is preventing educational research from making the same transition? Without predictive research, we can’t understand how individual students learn, which means we don’t know how to build student-centric learning technologies. “Our experience is that we learn differently. In the last three decades, increasing numbers of cognitive psychologists and neuroscientists have acknowledged this, too. Although there is considerable certainty that people in fact learn differently, considerable uncertainty persists about what those differences are.”

Instruction Is Not Improving

While the interdependencies in public schooling may lead to standardization, we should expect to see student-centric instruction in private schools and among personal tutors. In a competitive environment, innovations are developed “to sustain the performance improvement trajectory in the established market. And it seems not to matter how technologically challenging the innovation is. As long as it helps the leaders make better products that they can sell for better profits to their best customers, they figure out a way to get it done.” But that’s not what we see at all.

Christensen assumes that student-centric instruction existed in one-room schoolhouses and exists today in special education and personal tutoring because of the opportunity for teachers to work with students one-on-one. But if you study one-room schoolhouses, special education, or personal tutoring, you will find that the instruction in those settings is largely the same as instruction in the classroom. Instruction may be customized for pace and level, and sometimes for a learner’s interests, but it is not tailored for the way a learner’s brain is wired. We simply don’t know how to do that. Students who struggle in public schools typically continue to struggle with a tutor or in a private school because this level of customization is not enough on its own to make schooling intrinsically engaging for them.

Christensen cites Howard Gardner’s theory of multiple intelligences as one possible framework for further customizing instruction. But when schools and teachers attempted to apply Gardner’s theory, they couldn’t get it to work. When a teacher targeted a bodily-kinesthetic learner with a bodily-kinesthetic lesson, the student might respond once in a thousand times. That simply isn’t a sustainable batting average. Teachers that apply Gardner’s theory today now use a shotgun approach: instead of targeting one learner with one lesson, the teacher uses a range of lessons with the entire class purely in the interest of variety and diversity.

Another way for schools to customize instruction is to implement homogeneous groups so that students are grouped by level. While most teachers and parents support this idea, many school administrators are wary because they know that the instruction in the lower level groups can often be inappropriate and ineffective. Instead of designing their instruction based on the students they have in front of them, many teachers teach according to what they believe students can do. Their beliefs tell them to teach louder and slower, regardless of how the students’ brains are wired.

In the public school classroom, everyone gets cold medicine regardless of their symptoms (standardization). In personal tutoring, you get cold medicine if you have a cold and fever medicine if you have a fever (customization). But the medicines available to the classroom teacher and the tutor are the same, and we know that those medicines are ineffective for most people and haven’t changed in over two hundred years. Customization is important, but so is developing medicines that work. For some reason, this isn’t happening.

Outliers Are Ignored

Christensen argues that computer-based learning will be disruptive because it has the potential to take expert instruction to scale. “A great advantage in creating software that has been designed with success embedded within it is that it scales readily and economically. The intuition of those elite teachers who have the instinct to conquer motivation does not. Online learning changes a teacher’s job, and, as it improves, it will enable far more people to do what only the expert intuitive teachers could do before.” But in order to embed that expertise in software, it has to be understood first. Christensen notes that “a few outlier parents, teachers, and schools actually seem to have solved the motivation problem, but in most of these instances their solutions haven’t yet seemed to scale—as if there is a secret sauce in student motivation that defies codification.”

Christensen believes that expert instruction has little impact on schools because that expertise is ultimately twisted in an effort to plug it into the existing interdependent system. To make his point, Christensen brings up Jaime Escalante, the high school math teacher who taught AP Calculus to inner-city students at Garfield High School in Los Angeles. “Escalante was an exceptional teacher. Why not capture Escalante’s instructional magic on film and make it available to schools anywhere? Sure, it’s not the same as having Escalante himself, but if he is that good, why narrow his impact to one classroom in one school? People have in fact done this with great teachers of Escalante’s caliber. But these sorts of films have had little impact because they were simply crammed into classrooms as a tool on top of the traditional teaching methods.” Now, I don’t know anything about Jaime Escalante beyond what I learned watching Stand and Deliver, but I’m fairly certain that his lectures had little or nothing to do with the outcomes his students achieved.

I may not expect Christensen to know what Escalante’s secret sauce was, but I do expect math teachers to know. But we don’t. There is a general assumption that outliers cannot be replicated or codified, so they remain unknown and unstudied. If you are more than three standard deviations away from the norm, it is like you don’t even exist. What you do is too strange to ever work for anyone else. We make it a habit to study outliers in other industries, but for some reason, not in education. This is true of fellow educators, academic researchers, and edtech entrepreneurs.

Extra Talk Wires a Child’s Brain for Learning and Sophisticated Thinking

While Christensen is unable to paint a compelling picture of what student-centric instruction might look like in the future or provide any evidence that it will substantially increase intrinsic motivation, he does describe a technology we use now that does seem to work:

“Risley and Hart estimated that by age 36 months, children of talkative college-educated parents had heard their parents speak 48 million words to them. In contrast, children in welfare families had heard 13 million. Interestingly, the most powerful of these words, in terms of subsequent cognitive achievements, seemed to be those that were spoken in the first year of life—when there was no visible evidence that the child could understand what the parents were saying. The children whose parents did not begin speaking seriously to their children until their children could speak, at roughly age 12 months, suffered a persistent deficit in intellectual capacity, compared to those whose parents were talkative from the beginning.”

“When a parent engages in extra talk—speaking 48 million words to an infant in its first 36 months of life—many, many more of the synaptic pathways in the child’s brain are exercised and refined. This makes subsequent patterns of thought easier, faster, and more automatic. The major cognitive task for infants is to develop and use the synaptic pathways that will facilitate their thought processes. A child who has heard 48 million words in its first three years won’t have just 3.7 times as many well-lubricated synaptic connections in its brain as a child who has heard only 13 million words. Each brain cell can be connected to hundreds of other cells by as many as 10,000 synapses. This means that children who have been lavished with extra talk have an almost incalculable cognitive advantage compared to those who have not been. Their brains have been ‘wired’ to think in much more sophisticated ways than those of children whose synaptic pathways have not been extensively developed and lubricated through use.”

“Strong self-esteem is a foundation that can give children the confidence they need to successfully grapple with difficult educational challenges and life issues as they are encountered. When children whose cognitive capacities have been expanded as described above confront and succeed at the initial academic challenges they encounter in school, their sense of self-efficacy—their excitement and confidence in their ability to succeed at difficult intellectual tasks—can blossom. When they enter school without this preparation, their initial academic experiences consist of struggle and failure, which destroy self-esteem and make further academic work seem intimidating and unexciting.”

Christensen presents research that infants who “listen to parents speak to them in sophisticated, adult language” develop cognitive skills and intellectual curiosity that can set them on a virtuous cycle of lifelong learning. But there is no evidence that this process is student-centric in any way. While these conversations are one-on-one, it doesn’t seem as though parents need to tailor what they say for an individual child. In fact, the whole point of extra talk is to generate new pathways in the brain, not reinforce existing ones.

Toward a Root Cause

The fact that instruction is not improving is an anomaly. Given competition, instruction should be improving in private schools and personal tutoring, if not in public schools. Some believe that the technology of instruction is mature, and that it is simply a matter of getting people to use best practices. But if that was the case, then instruction in private schools and personal tutoring should be more modular, and the research should have entered the prescriptive stage. Why hasn’t this happened? If the technology of instruction is immature, why is it still immature and why isn’t it improving?

In order for instruction to be more effective, we need to know what works and under what circumstances. We also need to study the outliers—those educators who have an intuitive expertise in instruction—so that we can codify their intuition and turn it into understanding. This isn’t happening either. These anomalies indicate the presence of a root cause preventing instructional improvement. We need to address this root cause if we are going to have any hope of disrupting schooling. The research on extra talk shows us that there may be promising paths forward if we can get moving and start thinking in new directions.

Friday, October 24, 2014

Underlying Assumptions

Public schooling in the United States has been disrupted because we are asking it to perform two new jobs: keep the United States competitive and eliminate poverty by enabling every child in every demographic to reach proficiency in all core academic subjects. The metrics used to measure the performance of our schools have changed, and schools must change to improve along these new dimensions or else society and the political system will hire new organizations to do those jobs.

Christensen believes that the only way that public schools can fulfill these two new jobs is if schooling is an intrinsically motivating experience. “Motivation can be extrinsic or intrinsic. Extrinsic motivation is that which comes from outside of the task. Intrinsic motivation is when the work itself stimulates and compels an individual to stay with the task because the task itself is inherently fun and enjoyable.” “We all know that becoming a great athlete or a great pianist requires an extraordinary amount of consistent work. The hours of time required to train the brain to fire the synapses in the correct ways and thus hone the necessary muscle memory and thinking required is no different from that needed to learn to read and process information or think through math and science problems.” “When there is high extrinsic motivation for someone to learn something, schools’ jobs are easier. They do not have to teach material in an intrinsically motivating way because simply offering the material is enough. Students will choose to master it because of the extrinsic pressure. When there is no extrinsic motivation, however, things become trickier. Schools need to create intrinsically engaging methods for learning.”

Christensen argues that U.S. schools perform poorly because our prosperity has reduced our extrinsic motivations to learn. “When Japan was emerging from the ashes of World War II, there was a clear extrinsic motivation that encouraged students to study subjects like science and engineering that would help lift them out of poverty and reward them with a generous wage. As the country and its families prospered, however, the external pressure diminished. Some people who are wired to enjoy science and engineering in the way schools traditionally teach it—and therefore are intrinsically motivated—or those who have other extrinsic motivation in play will study them. But many no longer need to endure studying subjects that are not fun for them. The same downward trend is now beginning in Singapore and Korea.”

So how do we make schooling and core academic subjects intrinsically engaging? By tailoring instruction to match how each student learns. “In summary, the current educational system—the way it trains teachers, the way it groups students, the way the curriculum is designed, and the way the school buildings are laid out—is designed for standardization. If the United States is serious about leaving no child behind, it cannot teach its students with standardized methods. We must find a way to move toward what, in this book, we call a ‘student-centric’ model. We use the word ‘toward’ intentionally here because this is not, at least immediately, a binary choice. A monolithic batch process with all of its interdependencies is at one end of the spectrum, and a student-centric model that is completely modular is at the other. How might schools start down this promising path? Computer-based learning, which is a step on the road toward student-centric technology, offers a way.”

Christensen makes a number of assumptions here. First, he assumes that all students will learn if they are intrinsically motivated. Second, he assumes that “allowing students to learn in ways that correspond with how their brains are wired to learn” creates intrinsic motivation. Third, he assumes that we already know how to tailor instruction for every student. Christensen writes:

“In the 1960s and 1970s, society began requiring schools to customize offerings for students deemed to have special needs. Students who qualify for these designations typically require individual approaches, codified in an individualized education plan (IEP). In another special case, educators place immigrant students from non-English-speaking families into custom-designed English language learner (ELL) programs. Customization is almost surely an important advantage for both these categories of students, but it is also terribly expensive.”

“In the one-room schools that characterized public education during most of the 1800s, teaching was customized by necessity, at least by pace and level. Because the room was filled with children of different ages and abilities, teachers spent most of their day going from student to student, giving personalized instruction and assignments, and following up in individually tailored ways. But as classrooms filled in the late 1800s, this method of teaching changed as larger enrollments forced schools to standardize.”

“The second phase of the disruption we term student-centric technology, in which software has been developed that can help students learn each subject in a manner that is consistent with their learning needs. Whereas computer-based learning is disruptive relative to the monolithic mode of teacher-led instruction, student-centric technology is disruptive relative to personal tutors. Tutors today are largely limited to the wealthy; and for those privileged few, good tutors come as close as possible to helping students learn each subject in ways that match the way their brains are wired to learn. Like all disruptions, student-centric technology will make it affordable, convenient, and simple for many more students to learn in ways that are customized for them.”

Christensen assumes that student-centric models already exist in special education and personal tutoring, but that we don’t yet have the technology to bring these models to scale. That is where computers—and student-centric technologies—come into play.

Christensen acknowledges that, at the moment, computer-based learning is not competitive with teacher-led learning. “If the history of these types of innovations can serve as a guide, the disruptive transition from teacher-led to software-delivered instruction is likely to proceed in two stages. We call the first of these stages computer-based, or online, learning. In this stage, the software will be proprietary and relatively expensive to develop. It will also be relatively monolithic with respect to students’ preferred methods of learning in that the instructional methods in this software will largely mirror the dominant type of learning method in each subject.” “Currently, according to reports, online learning works best with more motivated students; over time, it will become more engaging so as to reach different types of learners.” Right now, students who lack motivation to learn are even less motivated by online learning. Christensen assumes computer-based learning will get better as it is adopted and refined in markets where teacher-led learning is unavailable. These markets target nonconsumers, people whose only option is to use either computer-based learning or nothing at all.

Christensen expects computer-based learning to improve along a specific trajectory. Experts in student-centric instruction will use the technology to take their models to scale. As the technology matures and this instructional expertise is codified, instruction becomes modular. “The level of interdependence found in a product is a function of the underlying technology’s maturity. In the early days of most new products and services, the components need to be tightly woven together to maximize the functionality from an immature technology that is not yet good enough to satisfy customer needs. As products and their markets mature, technology grows more sophisticated, as do customers. They begin to understand their unique needs and to insist on customized products. Technological maturity makes customization possible. Product and service architectures become more modular in this environment.” Modularity enables a product to improve more rapidly and inexpensively because the entire product does not need to be redesigned every time. If instructional expertise then becomes commoditized, then user-generated instruction can be delivered via facilitated networks and the existing value network can be disrupted. “In this second stage of disruption, the existing value chain, which we call a ‘value network,’ is almost always disrupted as well. It is rare for a disruption to appear in just one part of a value network without the rest of the system changing, too. It is the disruption of the full value network that ultimately enables these modular solutions to emerge. Embedding a disruptive product in an entirely disruptive value network is key to achieving a less expensive solution than was possible in the first stage of disruption.”

Unless computer-based learning competes on a different dimension (not just in a different market), it will not be disruptive. If computer-based learning simply does the job that schools do now, only better, it will be adopted by schools as a sustaining innovation and nothing else will change. To become a disruptive innovation, computer-based learning must evolve into a student-centric technology, enabling every student in every demographic to reach proficiency in all core academic subjects. But that can’t happen unless the instructional expertise to create student-centric learning models exists to be codified and commoditized. Christensen assumes it does exist, but I don’t. I don’t think we can afford to make that assumption without some evidence.

Wednesday, October 22, 2014

A Square Peg in a Round Hole

When analyzing schooling, Christensen observes that the public education system in the United States has been disrupted three times. “But because the United States has been unwilling or unable to facilitate the entrance of new organizations with new business models to disrupt the old, public school districts have had to negotiate this disruptive redefinitions of performance entirely within their existing schools. In our studies of disruptive innovation in the private sector, we are not aware of a single instance in which a for-profit company was able to implement successfully the disruptive innovation within its core business. The few that survived disruption did so by creating, under the corporate umbrella, a new business unit, with a new business model attuned to the disruptive value proposition. Asking the public schools to negotiate these disruptions from within their mainstream organizations is tantamount to giving them a demonstrably impossible task.” In the first two cases, public schools were able to manage the disruption from within their existing organizations. They are grappling with the third case now.

Disruption occurs when performance is redefined. A sustaining innovation improves a product. A disruptive innovation changes what improvement means. Originally, public schools in the United States were established to “preserve democracy and inculcate democratic values” by teaching the basics, instilling sound morals, and preparing “an elite group—selected on merit from this entire pool of students, not just those from the upper class—to lead the country wisely in elected office.” One-room schoolhouses appeared to fulfill this job.

“In the 1890s and early 1900s, competition with a fast-rising industrial Germany constituted a minicrisis; Americans responded in the early twentieth century by handing schools a new job: prepare everyone for vocations. The goal was to produce a sound workforce for jobs ranging from administrative functions to technically demanding manufacturing positions so that America could compete with Germany. The old job of preparing the next generation to lead and participate in democracy did not go away; society simply asked schools to perform both jobs.” One-room schoolhouses had been improving through sustaining innovations, but suddenly, those improvements didn’t matter any more. The direction in which schools needed to improve had changed, and the comprehensive high school appeared to fulfill this new job.

Comprehensive high schools steadily improved, fulfilling their job more and more effectively, until the public education system was disrupted again. “The nation asked its schools to take on the new job of keeping the United States competitive. Although seemingly similar to the previous job, it was actually quite different. No longer could students choose most of their classes or focus on the vocational or general or academic track depending on their interests or talents. Virtually everyone had to focus on the core academic classes and take the same tests. Japan’s disruption of America’s manufacturing industries increased the pressure for all students to attend college, which further ratcheted up the need to focus on the core subjects and tests because postsecondary schools increasingly required them. This was a radically different demand of schools.” Suddenly, schools had to measure themselves against standardized tests, some administered globally. Instead of continuing to expand course offerings, courses were pared back to focus on core academic subjects.

Once again, the public education system responded. It didn’t become an industry leader, but it did re-organize itself and begin improving along these new dimensions. Then disruption struck for the third time. “The No Child Left Behind Act not only federally cemented average test scores as the primary metric for performance improvement, but also arguably once again shifted the goalposts. No longer can public schools simply raise the average test scores in their schools; instead, public schools must see to it that every child in every demographic improves his or her test scores. Now the performance measure for schools is the percentage of students who are proficient in core subjects. The essential motivation for asking schools to make sure that all students are proficient in reading, math, and science is to eliminate poverty.”

Incumbents find it next to impossible to manage disruption from within their existing organizations because they are structured to satisfy existing customers. Imagine that someone develops a car that can hover. For most existing customers, these hover cars are vastly inferior to the cars they can already buy on the dimensions that matter to them. There are a few new customers that prefer the hover car for various niche uses, but their numbers are small. The car companies can’t invest in hover cars because their existing customers don’t want them and the market for new customers is too small to contribute to their growth. By the time the hover car has improved enough to either satisfy existing customers or attract enough new customers to make the market valuable, it is too late.

This is how disruption normally proceeds, but it isn’t how the current disruption is proceeding in the U.S. public education system. The customer of public schooling is society and the political system. Society hires public schools to do a job, such as keeping the United States competitive or eliminating poverty. In order to do that job, public schools need students to hire them also, but the primary customer is society. In the three disruptions described by Christensen, it’s been the existing customer that has redefined the job to be done. Public schools aren’t facing the dilemma of having to choose between satisfying existing customers or pursuing new customers. Sure, some stakeholders are unhappy with the new jobs that have been given to schools; some stakeholders wish that we could return to the days where the goal was to increase participation by increasing course offerings. But the most lucrative customer, the one that controls the purse strings, has spoken. This may explain why public schools have been able to manage these disruptions so successfully in the past where for-profit companies have failed.

The other significant difference I see is the source of the disruption. Typically, there is an innovative technology. If this innovative technology causes performance to be redefined and new business models and value networks to appear, then the innovation is disruptive. If none of that happens, then the innovation is sustaining (or not innovative at all). But note that the technology precedes the disruption. There is no disruption without a disruptive technology.

This was the case when public schooling in the United States was disrupted the first two times. Comprehensive high schools appeared because one-room schoolhouses could not compete with the schooling in Germany. Christensen doesn’t say what it was, but some innovative schooling technology had been developed in the German market, and it was now disrupting the U.S. market. The public education system had to respond or give way to new organizations with new models. The same thing happened when comprehensive high schools were replaced by a focus on core academics and standardized testing. The public education system was disrupted by innovative schooling technologies from other countries, such as Japan. But, as far as I can tell, the third disruption, the one we are currently in, was not triggered by any technology. Is there a schooling model anywhere in the world that has eliminated poverty by enabling every child to reach proficiency in all core subjects? This is as though existing car customers suddenly decided en masse that they wanted hover cars before anyone even knows if it is possible to build a hover car. Schools are now scrambling to invent technologies to respond to this disruption, but there is no guarantee that they will be successful.

I want to make one final observation on the history of disruption in public schooling in the United States. None of the innovative technologies in the first two disruptions were instructional in nature. Instruction has not changed since the days of the one-room schoolhouse. Sure, we almost certainly lecture more often today given the batch processing model of schooling we have now, but the lecture existed in one-room schoolhouses. If you were to observe a teacher from the 1780s working with a small group of students and a teacher from the 2010s working with a small group of students, the instruction would be very similar. The innovative technologies that caused the first two disruptions affected systems surrounding the classroom, but they did not change the instruction that occurs inside of the classroom. In other words, the instructional component of schooling was used to achieve a new purpose, but the component itself did not improve. Schooling was disrupted, but instruction was not.

Christensen believes, and I agree with him, that public schools in the United States will need new instructional technologies in order to fulfill both the new job of eliminating poverty and the old job of keeping the United States competitive. Christensen assumes that these new technologies will appear simply because schools have been disrupted and we need them. I am less optimistic.

Monday, October 20, 2014

Applying Disruption Theory to Public Schooling

Clayton Christensen is the author of The Innovator’s Dilemma and an expert in disruptive innovation. In 2008, he applied disruption theory to analyze public schooling in the United States.

When I first read Disrupting Class, I felt that Christensen made a lot of bold claims about schooling and education without backing them up. But after reading his book for a second time, I realized that Christensen isn’t trying to build a descriptive understanding of schooling from data, but a predictive understanding of disruption by applying disruption theory in a new context.

According to Christensen, “researchers build bodies of understanding in two major stages—the descriptive stage and the prescriptive stage.” In the descriptive stage, researchers “generally follow three steps—observation, categorization, and association—as they do their work.” Christensen has observed, categorized, and identified key relationships in industries undergoing disruption. Describing disruption from data has enabled him to construct a model of disruption that he is now applying to public schooling in the United States. In the second stage, researchers use their models to make predictions and uncover anomalies. “Anomalies are actually good news because they allow researchers to say, ‘There’s something else going on here,’ and that is what leads to better understanding.” “Researchers use the anomaly to revisit the foundation layers in the [descriptive stage] so they can define and measure the phenomena less ambiguously, or sort those phenomena into alternative categories. Only then can researchers explain the anomaly and the prior associations of attributes and outcomes.”

Christensen writes, “Our approach in researching and writing this book has been to stand outside the public education industry and put our innovation research on almost like a set of lenses to examine the industry’s problems from this different perspective.” Instead of taking a deep dive into education, he is taking a step back to look at schooling from a distance. In many ways, he isn’t saying what will happen based on his understanding of schooling and education; he is predicting what should happen based on his understanding of disruption. If his predictions are accurate, then his model of disruption is confirmed; if it isn’t and anomalies are discovered, then there is an opportunity to improve our understanding of both disruption and the public education system.

I think that there is great value in examining schooling through the lenses of disruption theory. It has helped me to categorize some of my own observations and bring certain relationships into focus. I also think it is valuable to take a fresh look at education from the outside. It is very interesting to compare what an outsider thinks should be happening to what an insider thinks is happening. That’s what I’ll be doing. In a series of blog posts, I will be re-examining Christensen’s examination, but doing it from the perspective of someone who has been much closer to the ground in schools.

In A Square Peg in a Round Hole, I examine why disruption theory may not apply to what is happening in public schooling in the United States today; in Underlying Assumptions, I examine some of the assumptions that Christensen makes in predicting how schooling will be disrupted; in Anomalous Readings, I discuss some of the anomalies detected in Christensen’s analysis; in Gazing Into the Crystal Ball, I compare and contrast Christensen’s prediction with my own; and in Removing Our Blinders, I examine how blinders could be preventing us from creating disruptive innovations in schooling and instruction.

Sunday, July 6, 2014

Lessons from a Boucherie

In one episode of No Reservations, Anthony Bourdain travels to Cajun country and attends a boucherie, a massive party where families gather to break down and cook an entire hog over the course of a day. The tradition of the boucherie arose because there was no refrigeration, so fresh meat had to be prepared and eaten quickly.

The food and the live music at this particular boucherie is phenomenal. It seems as though every adult in the community is an expert at cooking at least one speciality dish and playing at least one musical instrument. You can see the kids in the community hovering around the action, their faces lit up as they try to absorb and learn as much as they can.

I believe that when my friend Alec talks about “everyday” learning, this is what he means. Learning is informal, immersive, and seemingly effortless. Alec recently shared two YouTube videos with me to highlight what everyday learning can look like. The first is from a documentary, Boxing Gym. The second is from a talk by Alan Kay where he shows footage of a tennis coach teaching a 55-year-old woman to play tennis in about 30 minutes.

Notice that I said, “can look like.” There is nothing everyday about these examples of everyday learning. The reporter who shot the footage of the tennis coach set up the shoot in order to discredit the coach because he was offended by the notion that almost anyone could learn to play tennis in a single afternoon. The reporter had been trying to learn to play tennis for years. And I haven’t seen the documentary, but I’m going to guess that the gym in Boxing Gym is quite a special place.

Alec has repeatedly argued that everyday learning is effective because we get what we need from it; I have repeatedly disputed that. For me, the footage of the tennis coach teaching the woman to play tennis in 30 minutes was not surprising. I have seen what people can do in the right circumstances. I have constructed some of those circumstances myself. When you know what people can do, then the everyday learning that we see everyday is far from “good enough.”

At most boxing gyms, I’m going to receive little tutelage unless I show promise as a boxer. The elite boxers aren’t going to take me under their wing. There is probably a clear pecking order and I will be bombarded with the message: “You're wasting your time and ours. You’re just not that good.” Some young boxers will persevere through that and still get what they need, maybe winning the respect of the other gym members over time. But I’d probably quit and try something else.

At the gym in Boxing Gym, I’m going to guess that, somehow, a culture of mentoring has taken root; everyone helps everyone, regardless of skill level. In fact, the members of the gym probably derive more pleasure from seeing a single unskilled boxer progress than in producing x number of world champions. And that probably isn’t due to self-selection. You start boxing there. You see the elite boxers, the ones you admire and want to emulate, patiently working with that clueless kid. You try it too, and you experience that pleasure. In another episode of No Reservations, an ex-con working at a community kitchen talks about what it was like to find a place for the first time where you checked your ego at the door because there was no need for it. These are life-changing experiences. When you know that these kinds of places exist, it is hard to argue that most of us get what we need.

The boucherie culture witnessed by Anthony Bourdain exists because there is a critical mass of domain and mentoring expertise in the community. That community will be self-sustaining only if that expertise is at a sufficiently high level. If the food and music produced at the boucherie is only mediocre, or if the kids don’t see themselves stepping into the roles of lead cook and lead musician in a few years, then you are going to hear a lot of teenagers asking: “Is it okay if I hang out with my friends at the mall instead?”

I talk a lot about the need to ratchet up our domain and mentoring expertise even higher, beyond what we need to sustain a learning culture. I want to find out what it takes to export a learning culture. It’s not that I want to see neighborhoods with boxing gyms at every corner or that throw boucheries every weekend. It’s that: before we can develop the domain and mentoring expertise we need to coach others effectively, we have to want it; and for most of us, before we can want it, we need to see it and know that it is possible. I want people to experience a boxing gym or a boucherie and wonder: “Gee, why doesn’t this exist for <insert your favorite domain here>?”

I live near Boston and Cambridge where there is a large and vibrant maker community. This maker community is making a determined effort to infuse its DNA into local schools. But the coaching available to kids growing up in the maker community sucks. Not most of it; all that I’ve seen. There is nothing happening that comes close to what I know that people can do given the right circumstances. How is this possible? If you have misconceptions about what people can do, then you will be limited by those misconceptions. The boucherie, the boxing gym, and the tennis coach can’t counter those misconceptions because not enough people have regular firsthand experience with them. If we do learn about them, we marvel at them instead of emulating them.

So here is the challenge as I see it. In order for learning to be effective, whether everyday learning or in-school learning, you need effective coaches. In fact, you need a large number of highly effective coaches so that everyone has regular contact with good coaching. But in order for people to even aspire to be a highly effective coach, they also need to come into contact with good coaching. It’s quite the chicken or the egg problem.

Friday, July 4, 2014

Self-Concept, Pick-Up Basketball, and Clash of Clans

There are a few reasons why I’m skeptical of using everyday learning as the model for all learning. One of them is the issue of self-concept.

After college, I attended graduate school at the University of California at Berkeley, and two of my closest college friends settled in the Silicon Valley area. My two friends loved to play basketball, and we spent one summer working out and going to local courts to play pick-up basketball games. Now, the courts we were playing on didn’t look anything like the courts in the movie, White Men Can’t Jump. Guys were most definitely not dunking all over the place. But games were super competitive and the people playing in them could play.

I’m not really sure why I allowed myself to get dragged to these games. My friends were good; I was not. Growing up, I had shot around with my sisters and younger brother, but I had never played in any games, so my ball-handling skills were next to nonexistent. When I stepped onto the court, my mindset was to avoid making visible mistakes. I didn’t want the ball passed to me, and I dreaded having to take an open shot. I focused on defense and rebounding. During the hours of practice we did between games, I did next to nothing to work on my ball-handling skills. In games, I dribbled exclusively with my right hand. With a little practice, I could have learned to dribble with both hands (drastically improving my game), but I never did.

One day, we were invited to play a full-court game. Courts were usually so crowded that most games were half-court, and only the best players were able to play full-court. They had four, but we only had three. So the four guys we were playing against scanned the sidelines and picked this young, chubby kid to be our fourth. It was obvious that no one wanted this kid on their team. He had probably been waiting all day to get into a game, but no one ever picked him.

He was a chucker. As soon as he touched the ball, if he was open and in range of the basket, he was going to shoot. It didn’t matter if I was wide-open beneath the basket for a lay up, there was no way in hell he was going to pass the ball. He was probably thinking that he never gets to play in any games and everyone already thinks he sucks, so he may as well make the most of his opportunity and shoot as often as he can. Besides which, if he did pass the ball to one of us, he figured we’d never pass it back.

The situation looked dire. We were shorter and slower than the four guys we were playing against (at 5' 8", I was playing center in our 1-3 zone), and we were saddled with a chucker and me, a half player. It should have been a romp for the other team. But my two friends and I had something that the other team didn’t: great teamwork. We clamped down on the other team on defense and managed to build a small lead.

I’m not sure what the kid, the chucker, was thinking during all of this. He was hurting us on both offense and defense, but we kept passing him the ball and trying to integrate him into our system. We treated him as though he was a fully functioning member of our team, as though we expected him to play smart and play hard, and we didn’t get down on him when he didn’t. At some point, he must of recognized that something different was going on because he stopped chucking the ball and started working with us. He hustled, looked for the open man, passed the ball, and covered his zone. When we signaled him to cut across the court or switch on defense, he did.

We ended up losing that day, but the game went down to the wire. It was exhilarating and I remember being in the flow. I stopped being self-conscious and started looking to push the ball up court and get open for baskets. Anything to help the team. Among the spectators, I’d like to think that some of them could appreciate what we were doing (that some of them were rooting for us), but the vast majority were simply incredulous that the other team was playing this poorly and thought that we had nothing to do with it. For most players at this level, individual skill is more highly regarded than teamwork.

The transformation in the kid that day was amazing. He went from a classic chucker to a team player in the course of one game. Along the way, he picked up some skills for playing in a zone and communicating on the court that he could build on with the right teammates. He felt this. If we had decided to hop in our cars and drive to another court, he would have gone with us. If we had shown up at this court again the next day, he would have joined us. He had decent skills as a player (better than me), but his lack of status on these courts had caused him to pick up bad habits and become a chucker. Once he became a chucker, even the more generous players on the court didn’t want to play with him. His own perception of himself, drawn from how everyone around him perceived him, became self-fulfilling. But it could all be reversed given the right opportunities, the right mentoring and coaching.

Fast-forward twenty years and this scenario is playing out again. I’m playing Clash of Clans in a clan with fifteen other guys. About half of the clan are in middle school. There is a clear and fairly rigid hierarchy in the game. At the top are the innovators. These are the players who design new bases and attack strategies. Then there are the players who copy the innovators, but can internalize those designs and strategies well enough to adapt them for different circumstances. Then there are the players who can copy the innovators, but can’t counter when a design or strategy is countered; they run the script the same way every time. Finally, there are the players who can’t even manage to run the script for a given design or strategy properly. These last guys “suck.”

A few months ago, Clash of Clans introduced clan wars. Before clan wars, you attacked for loot in order to upgrade your base and your troops. When attacking for loot, you can look for easy bases to attack. It is common to attack fewer than one in twenty bases you look at. And your attacks are private. You can share the replays of your attacks, but that is optional. A lot of players who are poor attackers end up gemming (using real money to buy upgrades instead of using in-game currency).

Once clan wars started, you started attacking bases at your own level for the clan, and those attacks are public. A lot of clan members were embarrassed by how much they “sucked” and would go onto YouTube to search for better base designs and attack strategies. As one of the innovators in the clan, I’m not a fan of copying ideas from YouTube or other sources. At a minimum, I feel like you should understand those base designs and attack strategies well enough to modify them. Over time, I offered tips and suggestions, and encouraged the guys to analyze each others’ attacks. Most ignored me, but a couple took up my advice and became incredibly strong attackers. Once that happened, more joined in. At this point, we have over a dozen very strong attackers, which is rare. Most clans that we go up against have 2-3 strong attackers and bunch of other guys that “suck.”

Yesterday, Supercell updated Clash of Clans with some significant changes to how troops behave, breaking most existing base designs and attack strategies. Across the internet, players are waiting for the innovators to absorb the changes and post new YouTube videos. In my clan, there was a great deal of unease. I suggested that we use the next clan war to focus on experimenting with new strategies, and to forget about winning for a while. This unleashed an immediate torrent of new attack strategies on online chat. Up and down the clan, guys are analyzing the impact of the changes and discussing how to deal with them. The level of analysis is impressive. There’s something else that I’ve noticed. If a new guy joins the clan and he “sucks,” there used to be a chorus to kick him out of the clan. Now, a new guy receives a steady stream of high quality advice from multiple members of the clan. It is gratifying to see the guys I once mentored mentoring others, and doing a better job at it than I did.

The pick-up basketball game and my clan in Clash of Clans are both examples of everyday learning. But they aren’t typical examples of everyday learning. In everyday learning, that chubby kid typically becomes a chucker, internalizes that he is a chucker, and remains a chucker for the rest of his life… with his basketball skills plateauing or atrophying. In Clash of Clans, only the elite players are innovators and everyone else settles for copying the elite players. In the world that I envision, everyone receives the opportunities to overcome and exceed those self-concepts if they choose to do so. As far as I can tell, that requires a large number of strong on-court and in-game mentors and coaches. How do we develop them? That’s what I’m working on.

One final note. Overcoming your self-concept and shifting what you believe you are capable of doing (the standard you establish as “good enough” performance for yourself), is only the first step. If that kid worked hard at becoming a good team player and developed a solid team around him, he wouldn’t necessarily win many games. And without that positive feedback from winning, it’s really tough to keep going and maintain the belief that you can do it. When we started that pick-up game, we started in a zone because it complemented our skills as team players and we didn’t think we could match the other team’s athleticism. We started in a 1-2-1 zone, but we couldn’t stop them from scoring against us. After huddling and analyzing the situation, we thought that a 1-3 zone might work better, and it did. We were able to perform that analysis because we had played and experimented with zones many times, and we had an understanding of their strengths and weaknesses. We also had strong analytical skills. Those things all take time to develop, which is why I think coaching is so important. It doesn’t have to be formal coaching. It could just be random guys making suggestions and observations here and there. But I think that pervasive high-quality coaching is necessary to achieve what I envision.