Welcome to the Robo Classroom

Significant work has been done in the past decade for digitization of ed curriculum. The Internet has been a major disruptor for educational content distribution with free, blended, and interactive models arising. The second wave came with gamification and big data analytics. Companies like Knewton began amassing enormous databanks of performance factors through online means to deliver adaptive learning.

This sets the stage for the next wave of educational innovation – the robo classroom. At Houghton Mifflin Harcourt, I prototyped adaptive learning integrated with augmented reality – much in response to Samsung’s demonstration of “the classroom of the future.” Samsung had demonstrated how a student could “paint” on a tablet, while a teacher could view the child’s screen and lock it whenever the child was supposed to pay attention. While the audience cheered at the “innovation,” I saw the dehumanization of education (See Ben’s post earlier). As a result, I wondered… what role can technology play that would advance a humanistic education. An I-Thou relationship as Martin Buber would say.

I built the prototype for the system. A teacher could scan the classroom to see each student’s performance (essential because adaptive learning means all students will be at different places all the time). This part of the development was easy. It’s just a dashboard with a camera. The next part chilled me.

I realized that as soon as an engine is built for adaptive learning an engine for adaptive teaching would appear almost as soon. This would chain teachers to a system, whether it be artificially intelligent or not. As a result, teachers  become less empowered, innovation-starved, and further demoralized and underpaid/valued. WATCH THIS TREND. IT IS HIGHLY DANGEROUS.

I advanced the development to create an adaptive teaching engine. However, in doing so, I explicitly set the rule that the classroom teacher is the authority. The system is a guide, but the teacher is the expert. For example, an adaptive teaching system may know that Felisha learns best through peer-to-peer learning with Donna. However, it will not know that Donna’s parents are in the middle of a divorce and it may be more productive for an alternative path for education.

One benefit of an adaptive teaching system is that it provides CONTEXT for substitute teachers. And, if the data cloud expands to cover secondary factors (socioeconomic indicators, integrated government services like TANF or SNAP), social media, etc. The system can do a much better job of understanding the complexities of authentic learning.

When I learned IBM Watson was focusing on education, I was excited and worried. Excited because it is an interesting approach to education. Worried because I can pretty much guarantee they will do it wrong. In my discussions with IBM Watson Education leaders, it appears that they are simply replicating their work in Watson Healthcare, without considering that the models are completely different. I have played with the Watson system (read my blog for Watson Weighs in on the US Presidential Election) and it is crude. The ability for it to accurately extract semantics and identify emotions are at an infancy stage. It works best in a condition like healthcare and trivia (Jeopardy!) where the knowledge is highly structured and related. It does poorly in an environment where the data is unstructured, human-centric, and subject to interrelated fuzzy factors (e.g., socioeconomic, family, healthcare, DNA, weather, nutrition…)

I remember a presentation I gave where I closed by asking if technology will save us or destroy us. Using a google search, the answer was much higher that it will save us. But will we save ourselves from technology?


The Educational BlockChain: Liberating Education

As the Senior Director of Adult Education & Workforce at Houghton Mifflin Harcourt (HMH), I was challenged with helping transform a 180-year old textbook publishing company into The Education Company. In my work in educational innovation, I designed a radically new educational blockchain model that would fundamentally change the publishing industry. I offer it here as one possible future for the industry, and encourage you to think about the impact it would have on learning, education, and the ability for students to achieve their potential.

The structure of the the school and classroom boxes teachers through administrative procedures, overwork, low pay > education undervalued in the U.S. As a result, teachers quickly become a cog in the educational wheel with many disillusioned.

The educational system weighs against classroom innovation. The standardized test movement has resulted in a prescribed curriculum with little room for teachers to apply their creativity, address learning differences, introduce holistic experiences (like growing soft skills like empathy, emotional intelligence, artistic, innovation, etc.). As a result we have a stagnant model drifting to low performance. Even though Common Core advocates for teacher empowerment, the increased rigidity of complex requirements make it so that leading schools are already using Common Core, while other schools may never be able to implement them successfully. In short, we are where we are.

I wondered how HMH, a $1B education company, might change that. What if we could design a 21st century educational system that liberated teachers, moved the publishing dinosaurs into innovative leadership positions similar to what we experience in technology. What might that ecosystem look like? How might that work? What would the key triggers be? The result was the design of an educational blockchain system built upon current trends…

Here’s what I designed:

  1. Digital Learning Objects are the Core of the Educational Blockchain. Digital Learning Objects allow “learning” components to be broken down into digestible chunks. For example, the Battle of Iwo Jima may include learning objects for US military strategy for the battle, Japanese military strategy for the battle, Outcomes of the battle, etc. and be components for larger objects such as WWII, Japanese History, Military Strategy, etc. The industry trend has been to move to “digital first,” as became HMH’s mantra. In doing so, however, publishers have had difficulty rationalizing pricing. Previously the cost could be measured in pounds of paper. However, in digital publishers don’t have to print millions of forests, but they also don’t get to replace millions of books each couple of years. As a result, they need to identify new revenue sources. They are very poor at this, and consolidation, reduced revenues, and stagnation are a key trend. However, there is a diamond in the movement. The creation of large volumes of digital learning objects creates the foundation for building a digital learning ecosystem. Digital learning objects are the fundamental unit of the education blockchain.

  2. Eliminate the Ivory Tower: Curriculum is currently designed by “experts,” and pressed through an unbearably arduous process to ensure that each result is valid and reliable. Curiously, when I sought HMH case studies demonstrating that their educational content actually improved student learning, no one I asked could supply any. Historically, education was for the privileged. The teachers and owners of educational content were gatekeepers who determined who gained access. The long tail of this system still exists in educational content production. We have a few people making critical decisions that influence the trajectory of student lives. These academics are disconnected from the needs of local regions, diverse students, and business needs. What if we lose the Ivory Tower and allow teachers to innovate? Content providers will no longer in control of the educational content supply chain.

  3. Publishers as Referees: Instead of being the creators of textbooks, publishers become both digital content creators and referees. Digital Learning Objects may be created from any source: businesses, non-profits, schools, teachers, parents, students, etc. The ecosystem can be as inclusive and expansive as allowed by the publisher gatekeepers. School districts, states, individual schools gain the ability to create their own curriculum from digital learning objects. Publishers become referees – ensuring and validating that digital learning objects and curriculum passed the academic rigor. Publishers certify curriculum so that schools can be confident of value. For example, you want to be sure that the Holocaust is presented appropriately. Publishers become the certifier that the education blockchain is trusted, valid, and reliable.

  4. The Education Market Opens to New Suppliers: When studying at the Harvard Graduate School of Education, I worked on a project where we gained access to ABC News’ video archives. The treasure trove of content was unfathomable. How it was indexed and organized would have Dewey jumping in glee. I used this experience in designing the educational blockchain and imagined a platform where teachers/curriculum developers/school districts gained access to a rich and diverse universe of materials. Imagine pulling together a unit on the Holocaust and having easy access to the a diverse set of materials – traditional assets (publishers), personal stories (parents, students, NPR, PBS), Video (Netflix, National Archives), gamification (ELine Media), etc. The education blockchain includes film/tv, video, audio, game learning objects, pedagogical structures, open to all potential suppliers and entrepreneurs. Publishers, as the referees, determine who can enter the field through assessment, validation, and certification.
  5. Education Blockchains Products include digital learning objects, media, and delivery method: The prototype for this new educational blockchain system fundamentally provides a platform for teachers to easily pull together components for curriculum creation. There are a select number of ways teachers can present content and engage in learning experiences. Examples include flipped classroom, team-based learning, individual learning, game-based, case-based, experiential, emotional, kinesthetic, etc. In the platform, teachers would select their digital learning objects and content objects, and apply a teaching approach to the components. For example, selecting gamification automatically fits the blockchain objects into the appropriate structure, identifying gaps if existing. The use of big data analytics and adaptive teaching can provide scoring estimates for the effectiveness for each educational product – based on national/global performance for blockchain components and for the local classroom factors performance. As a result, teachers are empowered to innovate, be creative, design, and learn themselves as they teach.

  6. Teachers are Suppliers to and Consumers of the Educational Blockchain. Teachers/schools/districts will not always have the time to assemble new lesson plans and units. In the design, teachers will have the ability to create and publish their creations from the educational blockchain. Because the core elements have been validated and certified, the creation can be trusted to those purchasing the content. Purchasers can include other schools, districts, home schools, charter schools, and individuals. In my design, the Publisher would take a percentage of the sale, and a percentage would go to both the school and the teacher. Of course, this ignores the firewalls around the ability for schools and teachers to generate revenue, but I’m convinced that the need for new revenue streams for school funding would overcome the barriers. New revenue streams for schools, teachers, publishers, and content providers open up.

  7. Publishers Amplify High Performing Products. Publishers continue to play a pivotal role in educational success both as protectors of digital learning objects and referees for curriculum. They also play a critical role in amplifying performance for successful educational blockchain solutions. Publishers can identify the top performing curriculum through sales, innovation, outcome effectiveness, etc. and market the results (e.g., App Store Rankings for Education. Instead of free/paid, think sales/innovation/outcomes) through award programs, promotions, and advocacy. The liberation of the system enables curriculum that specifically responded to the need for classroom innovation, customization, personalization, and the ability to address socioeconomic and education equity challenges. Using big data analytics for adaptive learning, these measures can identify what truly works and can help drive improved student performance. Publishers become Marketers.

Although I left Houghton Mifflin Harcourt in 2014, I still am convinced that this approach has the opportunity to revolutionize education. It provides tremendous potential to liberate the classroom, drive high innovation, and improve outcomes. It provides a pathway to address educational failures, improve successes, and help students achieve their potential.

Better Education-to-Employment: Jump in the OCEAN

I’ve spent the better part of the past decade working on improving education to employment (e2E). At Monster, Houghton Mifflin Harcourt, and ACT, I advocated for improved performance in e2E. I argued that it is no longer acceptable for career/guidance counselors, Career OneStops, Job Boards, outplacement providers, or career service businesses to prepare candidates and wave Bon Voyage – your future has bright horizons. All providers have the ability to maintain a relationship through employment and career progression as a result of the rise of the Relationship Age.

However, very few accept my challenge. Working with the Ohio Board of Regents and Department of Jobs & Family Services, I designed OCEAN – the Online Career Education Accelerator Network. OCEAN provides an architecture to integrate the talent supply chain from K-12 through retirement. It includes several components:

  1. Career Planning from K-12 on – On a National Association of Workforce Boards International Summit, I witnessed the power of CareerCruising helping students in 6th grade develop realistic career plans. Listening to the students I was impressed with their confidence, vision, and clarity. Once a student develops a career plan, it tracks the student’s relationship between academic achievement and career plans. If someone wants to become an engineer but is failing physics, then they have a choice, improve academically or adjust their career plans. It is essential that education be connected to career aspirations. Students and parents should have the opportunity to understand current labor market trends, but workforce development needs to be redesigned around what people want, not what business wants.
  2. Career Skills from High School on – The Seattle Workforce Board needed a self-service resume builder. The Monster “form” approach was insufficient. My team began project codenamed Razorback – for really simple resume builder. After 6 iterations we cancelled the project after meeting OptimalResume. Their platform includes the best resume builder I’ve seen. But what really blew me away is their practice interview module. The system includes hundreds of interview questions for every type of interview. The interface presents 3 video panels. The first panel shows the recruiter asking the question. The second panel allows the job seeker to record their response. This provides an immediate feedback loop and allows the seeker to practice to be best prepared. The third panel contains a video of a career coach explaining the best answer and why. The design simplicity is powerful and valuable to job seekers. A quality resume and interview skills are fundamentally critical in career success. The system also includes an ePortfolio that is good, a self-assessment for skills, Indeed job search, and a notebook. What is missing from the platform is the ability to research companies in preparation for the interview, and a deeply integrated job search platform.
  3. Job Matching – Integrating a powerful job board (e.g., LinkedIn, CareerBuilder) provides the opportunity to bridge Career Planning & Skills into actions to identify and land a job. The system designed for Ohio incorporates education-career functionality where a job seeker who does not possess the qualifications for a job can see where they can get the education to land the job. The OCEAN platform delivers an integrated, holistic experience so that the path from 1-3 exists symbiotically to help a job seeker advance.
  4. Labor Market Intelligence – When I met with the Labor Minister of Canada in a private session several years ago, he asked what I thought of Canada’s labor market data. Courteously, I replied that it is a valuable tool helping the country’s orientation. He replied, “It’s garbage,” and threw the report in the trash. At Monster, I built the world’s largest talent supply and demand database ever constructed. I could tell in real-time (1 day delay) talent surpluses, deficits, incubation opportunities and high performance broken down by location, industry, role, level of education, experience, and a host of other factors. Government projections for labor markets is a good fundamental – if you realize that the price of oil, war, global economic changes, and other factors have the potential to significantly disrupt estimates. Instead, I focused on what what really happening now. If there are 100 manufacturing jobs – that may appear great if you’re a job seeker, but not if there are 10,000 candidates. Thus, supply and demand are critical. Monster, CareerBuilder’s EMSI, and BurningGlass deliver real-time analytics. An example of EMSI’s CareerCoach in use at WakeTech Community College can be viewed here. This insight is integrated throughout OCEAN to ensure that decisions are grounded in the reality of the local labor market.
  5. Online Communities – using LinkedIn’s model for groups is helpful, but the establishment of online communities (e.g., military.com, STEMPower.org, BetterJobsFaster.org etc.) provide a place for individuals to go to engage with like-minded individuals, gain from peer-based learning. BetterJobsFaster, for example, has functionality like Phantom Job Seeker where individuals can learn what products/services really work versus which are fads. It provides industry insights and content with a mission to help all achieve their career potential. This enables OCEAN providers to maintain a lasting relationship by creating sustained VALUE to users.

The OCEAN system includes diverse stakeholders from Workforce & Economic Development, K-12, Vocational Schools, Community Colleges & Universities, Business, and Service Providers. It serves as a bridge from education-to-employment and takes responsibility not for the current siloes, but for the entire supply chain. One way it may be applied is to control or streamline strategic talent supply chains (e.g., healthcare, manufacturing). It provides an ability for a region to differentiate, deliver high performance, and create bottoms-up workforce development approaches so that students can gain work that meets their career aspirations.

The education-to-employment system does not serve the needs of students seeking alternative pathways (college is not the right option), fails the underserved populations including disconnected youth and ex-offenders, works poorly for Veterans, and largely ignores older workers. We deserve better. Maybe I’m just boiling the OCEAN here, but I’d like to think that the architecture can deliver better.

The Emergence of the IoP – the Internet of People in the Age of Superfluidity

With the rise of the Internet of Things (IoT), the same transformation is taking place in labor markets as we move to an Internet of People (IoP).  We moved through the agricultural revolution, to the industrial revolution, to the information revolution. The relationship revolution is moving towards a “Matter” revolution.

Witnessed by the rise of LinkedIn, SnapChat, Facebook, and Twitter, the relationship age focuses on the interconnected of people. In 2005, I was asked to recommend acquisitions for the then industry-leading job board, Monster.com. I had been watching a small company that had created a unique model focused on creating relationships and value. That company was LinkedIn. Monster’s CFO, Bill Pasteur, declined to buy the company because he didn’t understand the financial model. As a result, in 2016 LinkedIn’s sales were $960M while Monster was acquired by Randstad in November 2016 for $429M.

The relationship age can be recognized by the financial value being attributed to social networking by markets. Facebook’s IP for $104B, Snapchat at $18B, and Twitter at $24B are clear examples that the markets place significant value on organizations focused on relationships.

The superfluidity of labor markets will grow significantly in upcoming years due to several factors:

  1. Significant Global Talent Deficits – In the next 10 years the Baby Boomers will retire, leaving not enough workers for the jobs today, never mind the jobs of the future. These shortages are global. Mexico, Canada, China, and India are all challenged to find the talent they need to respond. Canada has turned several overseas embassies into recruitment centers for critical jobs it knows it will not be able to fill. Compare this approach to the U.S. trying to close off talent immigration.
  1. Shift to an Ecosystem of Workforce Matter – The traditional recruitment process where a candidate submits a resume through an online job board will be replaced with a portfolio-based system that identifies the actual experience of the candidate. Facebook and LinkedIn are leading this revolution by shifting the resume to a project-based model. Both systems now ask an individual to add to their portfolio the projects they worked on, the results they accomplished, and the other team members who also worked on the project. This shift enables employers to identify at a deeper level what a candidate offers and the other members of the team involved. An employer can reach out and get feedback on the candidate without even engaging the candidate. And, in an age of superfluidity, employers are now able to hire an entire project team.
  1. The Rise of True Cognitive Systems – In 2009 semantic matching came to the labor market. It replaced boolean searches with promises of the ability to find candidates based on meaning. However, there are many dirty little secrets concerning how the proprietary engines actually work. In the age of cognitive systems, big data clouds will disrupt recruitment processes by enabling recruiters to directly identify candidates based on a large pool of data that includes traditional information, online social media engagement, patterns of behavior, and feelings. This new age will help employers find candidates who are a right cultural fit as well as who have the skills and competencies to do the job. Using IBM Watson’s cognitive platform, I was able to assemble a recruitment process whereby job seekers could respond to interview questions through online video – speaking for as long and in-depth as they want. YouTube’s closed captioning turns the video into text, and IBM Watson’s engine translates the text into meaning – analyzing the critical semantic content and the emotions associated with each response.
  1. The IoT and IoP – The Internet of Things will enable employers and job seekers to better find each other. With mobile beaconing for employers and seekers, a level of augmented reality arises. A candidate  shopping at Neiman Marcus and their phone might buzz to let them know that Neiman Marcus is hiring for the skills they have. The Home Depot could find shoppers looking for work that matches their hiring needs. They can directly reach out and engage with them without the traditional hiring processes. This will create a disruption in hiring practices.
  1. Increased Automation of Work– the knowledge economy and creative class foretell a future where what you know and the innovation you bring to the market matter most. As a result, enormous inequity in markets will occur. Those without skills, knowledge, and abilities will be left with few opportunities and cyclical poverty. Unless successful transformations in education and training occur. (Unlikely). Those with the knowledge and innovation will rise, while the others will struggle to find work as automation of business processes expands to automate human processes including decision-making. Corporate productivity will increase as a result.

Actions to Consider

To respond to these challenges employers should consider the following:

  1. Strengthen your brand– When I’m asked to speak, I often ask the audience, “How did Google go from being a 1 with 100 zeroes after it to being the most desirable company to work at in the U.S. and Canada?” I then go on to explain GoogleSeeds – the idea that the first encounter with your brand plants a seed that either grows or dies with every subsequent interaction. Employers need to focus on their brand touchpoints to strengthen their market positions.

Compare the response to the recent immigration executive order barring Muslims from entering the U.S. Starbucks announced they were hiring 10,000 immigrants. Uber supercharged passengers from JFK, resulting in #ProtestUber. To date, over 200,000 people have deleted the Uber app. Competitor Lyft made the management decision to not surgeprice and announced they were donating $1M to the ACLU in a bid to “protect the Constitution.” Employers need to know what they stand for and be prepared to defend their positions publicly.

  1. Build Stronger Talent Supply Chains – Compare the actions of a large aerospace corporation. They know there will not be enough candidates to fill their hiring needs, so they identify the best and brightest candidates while they are still in college – as early as their sophomore year. They agree to pay for the student’s education if the student agrees to work for them after graduation. It creates a win-win situation. The student gets and education and job security and the corporation gets the best and brightest. This is an example of moving closer to the source of the talent supply. As labor markets tighten, employers will need to move closer to the source of talent in order to remain competitive. A shift will occur where candidates gain leverage, and employers will need to compete more for quality talent.
  1. Workforce Planning becomes Strategic – HR professionals need to work as a key strategic stakeholder in their organizations and create a matrix (lo-hi) of value to the organization and level of expertise. Using this, HR should prioritize their efforts to dedicating funding and resources to the hi-hi, those with high value to the organization and a high level of expertise. Hi-Lo blocks should also receive attention, and the Lo-Lo should be outsourced or automated.
  1. Develop a Scenario Play Book – Using IDEO’s human-centered design approach, employers should co-create a scenario play book based on potential market disruptions. This includes potential risks and opportunities, such as the shutting off immigration to the U.S, the surge of Internet of Things and Internet of People, identifying the key technologies and their place as early adopters or fast followers. As a result, they will be prepared as uncertainty becomes clearer and can respond to capture talent, take advantage of new opportunities, and gain market share.

Finally, remember that it’s all about people. All of the work we do. All of the superfluidity we create. It begins and ends with people. When I was at Houghton Mifflin Harcourt, Samsung came to present the “classroom of the future.” I felt like I was the only person in the room horrified at the dehumanization of education as the entire experience was a human-glass screen engagement. So, I focused on how we could shape technology to unleash the pent-up energy for teacher innovation, to bring new approaches to traditional education using augmented reality, adaptive learning, and cognitive systems. The future has potential, but it is we who will need to wisely create the future that we and our children will inherit.


Image courtesy of Socilab

What the World’s Smartest Artificial Intelligence Says about the U.S. Presidential Debate? Watson…

In August, I wrote Watson Weighs in on the U.S. Presidential Race. The article used IBM’s Watson Alchemy Language Engine to analyze Hillary Clinton and Donald Trump‘s acceptance speeches at their national conventions. While these speeches provided good insights into what the candidates had to say to the global public, they were in front of their political base supporters and may not have accurately captured what the candidates really were like to the American public or what their ideas were for the country.

IBM Watson has the ability to analyze massive data clouds. It’s possible to take the every Twitter feed, Facebook post, news article and use that to analyze everything from what people believe about the candidates, to how the media portrays them. Of course, this can be used for authentic analysis, or to further polarize the American electorate.

With the first Presidential debate behind us, I thought it would be useful to apply the same methodology to see if Watson has any new insights into the candidates from the debate. I parsed Hillary, Donald, and Lester Holt‘s (moderator) word taken from the debate transcript on Politico.com.

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