The concept of the education “fog” versus the consumer “cloud” struck me as an effective way to metaphorically frame the confusion about technology, information and knowledge in education. Ed tech stands in stark contrast to the extraordinary use of data mining, online identity and social networking going on with every key stroke we take on the Web or over our smart phones and tablets.

The fog versus cloud metaphor begins by pointing out that schools don’t use information and data in the same way that consumers or companies do; but it goes much further, by highlighting that consumer systems know so much about individual users and their activities within particular areas. Such systems share the benefits of that knowledge with the consumer in the form of recommendations. Product companies, data aggregators and advertisers correlate these data in real time, usually to try to sell something or make a connection.

What if the thing that is being sold, or the connection being made, became learning or “understanding” in an educational framework? How would we know if each student was gaining understanding? Right now, even with the best use of the Common Core Standards and No Child Left Behind, we could not know this for every child. The reason for this is that schools are organized to manage classrooms. They are only concerned with individual students (in the deep data sense) when a teacher takes an interest or when the school is legally obligated to do so as required by Federal or state law.

While we aspire for universal education, we are a long way from it. Yet, in the age of the Cloud, there could be universal access to learning that can be used as part of a student’s education, and that can, hopefully, generate measurable “understanding.”

At NLET, we are invested in improving three things – individual learning, system efficiency and knowledge access. We think these are fog-piercers. We think every student, and their families or mentors, should see their data loop back to them, not travel off to the State and not merely used to inform each student about his or her learning or to build an individual plan at the school. We are in the age of data-mining. Why not have those effects delivered to each student?

NLET is in process of establishing a Silicon Valley Education Research & Development Center to get at these issues. We would like to see parity between the tools of the Valley and the tools for learning. The Silicon Valley Education R&D Center will bring together university researchers, high tech companies, school districts and other non-profits to start the process of getting learning on an equal footing with the rest of our lives.

Please keep an eye on www.NLET.org for developments, and contact us at info@NLET.org if you are interested in getting involved.

We created NLET to deliberately operate at the intersection of the old and the new and of the political and the possible. The old and the new has to do with the difference between a system designed for the manufacturing era, our current system, and a new one designed for the knowledge economy and information society, where kids and adults tend to reside. The political and the possible is another dimension that acknowledges that education is intensely political – politics all the way down from the governor to the PTA. The possible has to do with what is actually needed, what is real and what can make a difference for learners.

The idea of a national laboratory for education transformation grew out my contact with several NSF projects in the mid-1990s, just as the Web was coming into existence, and from early discussions about the National Digital Library. Meeting Chris Dede, then at the NSF, now at Harvard, and Jack Wilson, then at Rensselaer Polytechnic Institute (RPI), now president emeritus of the University of Massachusetts System, opened my eyes to the Federal efforts to promote STEM learning. I watched the idea of the National Digital Library fail to gain ground, possibly because technology development was outstripping the ability for large committees to act on change. I participated in and saw fabulous projects created by NSF grant-funded teams, but then these tended to go fallow as the grants ended.

On the commercial side of the equation, I worked in the education technology industry and saw the mismatch between corporate product and institutional need. Also, it seemed students were continually, almost deliberately, being left out of the process of change by nearly all the other participants. “They” were on the receiving end of the ideas of adults. Likewise, as data collection and analysis gained ground under NCLB, I saw the data flowing away from the student. This is the opposite of what happens in most other modern uses of data where end users, by definition, are actively involved in their own activity and socially with others.

So, I began to be puzzled as to why, in a country as rich and inventive as the U.S., we would not launch what was the equivalent of a “Manhattan Project for Education.” Why not pull the issues apart, go down to their roots, ask the primary and First Principles questions – just like scientists do?

The missed links between the life of knowledge, the state of technology, and the reality of school present a challenge that needs a solution, no matter the difficulty. In 2009, I helped arrange a think-group with some of the very top people in education from academia, foundations, research institutes and corporations. However, the future of education did not spring to life from this gathering. Instead, what became clear was a simple truth: it will take a community to re-build education. That community cannot be made up of just the “best people in education.” Nor can it be a single school district, one charter organization, or a single state. The stakeholder group has to be much wider and the participation much deeper. While the scientific and engineering communities continually ask for STEM capable students, their participation in creating those students is mostly ad hoc, non-scalable, and episodic. The reason for this is that they are not using their core capabilities to look at education as a re-design issue based on solid science and proven theories of scaling. Why not bring these into the equation?

In late 2010, as a participant with other education technology advocates, I brought these ideas into a new non-profit in New Mexico. When in New Mexico I became reacquainted with Kurt Steinhaus, Director of the Public Programs Office at the Los Alamos National Laboratory, and Steve Stringer, a creative technology transfer officer at Los Alamos. Los Alamos was, of course, “the” Manhattan Project lab. Along with Lawrence Berkeley National Lab at the University of California Berkeley, they heralded in a new age of science and the end of World War II. Kurt had been the Governor’s education lead in New Mexico, had been chair of the leading education technology organization worldwide (ISTE) and was at a Lab. We began to talk about the need for a strategic education R&D effort to address the strategic learning deficit in the country. Through a separate connection, I met Michael Chartock, recently retired from the other Manhattan Project lab. Mike helped me think about building the kind of research and development organization that NLET could become.

At that point, two and a half years ago, the concept for NLET was born. It was clear that the focus was to look to the future: to use tools and methods from outside the traditional world of education research, practice and policy; and to involve the real stakeholders who need highly educated workers, or who are individuals who need to be highly educated. This mission is purposely more future-oriented than most other education improvement and reform efforts. The reason for this is that other efforts steeped in fixing the past are not working at scale nor have they been able to equitably distribute education and learning opportunities. Given the enormity and complexity of the task, these efforts simply have not had the right people or organizations in the education transformation conversation.

In short order, it became clear from my contacts that there was a growing group of people interested in collaborating on using new methods to analyze the current system, to include the student in the change process in a more fundamental way, and to start a redesign capacity that would survive after the legion of individual grants sunset.

Two gifted and insightful people in the San Jose Unified School District, who built an incredible data culture and involved the community in critical choices for the district, joined with me in planning NLET. So did Paul Resta, a veteran of the national and international efforts in large-scale education change, who operates the learning technology center at the University of Texas Austin. Along with Bill Flores, President of Downtown Houston University, we formed the founding Board of NLET and in 2011 incorporated as a California non-profit corporation.

We then signed memorandums of understanding with Paul’s center at UT Austin, with Los Alamos through Kurt, and with UC Santa Cruz with Rod Ogawa, whose center is focused on serving the under-served. Along with our lead researcher Michael Strong, formerly with the New Teachers Center in Santa Cruz, we conceived of (and UCSC and Paul’s center applied for and received) an NSF grant to build a new computational “agent-based” modeling capacity for analyzing student success factors in math as the students flow over time through a test district. We have submitted several more grants to the NSF within our goals of: improving individual learning, creating greater system efficiencies, and fostering easier access to knowledge.

As we open our website to the public, our numbers have grown and involve numerous advisors from around the country who represent the various branches of science that we believe need to be in the transformation conversation. These branches include neuroscience, information systems, organizational theory and economics. We also hope, as we grow, to attract a new kind of investor – those interested in helping to design new systems for learning, consistent with the times, and in involving the broad community and the students. The change that NLET is fostering is difficult, political and time-consuming; but it can also be exciting and engaging, and it will light a new kind of fire in the country.

This meeting provided a crucial kick-off to the project’s core work – to create a predictive educational model and an effective and efficient simulation that demonstrates whether scientific modeling can be an effective tool for decision-making and support for the education community by generating accurate predictive models of student performance trajectories.

In order to accomplish the projects work, this meeting set the stage. Both the technical specifications of the model and the simulation were discussed and well as role of project management. A Gantt Chart will be carefully maintained throughout the life of the project. Regular status updates will be submitted to the Project Manager regular communications will be conducted via email or conference calls.

Thirteen years ago, I was asked to give a seminar at The Third Annual Global Village Schools Conference in San Francisco on “Education for the New Millennium.”  The topic I chose was “Reform vs. Reengineering.”  The question to be addressed was:  Have schools reached the point where radical changes from reengineering are needed or are we satisfied with the incremental changes of school reform?  Can education learn from the fundamental redesign of corporations?  These are bold questions for a system designed to support the economic needs of the 19^th century.   A 150-year old solution to solve the issues of a 21^st century globalized economy. Have schools reached the point where radical reengineering changes are required?  Thirteen years ago, the answer was yes.  Today, the yes is in bold.

For a reality check, suppose you are an entrepreneur interested in investing in a potentially successful Silicon Valley educational start up. Would this be an interesting portfolio?  The company is one of the largest in Silicon Valley and has 3500 employees and approximately 32,000 customers with an annual budget of around $300 million.    The company has five Board of Directors who are elected every 2 years.  To be on the Board, you do not need to have stock in the company, know anything about the company, or how to improve the company product.  The average tenure of the CEO is under 4 years.  The ratio of management to employees is 40:1.  Employees in the company work only 176 days a year. The majority of employees are over 40 years of age.  Because the Board of Directors has not been able to give adequate raises to the oldest employees, their union contract provides job security through tenure to minimize employee turnover.  In fact, less than .01% of the employees have been dismissed for gross incompetence.  Employee raises are automatic and have nothing to do with job performance.  To ensure quality, the Federal government demands that all 32,000 customers are treated the same without consideration to individual needs or abilities.  Even with as much as 12 years of development, one out of four products are defective. By the way, in California, there are 1,146 of these companies with over 7,000 elected Board members producing products that by global standards will not serve to drive the future demands of a global economy. These companies are today’s school districts.   They need a major investor.  Would you participate in a funding round?

Without such a major investment, is there any hope that the public education system can learn from the fundamental redesign of corporations? Systems thinkers such as William Deming have demonstrated that statistical methods can make a substantial difference in how to manage change, both within the public and private sector.  When there is alignment between the accountability system and decision-making, management is held accountable to those paying the bill.  Obviously, such an “alignment” has little relevance to the insulated national 6.8-million-student public education system with its multiple vested interests, bureaucratic fiefdoms, inherent inefficiencies and deaf ear to parents’ complaints.

California, and the nation’s fundamentally flawed school finance and governance system make it difficult, if not impossible to adopt system level improvements even if they work.  The laundry list of obvious options include throwing out the Education Code and starting over, restructuring the role of teachers’ unions, redesign of current governance structures and teacher/administrator education, restructure of the school day and school year, exploring tax incentives for business, university and school partnerships to inform and align academic and career readiness, data systems accessible to students, teachers and parents that support accountability within all system levels, and last, but not least, incentives to infuse data driven technology and student vested personalized learning options.

So what’s the next step?  Managing top down broad based system change is a daunting task.  Managing change bottom up sets the stage for broad system level change.  In other words, revisit the key business value added proposition:  put the customers needs first.  The depersonalized and institutionalized standard driven educational system where all students learn the same at the same time with no individual accountability is like using a World War I “mothball fleet” to win a 21^st century battle.  To prepare for the future, personalization, social networking and creativity are the foundational blocks required to maximize a child’s potential.  These are values that are not driven by 150-year old institutional priorities but are the requirements for 21^st century learning and a global economy.  Expanding personalized learning options and individualized accountability structures are a requirement not an option.   The right to engage in anytime and anywhere learning, using today’s vast informational and technological resources should be the rule for the present and the future, not the exception.

For starters, bottom up change requires a value system that fosters integrity and respect for what and how we learn.  This is the personalization of learning which starkly contrasts with todays institutionalized one-size fits all approach.  In essence, if you cheat the students, the students will cheat.  Personalization requires that students have access to their own and shared learning profiles that value their identity and builds their social capital.   Their stock of social trust- the norms that each student can draw upon to solve common problems.

In a “Different Stage of Imagination,” Gordon Freedman reminds us how companies like Amazon and Google use the Cloud to store incredible amounts of information and use this information to predict customer needs.   The goal is to personalize and maximize sales and marketing while improving customer satisfaction.  Every transaction is a data point analyzed to track variables, anticipate trends and reduce failure. In today’s world, using data to support success is crucial to developing a customer driven market.   It’s even more critical for a customer valued educational system.

Let’s take the premise that learning occurs anytime anywhere with opportunities unconstrained by time or place.   To thrive, you need to continually explore, create, capture and reflect.  Let’s also assume that the institution’s current measure of learning relies on narrowly focused standardized tests, antiquated course requirements, and prescriptive learning calendars monitored by day and time.  In other words, the value of the customer is sublimated by prescribed and poorly informed repetitive routines.  In contrast, the personalized learning profile acknowledges that students, not the institution, are capable of framing, capturing and validating the most critical learning moments necessary to thrive in today’s world.  We need to look up at the sky and Capture the Cloud before the storm.

Visualize the Cloud as a repository containing each student’s personal portfolio.   The portfolio provides immediate access to information needed to support interaction within their community of friends, instructors, parents and community.  Students, both individually and in teams capture moments critical to their learning.  Their social capital might include their work with peers, how they set individual and group goals, how they manage their time, favorite research topics, how to ask questions or ways to solve problems and find solutions.  Powerful data that informs what, when and how learning is, has and can take place accessible anytime and anywhere.  Visualize as well, the institution survives by continually exploring and providing expanded opportunities for personalized learning options.

As students frame their learning profiles, the supply side captures the multitude of learning reference points both from the BG Era (Before Google) and AG era (After Google) tracking a myriad of time and place choices.  The supply side creates algorithms capturing clickstreams of each student’s personal learning transactions and preferences.

This is the business education model for the 21^st century.  A business model where the supply side creates value added opportunities for personal learning, anticipates trends and in turn, reduces the options for failure.

While not explicitly mentioning NLET, the article highlights the needs for a “narrator” as community colleges begin to transition to “the new world of access, data and identity”.

Freedman’s advocacy for the introduction of “smart” approaches to bring systemic innovation through new organizational, economic and communication strategies resonates strongly with NLET’s essential mission and methodology.

You can download the article directly by clicking here

With the official launch of the project, the team is eager to begin. We have defined some initial steps that will need to occur before the core work on the model and visualization can begin. Los Alamos National Laboratory (LANL) must form the modeling team. The University of Texas, Austin must form a simulation team. The data warehouse at San Jose Unified School District (which houses 14 years of quantitative school, student and teacher data and 3 years of qualitative data for 30,000+ students)  needs to be scrubbed of unique student identifiers and then transferred to LANL and UT Austin. This data will provide the parameter/agent base upon which the model will be built.

This is a critically important topic to broach. First and foremost, the two are mutually supportive. High-quality research requires individuals who have undertaken and received high-quality learning (most often through a high-quality education system). High quality education can only be provided when the multitude of factors that impact student and teacher success are understood, which can only be accomplished through systematic observation, testing what is observed, analysing the results of the tests and disseminating the results – research.

Additionally, the marriage of research and education is critical because the accelerating speed of technology is quickly outpacing education. The advanced tools used in research, industry, and business should also be welcomed in the education sector to keep it relevant in the decades to come. This DRK12 project will determine whether a now-established research tool is appropriate as an education tool.

Finally, LANL and other research institutions have a direct need for qualified individuals with specific skillsets. If students are performing poorly in mathematics (and other related areas, such as engineering), institutions will be challenged to secure personnel in certain high-need positions that will impact our future. It is, therefore, in the best interest of our society to ensure that we understand the the factors that are affecting decreasing academic performance and interest. We aim to find out through this exploratory project if the model can define some of those factors.

The planning of this project benefited tremendously from the expertise of Principal Investigators Michael Strong PhD., a senior educational researcher in the Division of Social Sciences at the University of California Santa Cruz (UCSC), and Paul Resta PhD., Director of the Learning Technology Center at the University of Texas, Austin. Dr. Resta is also the Ruth Knight Millikan Centennial Professor with the University’s Department of Curriculum and Instruction. The project is fortunate to leverage the wisdom that comes with years of practical experience  in the education realm that these gentlemen offer, specifically in the areas of educational research and practical technologies which have the potential to benefit and improve both student learning and the education system.

The culmination of planning and proposal development resulted in the recent submission of our proposal to the National Science Foundation titled “Dynamic Modeling of School Variables to Predict 8th Grade Math Performance”. The goal of this project will be to create a predictive agent-based simulation environment (ABSE) which we hope will accurately predict student performance trends in math so that the ABSE can be used as a decision-making tool by education stakeholders such as school district personnel, state-level educators and legislators, and national educators and legislators.

The ABSE framework for this exploratory project will use data from the San Jose Unified School District’s data warehouse, which houses 14 years of robust quantitative data from over 30,000 students and teachers. The warehouse also houses qualitative data, a rare inclusion in many data warehouses, which will allow some interesting results in the ASBE model. The agents that will be used in the model are the various factors that influence a student’s success.  A few examples of agents are: a student’s previous knowledge of a subject, the manner and format in which subject materials are presented to the student, the student’s socioeconomic status, the teacher’s teaching competence, class size, and how much time a student and teacher interact on a particular subject’s material.

The benefits of developing a complex scientific model for education are multiple:

• A large number and range of influencing factors can more easily be considered within a single meta study
• We can begin to identify correlations and relationships between and among factors
• The model’s structure will be flexible and allow for scalability to service very large data warehouses
• The education sector will benefit from an established scientifically-valuable technology

As we learn more about the applications of scientific modeling technology for the education sector, NLET will be actively nurturing collaborations with research institutions that use this technology. It is one tool that we feel will be critical for educational decision-making as we move forward at breakneck speed into a fully technological 21^st Century.