This DIY ethic is now seeping into one of the most locked-down social institutions in existence: education. Educators, parents, technologists, students, and others have begun looking at the components, subassemblies, assemblies and specifications of excellent education and are finding ways to improve, reimagine, and reinvent learning at every level. They are inspired by a multiplicity of sources, from neuroscience to gaming, to knock down the barriers to learning that exist for so many young people. In every way, they are looking at the components of teaching and learning, and finding ways to re-create them to be more efficient; more effective; and, critically, more modular.

The disassembly of traditional educational products and processes into modular pieces invites students and educators to mash up apps and lessons and processes in ways that are more appealing, enjoyable, or effective for a particular learner or group. This puts us on the path to personalized learning. It weakens the requirement for students to learn together in lockstep, covering the same material at the same pace at the same time by listening to lectures in the same room and turning in the same homework on the same morning. It invites tinkering with different ways to break apart building blocks and put them back together while creating room for new building blocks to fit into those emerging structures.

What do these building blocks look like? They include content that gives everyone with an Internet connection access to free lessons on just about any topic from the Khan academy to MIT Open courseware and lots more. There are videos and simulations such as those created by University of Colorado’s PHET that show processes and concepts that are difficult to visualize. We see platforms like Edmodo that let students and educators communicate with each other any place any time via the Internet. There are augmented reality applications and immersive interfaces for learning. There are a host of apps and software that let students learn new concepts and drill important skills in ways that are more engaging than worksheets and textbooks.

The tools and technologies that are cherry-picked online or handcrafted by educators and learners enable more choices, more freedom, more personalization and more ownership than ever was possible with one teacher, 30 kids, and old-school print resources. We are beginning to see what is possible when learners, not institutions, own the education that is going to define their lives.

Improving schooling

Schoolers recombine the components of education to make schools better. They seek to increase opportunities for all students to be well prepared for college and careers that will allow them to participate economically on a level playing field in a global market.

Schoolers are applying new tools to traditional goals to crack open the case on the traditional schoolhouse. With laptops, tablets, and cell phones, students no longer wait to be spoon-fed information, but reach out beyond the walls of the classroom for images, information, and insights at the moment the question arises for them. Social learning sprawls beyond two-hour “group work” to anytime, anyplace collaborations using tools like Google Docs, Edmodo, text messaging, and even Facebook. Via Skype and video streaming, experts can visit classrooms and engage in meaningful talks with students both as individuals and in groups. Schools are using “blended learning” (combining online learning with brick-and-mortar schools) to let students work at their own pace and study topics that interest them beyond the classes they can afford to offer. Students across the globe connect with each other, learn how other cultures see them, and are bemused by the misperceptions.

We see flipped classrooms where students listen to lectures via podcast at home, leaving more face-to-face class time for deeper exploration, critical thinking work, and discussion. We see at-risk students moving from low achievement and aspirations in math to completing AP courses and heading for college once they start using mobile devices for peer mentoring and developing learning communities. We see young people eager to spend more time on math, thanks to engaging apps and competitive leader boards. Most importantly, we see students gaining a sense of agency in their own learning — education is less something that is done to them, and more something they own.

Re-specifying education

Edupunks take educational building blocks and repurpose them in ways ranging from the mundane to the nearly unrecognizable. Not content with improving schooling, the movement is deeply infused with a DIY ethic that questions the purpose of education and the legitimacy of institutional definitions. In effect, they place the right and responsibility of defining educational goals and approaches on learners and their communities, and put the disassembled building blocks of educational technology to personal use.

We see Edupunk teens and young adults creating their own majors; creating new jobs and careers; learning through travel, work, apprenticeship; and getting traditional college schooling online without incurring massive college debt. The Edupunk’s Guide to a DIY Credential asks young people to create their own learning plan, keeping in mind that “‘I want a college degree’ is not a goal, because it’s not an end in itself.”

We see Edupunk alternatives to traditional, costly college credentialing, including online universities, Udacity and University of the People. We see Edupunk parents creating alternatives to coercive education, such as Unschooling, where children learn through play, participation in work and household responsibilities, and other life experiences, hoping that their children will learn not only the basic skills needed to be effective in their lives and communities, but also retain their joy, creativity, and initiative.

We see Edupunk technologists and innovators finding ways to replace institutionally defined, expensive learning tools and materials with modular, free and open alternatives, such as Open Education Resources, Moodle, CK12, and many more. We also see free tech, such as the curation software from Pathbrite, that lets us show off our accomplishments much more richly with portfolios than with grades.

Making to learn and learning to make

Makers participate in a DIY community that embraces “technology on their own time.” At Maker Faire, we can see projects that call for the knowledge, talent, and skill of a 21st-century Renaissance person. We also become immersed in an eclectic community of modern innovators who take joy in the hard work of creation and in sharing not only completed projects and achievements, but their knowledge, ideas, and tricks of the trade.

When we talk about making and learning, we usually do so from two perspectives: “making to learn” and “learning to make.” “Making to learn” refers to the phenomenon that real learning is an inevitable side effect of making. In this context, the learning serves the maker’s own true purposes (as opposed to simply winning good grades). That means that the learning is deep and meaningful, and stays with the maker.

Much of this learning turns out to be the kind that is valued in schooling, such as electronics, programming, and other skills and knowledge that are valuable to the science, technology, engineering, and math (STEM) fields. Even more of this learning turns out to be the kind that is valuable in life, such as the perseverance to achieve ambitious goals, even in the face of obstacles; the technical fluency to use modern resources such as Instructables, YouTube, blogs, and other online sources; and the collaboration skills required for participating in communities that are local and face-to-face as well as those that are global and virtual.

“Learning to make” refers to the intentionality with which makers pursue the skills and knowledge they need for their projects. Makers learn their trades through traditional and non-traditional means. They may take a welding class at a local maker space, take a programming class at a community college, get advice from other makers at a local Dorkbot meetup, or figure things out through trial and error. Makers become expert learners.

Importantly, at a time when we are struggling nationally with a fundamentally flawed system to test and grade children to make sure they are learning, the maker community shows us another viable and proven approach. As with authentic communities of practice or learning communities, makers respect contribution and work at all levels of proficiency and innovation. The standard of excellence is set by an emergent, distributed consensus where makers individually and collectively recognize great work when they see it and use the example of others to raise the bar for their own work. Ron Berger explains how setting the bar for quality work in a classroom works very similarly in his book, “An Ethic of Excellence.”

Sharing the experience at Maker Faire

This year’s Maker Faire is coming up this weekend and is an unparalleled opportunity to experience the DIY ethic as it applies to young people first hand. Families with kids ranging from toddlers to teens will make rockets, learn how to solder, sew, and make all kinds of interesting projects. Young Makers will show off the ambitious projects they have developed over the past year. EdSurge and the Charter School Growth Fund will host a DIY Learning Pavilion where some of the building blocks of DIY learning will be exhibited as well as examples of how they are repurposed by schoolers, Edupunks, and makers alike. This year, visitors will be participating in DIY learning as they engage with makers and participate in making their own projects all over the Faire as well as building a collective learning portfolio with Pathbrite.

In a pretty fundamental way, DIY is intrinsically about owning your learning as well as your hardware. No wonder there is a growing movement to open it up, void the warranty, and tinker. What will you make of it?

Related:

• Teachers as Makers
• World of Warcraft and Minecraft: Models for our educational system?

It’s pretty straightforward to recognize that new job categories, such as data science, will require new skills. The first-order solution is to add data science as a college curriculum and work the prerequisites backward to kindergarten. But if JSB is right about the half-life of skills, even if this process were instantaneous, the learning path begun in kindergarten might be obsolete by middle school.

The second-order solution is to include meta-skills into the curriculum — ensuring young people learn how to learn, for instance, so that they can adapt as new skills are required with increasing frequency. This is essential, but raises the question of how to stay ahead of the skills curve — what are the next critical things to learn, how do you know, and how do you find them?

John Seely Brown and co-author Douglas Thomas propose in their book “A New Culture of Learning: Cultivating the Imagination for a World of Constant Change” a third-order solution, which is to inculcate the mindsets and dispositions that will lead us, as independent agents, to the things that matter. These include curiosity, questing, and connecting.

A similar theme emerged at the Design, Make, Play workshop at the New York Hall of Science in January. Focused on the question of how the maker movement can catalyze innovation in science, technology, engineering, and mathematics (STEM) education, participants included technologists, makers, learning science researchers, educators, and more, all wrestling with how to translate the authentic, integrated experiences that designing, making, and playing provide into something that can be measured, understood, and incorporated into education.

The primary outcomes of making, designing, and playing look much more like JSB’s dispositions than the skills demonstrated on standardized tests of reading, writing, and arithmetic. At the same time, though, practical skills are developed — the kinds of projects exhibited at Maker Faire require the same skills as many high tech professions.

This highlights the most pernicious, devilish, intransigent challenge to bringing critical learning into school. Through the lens of standardized tests, higher order skills, meta-skills, and dispositions are literally invisible. Yet, these tests are the gold standard of educational efficacy for judging schools, educational innovations, and now even teachers themselves. School boards are held accountable by property owners for such test results due to their direct correlation to property values. Innovators, researchers, and even the philanthropic institutions that fund them are beholden to education investors for meaningful results that prove innovations work — with test scores as the default.

This conundrum is well understood by the very stakeholders who are trapped by it, and there are efforts at many levels to combat it — from incorporating critical thinking skills into the core standards being adopted by most states to alternative measures of effectiveness being adopted by grant makers. At the DMP workshop, participants struggled with the very real challenge of authentically articulating the benefits of design, make, and play at different levels and the measures that would make these benefits visible. It’s a tricky balancing act to reduce something to metrics without losing its essence.

One fascinating approach was presented by Kevin Crowley about how to recognize the impact of science experiences such as those found in museum exhibits on young people. Crowley and his colleagues researched the forces and events that influenced scientists and science enthusiasts in their career/hobby choices. They identified the notion of experiences that caused “science learning activation,” which they defined as a “composite of dispositions, skills, and knowledge that enables success in science learning experiences.” The idea is that perhaps we can measure the degree to which a specific informal learning experience creates such activation and that this becomes one of the measures that shines a light on the outcomes of making.

As the gathered experts brainstormed to articulate the genuine outcomes of making for students and how to capture those, it became clear that this is a task that is both crucial and emergent. If authentic learning is to become available to all students regardless of means or zip code, the iterative and ongoing process of articulating the educational values of a world of rapidly changing expectations must become a priority for experts and lay folk alike. What are your thoughts? How do we capture and share the soul of making without turning it into something that can be tested using the No. 2 pencil?

Related:

• Teachers as Makers
• Can standardization and innovation coexist in education?
• Tinkering with technology education
• Education as a platform

The Learning Registry addresses the problem of discoverability of education resources. There are countless repositories of fantastic educational content, from user-generated and curated sites to Open Education Resources to private sector publisher sites. Yet, with all this high-quality content available to teachers, it is still nearly impossible to find content to use with a particular lesson plan for a particular grade aligned to particular standards. Regrettably, it is often easier for a teacher to develop his own content than to find just the right thing on the Internet.

Schools, states, individuals, and professional communities have historically addressed this challenge by curating lists of content; rating and reviewing sites; and sharing their finds via websites, Twitter and other social media platforms. With aggregated sites to peruse, a teacher might increase his odds of finding that “just right” content, but it is still often a losing proposition. As an alternative, most educators will resort to Google, but as Secretary of Education Arne Duncan told the SETDA members, “Today’s search engines do many things well, but they aren’t designed to directly support teaching and learning. The Learning Registry aims to fix this problem.” Aneesh Chopra, United States CTO, called the project the flagship open-government initiative for the Department of Education.

The Department of Education and the Department of Defense set out to solve the problem of discoverability, each contributing $1.3 million to the registry project. Steve Midgley, Deputy Director for the Office of Educational Technology pointed out, “We didn’t build another portal — that would not be the proper role of the federal government.” Instead, the proper role as Midgley envisioned it was to create infrastructure that would enable all stakeholders to share valuable information and resources in a non-centralized, open way.

In short, the Learning Registry has created open application programming interfaces (APIs) that allow publishers and others to quickly publish metadata and paradata about their content. For instance, the Smithsonian could assert digitally that a certain piece of video is intended for ages 5-7 in natural science, aligned with specific state standards. Software developers could include algorithms in lesson-planning software systems that extract, sign, and send information, such as: “A third grade teacher used this video in a lesson plan on the bridges of Portland.” Browser developers could write code to include this data in search results and to increase result relevance based on ratings and reputations from trusted sources. In fact, Midgley showed the SETDA audience a prototype browser plug-in that did just that.

The virtue of this system comes from the platform thinking behind its design — an open communication system versus a portal — and from the value it provides to users from the very beginning. In the early days, improved discoverability of relevant content is a boon to both the teacher who discovers it and the content owner who publishes it. The APIs are structured in such a way that well-implemented code will collect valuable information about how the content is used as a side effect of educators, parents, and others simply doing their daily work. Over time, a body of metadata and paradata will emerge that identifies educational content; detailed data about how it has been used and interacted with; as well as rating, reputation and other information that can feed interesting new analytics, visualizations, and meaningful presentation of information to teachers, parents, researchers, administrators and developers.

Midgley called for innovative developers and entrepreneurs to take advantage of this enabling system for data collection in the education market. As the simple uses begin to drive use cases that shed increasingly rich data, there will be new opportunities to build businesses based on analytics and the meaningful presentation of rich new data to teachers, parents, students, and others who have an interest in teaching and learning.

I am delighted and intrigued to see the Department of Education leading with infrastructure over point solutions. As Richard Culatta, Education Fellow in Senator Patty Murray’s office, said to the audience, “When common frameworks are put in place, it allows smart people to do really creative things.”

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Related:

• Education as a platform
• Educational technology needs to grow like a weed
• How data and analytics can improve education

Level 1: Leveling up and questing

The first level is one where leveling, questing, and leaderboards can help motivate students to engage more with their schoolwork. Like a gamer who chooses his or her own path and pace to “level up,” a student will choose his or her own path and pace to learn a standard curriculum and be able to prove advancement to that next level through performance on tests.

The technology to be successful at this level exists today — the obstacle is cost, and the payoff is more students demonstrating success on state tests, closing the achievement gap. To work, this model calls for a mobile device with plenty of bandwidth for every student and software that lets the student level up at his or her own pace. The software can be an online course or something more sophisticated and engaging. The idea is that with software support to allow personalization for each student, teachers will have more time to spend with individual students and small groups to help them succeed with whatever unique challenges they are working on that day.

Despite the numerous challenges to achieve this level in reality, this is actually the easiest of the three levels.

First, this level is easy because objective standards of “better” exist — higher scores on standardized state tests. A school can try various online classes or drills, or adaptive software with its particular students, and standardized test scores will provide the data regarding what worked best for them.

Second, this level is easy because the technology infrastructure degrades gracefully — it still works even if students don’t have a device of their own. The first gains will come from just allowing students to work at their own pace on shared school computers. Since real schools are likely to have an uneven and years-long transition from the shared computer labs that most schools have today to ubiquitous computing environments, schools can make every penny count by creating an IT roadmap that supports self-paced leveling. In short, this will involve transitioning to cloud-based services as quickly as possible and increasing computer-to-student ratios and bandwidth as budgets allow.

Third, this level is easy because there are already processes in place for evolving the definition of “better.” For more than 40 states, current standards are being replaced by the Common Core Standards developed through an initiative by the Council of Chief State School Officers and the National Governors’ Association. The Common Core Assessments that are being developed to support these standards not only raise the bar for existing basic skills, but create assessments for higher-order thinking skills. By following their IT roadmaps, schools will be able to swap out current online tests for more sophisticated online tests over time, with no new technology architecture needed to participate in that continual improvement. If they have chosen cloud-based software that is easy to opt into and out of, they can experiment with new applications at will to see which ones best help their students perform on these increasingly sophisticated tests.

Level 2: Group collaboration

The second level is more like the World of Warcraft gameplay called “raiding” — group collaboration to achieve a shared goal. In Warcraft, that could involve downing a boss while in school it could be a collaboration on a book about local ecology. To the degree that work (or play) happens digitally, leaders (or teachers) can get rich insight into everyone’s contributions and participation.

This level is hard. First of all, there is no agreement on what these collaboration and communication skills should look like. Second, there are, consequently, no assessments for these skills available. Third, there is no software developed to interpret collaboration based on the digital tracks left by students working together online. Fourth, there are no standards for how to balance student privacy with such data collection.

For all these reasons, the full burden falls on the teacher to create shared goals for students; create collaboration environments; and observe, analyze, and measure their skills. Fortunately, the same technology architecture that supported the comparatively easy first level of personalizing learning (above), can support the teacher in these tasks. By using project management tools and shared authoring tools, such as Google Docs and wikis that generate histories as students edit their shared work, a teacher can get pretty good first-order information on the timeline and magnitude and quality of each student’s digital contributions. That’s a big improvement over trying to be everywhere at once to observe each group’s work.

Also, the same assessment groups that are working toward improved digital assessments for basic skills and higher-order thinking are also targeting 21st-century skills. If structured carefully, these digital assessments will also flow seamlessly into an IT roadmap for schools that is moving toward a ubiquitous computing environment.

Level 3: Play

The third level is less like traditional gamification and more about play. Rather than using Warcraft dynamics, it focuses on open-ended exploration — more like the game Minecraft. It already shows up in education through inquiry and the arts, and is more focused on developing questions than finding answers.

This is the expert level. This level confounds traditional approaches of measuring success — how do you measure the value of a question, or a journey, or artistic expression? If there are no outcomes that we know how to measure, then is the activity even a valid one for schools?

Still, teachers, critics and experts evaluate art all the time. Perhaps the artistic tradition of portfolios will serve the role of capturing open-ended student work that isn’t readily reduced to performance on a test. The student work itself, including student reflections on the journey of creating that work, may in its entirety be interpreted and understood by an audience of teachers, college admissions arbiters, employers, friends, family, experts and critics.

I’ve written previously about the notion of a student digital backpack wherein students and families own their data and which can include everything from test scores to rich digital portfolios. Although the need for standard privacy and data-sharing policies is as yet unmet, and the structure of such backpacks may not yet be fully conceived, the good news, once again, is that the technology degrades gracefully. An IT roadmap that includes cloud-based, student-controlled portfolios today will support a migration to systems that provide privacy management and evolving mechanisms for demonstrating achievements, performance, and student work in the future.

It is a fairly small technical shift, though a potentially significant conceptual leap, for schools to change from the current kinds of planning that tends to include lots of locally maintained servers and fixed computer labs to planning for mobile devices and cloud computing provided as a service to schools. Regardless of the hardware, software, and bandwidth a school currently has available, planning for this emergent infrastructure will provide critically needed flexibility over the next decade.

There are many examples that highlight this need, but the lens of gaming and gamification make a point that can be overlooked when discussing the use of technology in education: we learn best by doing, we learn best in authentic situations, we learn best socially, and we learn best playfully. These elements can be seen in the best classrooms, regardless of whether technology is involved — from gold stars for recognizing achievements, to students collaborating on a meaningful community project, to young people engaging in open-ended inquiry. The risk is that as we move to more digitally supported and mediated teaching and learning, these best traditions and practices might be lost. Thoughtful roadmapping of technology that supports both Warcraft-like and Minecraft-like student work can help keep these practices central.

Related:

• World of Warcraft and Minecraft: Models for our educational system?
• Gaming education
• Innovation, education and Makers
• The purpose of gamification
• Can standardization and innovation coexist in education?

Numerous game-like technology approaches for learning have been known to improve test scores among low-performing students. Computer-based learning that allows students to proceed at their own pace, to slow down and repeat subjects when they get stuck, to skip material they have already mastered, and to have a digital dashboard that lets them know how far they’ve come seem to help students stay more engaged — at least when combined with guidance and support from an excellent teacher. As these elements parallel many of the mechanics of games like World of Warcraft (WoW) it is not implausible to think of including them in both digital and brick-and-mortar learning in the hopes of creating significantly increased engagement and achievement on the part of students.

World of Warcraft and education

There are some powerful ideas in this approach, including the most common gamification mechanism: leveling up. Traditionally, students learn one day at a time. “What are the new example problems, and can I reproduce the process of solving them? What will be on the test?” In this model, the goal is the grade, not understanding, and the game is school. If done well, implementing a leveling-up metaphor can help shift a student’s mindset to one in which the game is learning and the grade is a side effect of getting better. “What do I need to understand in order to reach the next level?” Generally, this requires that the levels are awarded as indications of genuine accomplishment as opposed to being expected to have intrinsic motivational value.

Another common mechanism is “unlocking” new content: one can imagine a math curriculum being broken up into smaller modules that allow a student to choose what skills to “unlock” next, increasing ownership and autonomy in a way that is associated with increased motivation. “Achieves” (acknowledgement of having accomplished something significant) can motivate students to explore more widely. Leaderboards can stimulate competition and peer pressure to succeed. With careful design, the structure can create an environment that supports both intrinsic and extrinsic motivators for personal achievement using traditional gamification tools that parallel the leveling aspects of games like WoW.

Screenshot from “World of Warcraft Cataclysm.”

The challenge with the gamification approach as described so far is that it doesn’t address the whole story. What education has found over the past decade by incentivizing improved test scores is that those come at the cost of other forms of student achievement. For instance, a student who can achieve proficiency on a state math test may be able to solve rote problems and perform computation, but not know how to apply those skills to challenges in the real world that require higher-order thinking. More importantly, competency in these basic skills may not be enough to prepare a student for work in a global economy. There is a growing emphasis in education on 21st-century skills such as collaboration and communication — skills that advanced players of WoW must master in order to succeed in dungeons, battle grounds, and raids; those aspects of the game that require groups or teams.

Leveling up in WoW means solving problems (quests) and grinding (tedious monster-killing that gains experience points), and requires only basic skills. You measure success by your level, and you gain levels faster by becoming faster at questing and defeating monsters. The key statistic in how quickly a monster goes down is the “damage per second” (DPS) that your character can deal. Optimizing DPS is challenging and takes both practice and analysis, but in the end, great DPS only gets you so far. WoW is not just an online game. Like the real world, it is massively multiplayer, and much of the game, including all of the advanced gaming, involves working with teams to achieve challenging objectives. While statistics like DPS and others provide the minimum requirements for entry into advanced team gaming, you will only be able to participate if the rest of the group accepts you as a team member. This requires a more advanced knowledge of the challenges, collaboration and teamwork, communication, and other 21st-century skills. (The relationship between massively multiplayer online role-playing games (MMORPG) and 21st-century skills has been described for years by Marc Prensky and John Seely Brown.)

There is no point system in WoW to grade you as a team player — there is only your reputation. Other players include and invite you based on your value as they see it — a combination of your performance and their biases. Similarly, in school, there are currently no digital assessments that can predict the ability of a student to perform effectively on self-managed, collaborative teams once they enter the workforce, yet preparation for work or college is one of the top goals of K-12 education.

That’s not to say that there is no performance data available — it just requires human interpretation. In WoW, raid leaders download spreadsheets with data on every action of every character and its effect — data that is available because the game is digital. This data is used to determine the performance of the players and the effectiveness of their strategies. Combined with first-hand experience of collaborating with each player, this data can provide a well-rounded picture to an experienced raid leader. Analogously, in schools, one could imagine that digitally mediated group projects might yield data that would help an educator understand how a student was performing as a collaborator and a communicator. Of course, teachers do this without technology all the time; but with large classes and little time, they are exposed to only a fraction of the work and interactions that are actually happening in teams.

A personalized education can parallel WoW on two levels — in the first, a shared standard for success lets the student “level up” based on mastery rather than moving through the system based on seat time. In the second, shared common goals give the student the opportunity to demonstrate 21st-century skills such as collaboration and communication. But this interpretation of gamification still falls short of the big picture. Life doesn’t have the pre-defined goals at which these structures are designed to help us succeed; whether work does or not depends largely on the work environment, far more than on the nature of the work.

Minecraft and education

If part of college or work preparation also involves gaining experience and confidence with open exploration, curiosity, creativity, and following a hunch or an interest without knowing where it will lead, let’s shift our metaphor from Warcraft to Minecraft.

Screenshot from “This is Minecraft” video.

Like Warcraft, Minecraft is a virtual world with a few simple rules. In a nutshell, the world is littered with materials that can be used for building things, a “craft table” for making things from raw materials, and optional monsters to battle. Unlike Warcraft, there are no pre-defined goals. Players may create adventure maps with all kinds of goals and challenges for other players, and these are wildly popular, but conquering a map doesn’t get you points in a bigger game-wide contest.

Minecraft is about making stuff. Virtual stuff, but stuff nonetheless. It is also about exploration. In Minecraft, you can get lost and never find your way back, in which case your best option may be to cut your losses and move forward. In Minecraft, players make elaborate buildings, works of art, performance art (see the TNT videos on YouTube), and mini worlds and challenges for other players. Games like Minecraft can offer us a perspective on balancing the goal-based solving of problems with the open-ended finding of valuable questions — a skill education will need to provide to every new global citizen.

If there are things to learn from the notion of gamification, let’s apply them at multiple levels, not superficially. We can learn from levels and leaderboards to add intrinsic and extrinsic motivators to help motivate students to succeed at traditional state standards and tests. We can learn from the structure of the human dynamics in massively multiplayer games to value and capture collaboration, communication, and other higher-order skills needed to achieve collective pre-defined goals. We can learn from simple rule-based (as opposed to goal-based) games to value and preserve the artifacts of exploration as well as its end products.

Related:

• Gaming education
• Innovation, education and Makers
• The purpose of gamification

Having flown directly from Maker Faire in the Bay Area where girls and boys were both deeply engaged in all kinds of tinkering — from making spinbots to sewing to crafts to soldering — it was a pretty interesting cultural shift to attend a conference dedicated to overcoming the gender gap in computing and engineering. It seems counterintuitive that a field that has such an egalitarian, merit-based culture and ethic as computer science should be so overwhelmingly composed of men.

For many reasons (arguments range from equality and human rights to economic necessity) industry and the field of education have been working for decades to increase the representation of women in the engineering fields. Industry has looked to issues such as equal pay, women-friendly cultures, and benefits such as improved maternity leave and flexible working hours. Educators have focused on making science, technology, engineering, and math (STEM) courses more attractive to young women, and to actively recruit young women into these fields.

Alongside these top-down efforts to actively increase the number of women in tech careers, the grass-roots, bottom-up maker movement has been quietly attracting tinkerers and DIY-ers of both genders. At Maker Faire, 100,000 folks got together to share projects, skills, and materials for making. The maker culture thrives on open sharing of techniques and knowledge and innovation, often leveraging open source software and open source hardware. In a perfect example of what John Seely Brown refers to as “Pull,” thousands of people are enabling themselves and each other to create freely using tools from the medieval to the hyper-modern. The goal is to make things: for their own sake, for utility, for artistic or technical exploration, but the side effect is the creation of a wide variety of the actual makers, themselves.

It turns out that the context in which technology is presented has a large effect on how attractive it is to each gender. At the risk of gender essentialism, it seems that often boys are attracted to robot battles while girls are attracted to robots as a means of helping the disabled, for instance. Boys are attracted to competitive video games while girls are attracted to social software. In making, there are such a variety of materials and ways to participate that the appeal is much broader than traditional technology contexts. I spoke briefly with Dale Dougherty at Maker Faire and noted that both boys and girls would happily solder or sew in this environment. Dale pointed out that with the large number of entry points, a very broad set of people are attracted to making. These people then find it easy and enjoyable to move around within the various approaches and technologies.

Sylvia Martinez, president of Generation Yes, advocates strongly for bringing this approach into formal education. At the NCWIT panel she talked about how her organization trains young people in schools to serve as in-house tech support. From manning genius bars to maintaining the school’s hardware and software, these young people have the opportunity to become leaders and explorers in the use of tech within their schools. Around 40% of the students who participate in Generation Yes projects are young women — roughly twice the representation of women in industry. Sylvia also spoke about Seymour Papert’s theory of Constructionism, essentially that children learn by doing. In the same way that professionals become expert as a side effect of doing their jobs, and makers become expert as a side effect of creating things, students learn both the complex skills of collaboration and innovation and communication as well as the hard skills of reading, writing, and ‘rithmetic through doing meaningful, hands-on work.

Tony DeRose, lead of Pixar’s Research Group and founder of the Young Maker’s program, talked about how the time outside of school allowed young people the freedom to experiment, get things wrong, go down dead ends, recover, and move forward. As in real life, where there is no single right answer and where trying something new has risk, Young Makers have the chance to experience the gratification of genuine accomplishment through innovation and perseverance.

It seems much of the power of making is in its hobbyist timescale. There is time for the rhythms of hard grinding work and periods of flow, for brainstorming, collaboration, disagreement, and persistence. There is also tremendous learning about technologies, techniques, and materials that are far more authentic than most college courses. It provides lessons that stick because they are learned in a context of doing, rather than just listening.

Tony founded the Young Maker organization more than a year ago, bringing together young makers, mentors, and experts to support young people in truly ambitious projects. In the first year, 20% of the participants were young women, in the second year 40% were. Tony notes that in his experience so far, the young women are motivated by working together and the young men by doing “dangerous things.”

The final NCWIT panelist was Leah Buechley, head of the High-Low Tech Program at MIT’s Media Lab. Leah and her team have been researching how people combine high-tech and low-tech materials, such as electronic circuits with fabric for e-textiles, or conductive paint with paper. They developed the Lilypad Arduino, a washable, sewable version of the open-hardware Arduino microcontroller, and observed what kinds of communities adopted each of the technologies. Once again, the evidence suggests that the context in which technology is introduced is tremendously influential. Leah’s research showed that out of all Arduino projects, only 2% were created by women vs. 86% men and 12% unknown. For the Lilypad Arduino those numbers were 65% women, 25% men, and 10% unknown.

The maker movement is powerful on many levels. As with any important meme, it has powerful side effects, in this case as a welcoming culture and appealing invitation to technology for a broad audience that includes both women and men, seniors and kindergartners, technologists and artists. In the end, perhaps the most meaningful thing created by the maker movement will, indeed, turn out to be the new makers who find the tools, culture, and inspiration to create in new ways within its community.

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Fundamentally, the use of Internet-enabled technology in classrooms has two challenges. The first is student safety and privacy — preventing information that is obscene or harmful to children from being accessed by the devices. The second is classroom management — focusing student attention on the task at hand rather than the myriad distractions of the web.

With laptops, these challenges are addressed by classroom management software that provides Internet filtering and control of the student computer screens. Teachers have the ability to put all the laptops on the same page, project a single student’s screen on the whiteboard to show their work, or to shut down student screens altogether. Internet filters allow schools or districts to create “white lists” of websites that students are allowed to access and to block the rest.

Of course, none of these services are foolproof — the Internet has numerous sites dedicated to helping people hack around these restrictions, primarily in support of human rights in countries where Internet access is censored. Go into any middle school classroom and you will find any number of students who can readily get out onto the Internet beyond the filters. You may even find teachers who rely on these kids to sneak past the filtering walls if they do not have the time to make an IT request to have a site unblocked for the day’s lesson.

The philosophy around Internet filtering and classroom management varies from school to school and district to district. In some settings, the Internet is considered too dangerous to leave in the hands of students and the school chooses a limited set of sites that students may access while teachers tightly control the use of computers in the classroom. Other schools feel the same burden of responsibility to help students develop the skills to successfully navigate the Internet that they do to help students develop interpersonal skills in the classroom and on the playground. Their philosophy is to have adults model those skills, teach them explicitly, then to monitor students as they try them out, make mistakes, and learn — ready to step in when they are needed.

Just as students gain more freedom as they become more mature in the physical world — such as choosing coursework, leaving campus for lunch, or taking on internships — they gain more freedom on the Internet as that becomes developmentally appropriate. These students are expected to be as prepared for navigating the virtual world as young adults graduating high school as they are the physical world.

The first approach relies more heavily on controlling the student Internet experience. The second relies more on appropriately monitoring student Internet use. Laptop technology supports both approaches. But cellphone technology often does not. If that one thing were to change, educators would have the tools at hand to use always-on, always-connected devices for anytime / any place learning. If this change doesn’t come about, the potential of wireless education technology will sadly remain limited.

I had a really good conversation with Ben Weintraub, COO and co-founder of Kajeet, on this exact topic. Kajeet is a Mobile Virtual Network Operator (MVNO) that focuses on cell phones for children. An MVNO is essentially a reseller of cellular minutes and megabytes that also has the ability to sell added services on top of connectivity.

Not surprisingly, parents have many of the same concerns as schools when it comes to their kids’ Internet use. In response to these parent needs, Kajeet provides services that let parents control when their kids can use the cell phone, who they can text or talk to, and what phone features (such as the camera) they are allowed to use. Recently Kajeet has been talking with Netsweeper, a company that provides a cloud-based approach to Internet filtering. With all these pieces in place, there is only one technology obstacle blocking cell phone use in schools: in order for Internet filtering to work both when the phone is using cellular services and when it is using Wi-Fi, the phone needs to be “locked down” to ensure that all Internet access is authorized by the Netsweeper (or similar) service, regardless of the access network.

Unfortunately, MVNOs, carriers, and software providers who are interested in solving this problem don’t have access to the layers of the cell phone software stack where this kind of secure lock-down can occur — they lie below the level of the High Level Operating System. It’s up to the manufacturers of phones or their chip suppliers to respond to the need for cell phones that are kid-safe and school-ready. As the costs of smartphones are coming down drastically, these devices are finding their way into the hands of younger and younger users. As an industry, we have a responsibility to make it possible for parents and educators to have Internet safety tools on computers and phones alike.

For the wireless edtech ecosystem, this really does appear to be case where “for want of a nail, a kingdom is lost.” For want of one enabler, the potential of wireless edtech may either be drastically inhibited or lost altogether.

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The question came up during a great conversation with Matthew Rascoff of Wireless Generation about personalizing the educational experience. He was making the point that information about students is lost every time they change schools, making it impossible to use data for personalizing learning the way we personalize our music, video, and reading experiences using Pandora, TiVo, and Kindle.

Personalization is the holy grail of education technology, but it can’t be achieved without mechanisms for rich data about each student’s learning. And that data must be persistently stored and appropriately accessible. Matthew neatly turns the traditional metaphor of a “digital locker” on its head by replacing it with the “data backpack” — a container that goes everywhere the student goes.

Matthew’s insights led me to Wireless Generation’s white paper on “An American Examination System.” The paper outlines a platform for using technology to collect and store data on individual student performance. With this rich data following students, teachers will have the data available to know what students need to work on or learn next. The data can become the basis for “adaptive mass personalization.”

What I particularly like about this vision is that it is designed with nicely partitioned layers: beginning with the technology and protocols for data collection and sharing, moving to a format for encoding a hypothesis about an optimal set of learning trajectories, moving to an automated and rich layer of high cognitive demand tests, and supported by grading mechanisms that are automated where possible, and draw on networks of graders where appropriate.

The idea is that by using technology, standardized tests can be graded by any teacher anywhere, not just a given student’s classroom teacher. With this sort of expert crowd-sourcing, the community of teachers can become much more consistent in their expectations, and minimize the variation in grades that comes from the subjective nature of evaluating creative work.

Because the layers of functionality are segregated, this vision represents a meaningful platform approach to what I consider to be the absolute core issues for reinventing education: testing and assessment.

Standardization is what makes a platform powerful. Railroads are a platform for the transportation of goods and people because all tracks are the same size and all trains can ride on any track. This means there’s an the opportunity for innovation regarding different kinds and models of trains, speed and efficiency improvements, business models for transporting goods, etc. Over time the train tracks and systems have come to support another layer of standardization — containers — that allow goods to be efficiently transported across railways, trucks, and ships. If that second layer of standardization had happened at the same time as the first, the resulting standards would have been far less efficient for the mass movement of goods than those that exist today. If business model competition didn’t happen, the economic environment that made container standardization so powerful might never have developed.

When technology products seek to become platforms, they often look to lock up the value chain from top to bottom by standardizing every layer according to their own product’s protocols. They “open” the top API layer to entice others to choose their platform. I’ve often heard this informally referred to as the “build it and they will come” strategy by those who are skeptical of it, and a “vertical integration” strategy by those who are fans.

In industry this plays out in the debate of “open” vs. “closed.” Is the iPhone closed because of the many layers of the platform Apple controls, or open because of the breadth of innovators who can try their products on top of Apple’s API’s? Android embraces the idea that an architecture standardized at a lower layer will breed more innovation and eventually lead to global domination over the siloed Apple stack. The question of which layer to standardize in a cell phone platform is an open one and the economic implications of choosing the right layer are vast.

In the area of education technology, this question of where to standardize is even more critical. Whereas in industry, competing platforms will eventually answer the question of which approach generates the most innovation and success, in education, early decisions about platforms will become institutionalized and almost impossible to change for decades. This is a critical point to consider as the US Department of Education, governors, and chief state school officers all are investing heavily in a vision of the transformation of schooling through technology.

If standardization happens too far down the stack (say, below the level of student data flow protocols), the market will continue to be fragmented and there will be significant barriers for education innovations to reach students at scale. Innovators will essentially be selling school to school and district by district. If standardization happens too far up the stack, areas that are still immature in the field will become cast in concrete and innovation in those areas will be unlikely.

With a platform structure for education, the key question becomes what to standardize in order to enable wide adoption of innovations, and what things must be deliberately and specifically not standardized in order to allow new innovations to flourish.

Using assessment platforms as an example, the Wireless Generation White Paper highlights a specific theory for students’ learning trajectories in math, yet at the same time provides a structure they refer to as a “honeycomb” for specifying that theory. If the field were mature in its understanding of learning trajectories, the suggested trajectories could be a useful place to standardize. But given that competing learning trajectories are still emerging, the honeycomb structure instead provides a well-defined place for critical innovation.

Platforms are valuable precisely because of what they do and do not standardize. Widespread standardization is difficult to accomplish, but critical to realizing the potential of technology in reinventing education. Wireless Generation has an intriguing framework for such a platform (which is probably why it was just acquired by News Corp. for $360 million). With the resources of News Corp. joined with the innovative platform approaches of Wireless Generation, standardization at the right layers is a real and compelling possibility. It will be fascinating to watch this marriage unfold.

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At the Gov 2.0 Summit, Deputy Director for Policy for the White House Office of Science and Technology Policy,Thomas Kalil, referred to the challenge of educational software that improves the more students use it.

What would it mean to talk about a whole school system that improves the more students use it? I’ve heard the Department of Education’s Steve Midgely refer to school as a service and education as a platform — why not apply this kind of systems thinking to the Gordian knot of our education system, using the Internet as a lens and a platform model?

Applying the Web 2.0 model to education

The Web 2.0 model can be applied to education on two levels. The first is at the level of software that provides or supports educational experiences. The second is at the level of the human systems and workflows that are entailed by the day-to-day work of educators and students and citizens.

As a veteran software organization leader and management geek, I see deep parallels between the architecture of software platforms and that of human organizations. For example, in both cases, the question of quality has moved from “does it work as designed” (which is now considered table-stakes) to “is it designed to do the right thing?”

A software program that works exactly as intended but isn’t useful to its end users is a waste, as is a team that is executing to the letter of a Statement of Work at the cost of the real needs of its multiple and diverse stakeholders. So is an educational system that mass-produces graduates who are prepared for an agrarian/industrial economy when they will have to live and work in an economy powered by knowledge, collaboration and creativity.

One possible criterion for education as a platform is whether the underlying services can be mashed up to serve different sets of goals. As Clayton Christensen, Curtis Johnson, and Michael Horn outline in “Disrupting Class,” our educational system was originally created to prepare the elite to rule, then to prepare all people (or at least white men) for informed citizenship, then to provide all students with an equal opportunity to prepare for college or careers, and now to prepare every child for higher education. These changing goals have strained the current school architecture to the point where any number of responsibilities that schools have traditionally considered important, such as vocational training and the arts, are now being dropped in favor of “the basics”. There are many who argue credibly that the goals of school ought to go beyond the basics to include modern work-force preparation (learning how to learn, collaborate, invent, communicate, etc.) and global citizenship.

By this criterion, the inability of our education system to accommodate these multiple and shifting goals suggests that it does not have the architecture of a platform (at least not a well-designed one). “Disrupting Class” suggests that, much as the web disrupted many traditional business models, technology in the form of online learning will disrupt school. The argument is that computer-aided education and online learning will be welcomed into schools as a low-cost way to provide services they otherwise couldn’t afford. These new offerings may be paid for by parents or schools and may give students school credit. Although the technologies will initially be very poor substitutes for classroom teaching, they will be much better than nothing and the schools will welcome them as they lose the resources to provide these services for students in traditional ways. Over time the technologies will continue to improve until they revolutionize what teaching and learning look like.

This disruptive mechanism has intriguing implications for education as a platform. First, critically, given the assumption that technologies are going to improve, there is an implicit feedback loop driven by criteria for what “better” looks like and that allows publishers and providers of educational services to continually adapt and improve — more on that later.

Second, there is an implicit design approach that eschews traditional top-down, requirements-based engineering and assumes that the complex solutions that will someday serve education begin with very simple systems that then evolve in the market, much in the way the Internet evolved from the simple TCP/IP stack rather than the complex, traditionally designed OSI stack.

Third, I infer that innovation demands multiple, varied providers of computer-aided and online learning, which in turn calls for a layer of standardized interfaces, API’s, and delivery mechanisms that make it easy for great education innovations to spread virally in the way popular Internet innovations do.

Defining “better”

These implications for the content and software infrastructure of Education 2.0 translate in interesting ways to the parallel pedagogical and human infrastructures. First, and critically, in order to establish positive feedback loops for the work of students and educators there needs to be a set of criteria for what “better” looks like. Metrics in this area are the absolute crux of education reform and poor metrics are a major contributor to how innovations are damped out in the education system — again, more on that later.

Second, my own experience in leading large software organizations suggests that traditional hierarchical, silo’d human systems are inefficient and resistant to change, but that they improve dramatically when restructured to support self-organizing teams. Self-organizing teams are the organizational equivalent of “simple systems” — they evolve to support complex work with extraordinary capacity and adaptability. One key to self-organizing teams is to set goals (or in the language of emergence, “simple rules”) that drive positive feedback loops — such as “be the school everyone wants to transfer to”. Another is to remove constraints from the systems and allow for greater autonomy and innovation on the part of each member of the team. In industry, a classic example is to reward people on the basis of outcomes rather than seat time (great code doesn’t care if it was written in a suit from 9-5 or in pajamas at midnight.) What if students could advance based on outcomes rather than seat time in the classroom, and teachers were rewarded for many dimensions of student achievement and professional contribution?

Third, I am of the opinion that the distinction between formal learning (school) and informal learning (museums, Internet, community classes, affinity groups, etc.) is one that is both artificial and obsolete. In Education 2.0 there should be multiple providers of educational experiences, and standard discovery mechanisms that allow great experiences to spread virally as well as standard ways to give students credit for what they know and can do rather than for what classes they’ve sat through.

Student achievement beyond a test

There is broad agreement that testing in our educational system is fundamentally broken. Today, our educational feedback loops are driven by “the test” — state-wide standardized tests in the basics that are used to assess whether every student is able to perform to a certain lowest common denominator. Collectively, the results of these tests are used to grade schools and determine whether they will continue to receive funding. Indirectly, attempts to reward teachers for performance are often based, in part or whole, on student performance on these tests.

The unintended consequence of using student achievement on “the test” to define what “better” looks like is that the feedback loops in the educational system will damp out work and innovations that aren’t measured at the lowest common denominator. In some cases, teachers will spend up to half the school year in “test preparation”, which doesn’t leave time for any learning above and beyond the basics. There are horror stories of mathematically rich curricula developed at great expense and with deep thoughtfulness under National Science Foundation funding that aren’t adopted because much of the mathematical depth that students gain from it is not reflected by “the test”. There is a disservice done to teachers who are faced with extraordinary obstacles, such as teaching students who come to school hungry or fearing for their safety, or teachers who create extraordinary learning environments where students learn to create and collaborate in ways that are not reflected by “the test.”

Education as a platform must support vibrant innovation in the area of metrics. States, assessment publishers, web start-ups, researchers, parents and teachers must be able to experiment with different ways to measure student achievement, and, indeed, with what things are important to measure. In a world of assessment innovation, a student portfolio might contain a combination of completed projects in addition to state test results, richer third-party assessment results, and innovative assessments of non-traditional skills such as collaboration and creativity. Colleges and employers might value this multi-dimensional view of a student more than just grades and standardized test results when evaluating applicants. Parents and students might take ownership of enriching their portfolio of assessments according to their own values. Publishers of curriculum and educational experiences might be able to improve their offerings based on a broad set of assessments of student outcomes — driving innovation in educational content. Administrators and states might be able to reward teachers for many different kinds of critical achievements.

What kinds of services would comprise an education platform that encourages innovation around metrics? Certainly data science is key — instrumenting how students and teachers interact with technology and digital content and capturing that data according to open standards; storing and cleaning that data with appropriate privacy considerations; performing data mining, analytics, and analysis of the data; and creating meaningful visualizations of the data are all areas that can be both services in support of education as a platform as well as areas for innovation in their own right. The data itself will be a sort of national treasure — the key to understanding what works and what doesn’t and the fuel for innovative services and applications.

Also key are mechanisms for discovering quality assessments — Web 2.0 mechanisms of crowd-sourcing, peer review, and rating are commonly invoked for sorting out the best of the best when there is an explosion of innovative products available. But to date, much education-related crowd-sourcing has assumed that teachers will voluntarily rate and recommend educational products. With the burden that teachers are already carrying, that additional volunteerism is not a realistic expectation. Fortunately, there are two communities that might well provide data on products either because they are motivated or as a side effect of using them: education researchers and families. How will education-as-a-platform leverage these communities? Are these the same mechanisms required for discovering exceptional educational experiences?

These kinds of services from the technology infrastructure also serve the human infrastructure. With educators, administrators, and schools using a much richer metric of “better” than state test results, the same feedback loops that currently damp out change can instead drive improvement. Schools (and informal learning channels) can differentiate themselves by offering educational experiences that support the learning goals of each student — as reflected by the unique portfolio that student is building. Schools themselves can actually “get better the more people use them.”

But how can these hypothetical innovative approaches to metrics (or for that matter curricula, pedagogy, digital textbooks and games or other innovations) spring up in a cumbersome, over-constrained system like our schools? Probably not through top-down design or national mandate. Perhaps, like online learning, an assessment ecosystem will have to evolve outside those constraints — where there is currently no or little competition. Perhaps parents and students looking to have a more complete picture of a child’s skills and strengths and gaps will be the initial market for innovative assessments. What parent doesn’t want to understand their kids’ achievements in a deeper way than letters on a report card? If a wealth of affordable multi-dimensional assessments were only a click away, how many families would use them and in so doing help make them better? Perhaps, like online learning, innovation in assessments will, in the best way possible, disrupt school and class?

Photo credit: teacher’s eye by HoQ-10, on Flickr

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Last year, High Tech High performed an extensive search for a computer-based system for learning math, in particular to drill students in areas where they needed more practice. They found that the ALEKS intelligent assessment and tutoring system was the best fit for their particular needs, but budget cuts kept them from obtaining the software for more than three or four classrooms. Ben Daley, COO and chief academic officer of High Tech High, explained how ALEKS captivates students by giving them simple feedback in the form of pie charts that represent how thoroughly they have mastered a given topic. It’s just a report, but there is a serendipitous magic in smart experimentation — in this case, presenting information in a certain way changed students and inspired teachers.

It turns out that, simple as it is, students get pretty serious about getting their pie charts filled out. The smart design of the ALEKS math programs also does a good job of giving students math drills, feedback, and help that is at the right level for what they know, making them highly independent in making progress. Although they are still in the preliminary stages of analyzing the data, the teachers at High Tech High were surprised by the increase in student achievement when kids were turned loose on the ALEKS system. The administrators were surprised to learn that although only a handful of licenses had been purchased, ALEKS had spread through the school like a virus as teachers talked to each other about what they were seeing in the classroom and found creative ways to finance additional licenses.

This story presents an interesting counterpoint to the recent emphasis on using technology primarily in developing 21st century skills such as collaboration, creativity, critical thinking, and communication. These “higher order” skills are associated in the education dialogue both with students taking more ownership of their learning through access to rich original source material and collaboration via the Internet, and with students learning through solving authentic problems or working on long-term cross-disciplinary projects that more resemble the work of professionals than traditional lecture/worksheet/multiple-choice-test schooling. The notion of “computer tutors” echoes back to the unrealized ideals of Artificial Intelligence from the 1980s, and the success of intelligent tutoring systems suggests that there is something important in traditional, time-intensive individual practice. Yet, it also evokes a distasteful undertone that the complex role of a teacher can be reduced to a set of algorithms impersonally enacted by a machine — the absolute antithesis of the teaching environment at High Tech High.

Drills, chunking, and attention to spare

Perhaps there is some reconciliation of these ideas in the nature of expertise-building and the quirks of the human brain. When it comes to logical problem solving the human brain is brutally slow, linear, and limited. Our minds can only reason with the building blocks we are able to hold in working memory, which for most people is about seven items (not coincidentally the number of digits in a phone number.) When we are novices in an area, such as when learning to drive a car, it requires all our attention to take our foot off the gas, push in the clutch, push on the brake, put one hand on the gear shift, move the gear shift up and to the right, and turn the wheel with the other hand. By the time we add in glancing in the rearview mirror and watching out for pedestrians, our working memory may well overflow, causing us to stall the car or get into an accident. With practice, through repetition, all of these separate actions get “chunked” together in long term memory, and making a right turn gets simplified to a single integrated action. Eventually, the complex actions of driving become so automatic that we sometimes bypass working memory altogether and find ourselves waking up at our destination with no real memory of having driven there.

This chunking and automatizing frees up our cognitive resources when performing mundane tasks. We now have attention to spare for other things. An experienced driver might choose to focus this attention on listening to the radio, talking with passengers, or thinking about work. An expert driver, however, uses those resources to become a better driver — having mastered the art of the right turn he or she begins to master the art of defensive driving or perhaps race-car driving as a true professional, putting all his or her attention on increasingly sophisticated nuances of expert driving. Similarly, as an expert in any field gains experience, elementary ideas get chunked together into a single concept. As the concepts held in working memory become increasingly complex, the expert can address increasingly complex problems. The more information working memory can hold, the more room there is for multiple constraints and real-world variables and the less a problem has to be simplified to be tractable.

Athletes and musicians drill endlessly on simple tasks that are fundamental to their field. Coaches ensure that the drills are performed with proper form since it takes far longer to unlearn a bad habit than to learn a good one. Martial artists practice katas for years that eventually become the subroutines they automatically execute during competition and sparring. Does drill play a similar role in math and other learning? Is it necessary to free up working memory from the mechanics of addition and multiplication in order to solve problems in algebra? Do the patterns of algebraic manipulation need to be chunked into long-term memory to free up attention for a problem in calculus? What is the role of drill in math, and is it one a computer can provide better than a teacher?

If we view a teacher as a coach or a sensei, then software takes on its proper role as one of many tools available to teachers and students. With human guidance to ensure students are gaining understanding and with software tools to drill that understanding into automaticity, it is possible to structure learning so that every student can advance at his or her own pace. Individualized learning is far more efficient than when students are required to learn in lockstep, listening to the same lectures or completing the same assignments regardless of whether they have already mastered the material or are hopelessly behind. Self-paced intelligent tutors can help students learn more independently, more quickly, and more deeply.

How will mobile and 24/7 connectivity change learning?

At High Tech High, the reason for turning to intelligent tutoring systems is simple: if they help teachers enjoy a coaching role that supports kids in learning basics more independently, it gives them far more flexibility in how teachers spend precious classroom minutes. High Tech High has applied for grants to provide students and teachers with mobile devices that are connected to the Internet 24/7 via mobile broadband. In large part, High Tech High is exploring how technology can support anytime, anywhere collaboration within communities of learning, but they will also experiment to see how intelligent tutoring systems have an impact in the snippets of time available to mobile device users — beyond the results they see with students using the software only in the classroom. They suspect that 24/7 connectivity will support and enhance the human connection in learning. If it also lets kids move through curriculum basics more quickly or more independently outside the classroom, it gives back something the High Tech High community never has enough of: more time for cross-disciplinary, collaborative projects that build higher-order skills and ground the basic curriculum.

The High Tech High programs will also give the education community something it doesn’t yet have enough of: concrete data. Does anytime, anywhere learning with technology help teachers and students be more efficient in what they already do? Does it enable new ways of learning? How should those two different goals be balanced to leverage great teachers? What approaches increase community versus fostering isolation? There are countless opinions and plausible theories. Leadership like that at High Tech High will provide the data to ground the debate.

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