STEMspirations: Do You Really Want to Inspire STEM Interest?

Much attention, resources, education curriculum, and energy has been focused on helping develop interest and career pathways for students and adults directed to careers in Science, Technology, Engineering, and Math (STEM).

Some of the hottest areas are 3D Printing, video game and app development, code-a-thons, and student camps. Much of these efforts are driven by top-down workforce and educational approaches. Teachers, administrators, and workforce development leaders are constantly asked to create interest and experience in what business needs.


The problem with these approaches are that they are extrinsic. Many leaders are “selling” interest to youth, and today’s youth are rejecting traditional selling methods from adults. The rules of the game are changing. Intrinsic motivation is significantly stronger, but the challenge is how to create intrinsic interest in something that many s
taff do not understand, can’t see the ultimate vision, and are building skills for jobs that don’t exist currently. This is a high risk for the lives of students, and I’m seeing them turn more towards humanistic interests (read social media) than externally-driven approaches. Just as the baby boomers taught the Gen-Xers the downside of materialism and capitalism, Gen-Xers have taught Gen-Yers to strive to move away from complete control of completely planned social activities (any event/activity that requires a parent to drive a young person to). Have we created a generation yearning to reject what we’ve done Bowling Alone?

51pcdvqwc9lThe problem with “selling” means that the other person has to be sold, and they have to buy something that they may or may not want. In the West, we have become masters at marketing unnecess
ary must-have products and services that add little value. As the Atlantic magazine asked in their September 2016 issue, “15 Years After 9/11, Is America Any Safer?” As Alfie Kohn points out in Punished by Rewards, “our basic strategy for raising children, teaching students, and managing workers can be summarized in six words:

Do this and you’ll get that. 

Alfie shows that while manipulating people with incentives seems to work in the short run, it is a strategy that ultimately fails and even does lasting harm. Alfie argues that our workplaces and classrooms will continue to decline until we begin to question our reliance on a theory of motivation derived from laboratory animals.

Surveying hundreds of research articles, Alfie shows that the more we use artificial inducements to motivate people, the more they lose interest in what we’re bribing them to do. Rewards turn play into work, and work into drudgery.


Think about what all these motivators and inducements mean for our STEM initiatives. We should not be attending to creating human resource products (i.e., workers) to satisfy STEM-related employers, which is shifting the burden of responsibility for youth and adult interest, education, and training from business to the responsibility of the public sector. We should be attending to the fundamental question:

The Question We Need to Ask is:
What do youth really want?

Understanding intrinsic motivators is a primary path to career achievement, success, and a person realizing their potential.


Working with the Commonwealth of Massachusetts team led by Jeff Turgeon, Executive Director of the Central Mass Workforce Investment Board, and Lisa Derby Oden, STEM Program Coordinator, Sandy DeMaioNewton, CEO of SHE Design, and Bill Bradbury of, we created – the Commonwealth’s online community connecting STEM leaders in education, higher education, and workforce development, as well as businesses, students, and job seekers. It was the first attempt at bringing the entire STEM talent supply chain stakeholders into a common forum for dialog from end-to-end to help produce better outcomes. Nearly a decade later, the site is still going strong making a difference in STEM advancement in the state.


the-art-of-immersion-coverThe question becomes how to create intrinsic motivation in students who are not interested in being sold. There are two ways, immerse them and inspire them. Immersion has to use a design that is salient to youth. When Bill Bradbury, Tracy Linville, and I worked to create My IE Career with Riverside Youth Services, we designed a solution by youth, for youth. We designed absolutely brilliant immersive experiences using approaches detailed in Frank Rose‘s book, The Art of Immersion, to create superversive experiences – the coming together of people to (often) clandestinely improve the state.


The result generated interest from the inside out and produced future materials that were salient to youth because they were designed in the voice of youth and by youth. Not top down.


The second approach to helping to create STEM pathways is to inspire them. Inspiration is an internal quality. Rather than teaching, it focuses on learning. The best teachers inspire their students to learn. But inspiration comes from within the individual, not from the teacher. Just as healing takes place within the person, not by the doctor. How to inspire STEMspiration? Here’s a link that will give you some good ideas. This is Why I’m Broke is a great site for innovative, exciting, and inspiring products that can, yes, lead to bankruptcy, but also inspire imagination, creativity, and opportunities. Below are some pictures to get you started. They should help get you started by inspiring ideas for you to inspire others. Check out these amazing STEMspirations and Do-It-Yourself products. My recommendation is that wherever possible, ask students and STEM potential participants, what would you do with this? How could this be used to do something really cool? How could you use these ideas to do something meaningful. And then, help them make it happen.

I’d love to hear your stories, successes and failures applying STEM curriculum and innovation, so feel free to share in the comments.

May we all reach our potential.

Disclosure: The author does not have any relationship with ThisisWhyImBroke, and do not receive any financial compensation for any products or services sold through their site.

Biggest Hits and Misses from Apple Special Event

Apple had their latest Applefest on September 7. This year it featured performances by, well, Sia, but there will be the Apple Music Festival streaming free from September 18-30. What were the biggest hits, misses, and eh moments from the event?


  • Social Impact
    • Apple’s donation to ConnectEd of $100M of teaching and learning donations to teachers and students.
    • Apple Watch’s environmental standards
  • Apple Watch
    • Swim proof
    • Built-in GPS & Hiking
    • Brightness
  • iPhone7
    • Depth of Field
  • Programming
    • Swift Playgrounds to teach kids programming

Eh’s – Announcements that were just… Eh.

  • iWatch
    • Nike Watch
    • iOS3
    • Ceramic
  • HomeKit
  • iPhone 7
    • Telephoto
    • Colors
    • Water & Dust Resistant – playing catch up
    • Camera(s) – worst kept new iPhone secret
    • Stereo Speakers – playing catch up
    • Lightning Headphones
  • Siri improvements
  • Contextual Predictions
  • ApplePay Japan
  • Games
    • Nintendo Mario
    • iWatch Pokemon Go device


  • iPhone 7
    • No WOW innovation factor
    • No 100% glass screen
    • Retained home button
    • Wimped out on headphone jack
    • Price
    • Wireless, Lightning Headphones with 5 hour battery life
  • iOS 10
  • iWatch
    • Nike iWatch
    • Pokemon Go
    • Breathing App
  • iWork Collaborative – working together was eerily silent…

Crying for Attention

  • Hello, Can You Hear Me?
    • iMacs
    • iPads
    • AppleTV
    • iPhoto
    • iCloud
    • iTunes
  • Apple Education
  • Apple Artificial Intelligence (e.g. Watson)
  • Apple Cars
  • Business
  • Investors (no sales figures)
  • Britney Spears & Justin Bieber



Infographic: What’s the World’s Smartest Artificial Intelligence Say about the U.S. Presidential Election?

Last Week I wrote Watson Weighs In, looking at the perspective of IBM’s Watson – the world’s most intelligent cognitive system platform. Watson’s artificial intelligence, neural networks, adaptive learning, and semantic matching make it a force powerful enough to beat all Jeopardy! champions. With that kind of intelligence, why not challenge it to make sense of the U.S. Presidential election. Should be easy, right. Right.

As a follow up to that piece, below is an infographic summarizing Watson’s interpretation of the Acceptance Speeches of Hillary Clinton and Donald Trump.


By Dan DeMaioNewton Posted in politics

Watson Weighs in on the U.S. Presidential Race

Hillary-Trump-DaveWhat does the world’s most powerful artificial intelligence say about the U.S. Presidential Candidates?

I spent the last week engaging with the world’s smartest artificial intelligence brainiac about the U.S. Presidential Election. I pressed IBM’s Watson to light up its neural networks, apply cognitive systems, crunch semantic learning, and emote sentimentalism to help me understand what the candidates are saying and meaning.  The results were astonishing.

IBM’s Watson platform is a cognitive system enabling a new partnership between people and computers. It is most famous for beating the Jeopardy champions for a $1 million prize.  The Watson platform has introduced groundbreaking advancements in healthcare, finance, biotechnology, and other sciences, and is entering the fields of education and finance. With that breadth of intelligence, a natural question to ask Watson would be, “What do you think of the U.S. presidential race?”

Mr. Watson. Come Here. I Want to See You

As a cloud-based computer platform, Watson should be an apolitical judge.  Watson uses natural language processing to understand meaning in text messages. Coyly, one may argue there is nothing natural about this presidential election. Nevertheless, Watson is the best artificial mind we have to interpret what the candidates are saying and what they actually mean.

When engaging Watson, I didn’t explain the context of everything related to the election, not Donald’s business successes/failures, nor Hillary’s emails. Why bother? Watson is in the “cloud.” It lives in the Internet even more than I do.

To prime Watson for our conversation, I provided transcripts from acceptance speeches at each party’s national conventions and ran them through IBM’s Alchemy Language – Watson’s brain for text analysis using natural language processing. Watson’s Alchemy Language engine analyzes text to help understand concepts, things, keywords, sentiment, and emotions.

Determining context from a phrase is not an easy task neither for humans with political candidates, nor for Watson trying to dissect and understand a political speech.  For example, in Hillary Clinton’s speech she said, “I will be a President for Democrats, Republicans, and Independents.” Is this neutral, positive, or negative? For Republicans and Independents, maybe negative. Unless you’re a republican who loathes the idea of a President Trump. The beauty is in the eye of the beholder.

When Donald Trump said, “The problems we face now – poverty and violence at home, war and destruction abroad – will last only as long as we continue relying on the same politicians who created them,” his words contained problems, poverty, violence, war, destruction – four highly negative words. However, anyone reading the line may interpret it as a call for change, hope, and a better future.

To best illustrate the problem of attaching sentiment and emotion is the line from Donald Trump’s speech when discussing the horrific Orlando nightclub massacre, “49 wonderful Americans were savagely murdered by an Islamic terrorist.” The word wonderful is a positive emotion attached to Americans. Savagely, murdered, and terrorist are all negative words also attached to the Americans, Islam, and terrorists. Donald Trump was not being negative towards Americans, but the semantics of the words associated with their objects was negative. These are the complex problems cognitive systems must understand to be most beneficial to humans.

Screen Shot 2016-08-24 at 4.48.53 PM

Donald Trump’s Acceptance Speech Word Cloud

That’s Good, But How Do You “Feel?”

When Watson extracted and examined the top 50 things (entities) that each candidate mentioned in their speeches, it found that Donald Trump was positive only 22% of the time, compared to 38% for Hillary Clinton. Both candidates were negative about 35% of the time. Donald Trump’s primary sentiment towards things was neutral, while Hillary Clinton’s was positive.

When Watson extracted and examined the top 50 keyword concepts from each candidate’s speech, Watson found that Donald Trump was positive only 22% of the time versus 58% for Hillary Clinton. Inversely, Trump was negative 66% of the time compared to 30% for Hillary.

For targeted sentiments, Donald Trump was negative 65% of the time, while Hillary Clinton was positive 65% of the time. Donald was positive only 25% of the time, while Hillary was negative only 30% of the time.

Eliminate All Other Factors, and the One Which Remains Must Be the Truth

There were many areas where Watson hit the bullseye.  Below are some top examples:

  1. Each candidate’s number one topic was America
  2. Each candidate’s number two topic was their opponent, and they were negative about their opponent.
  3. Donald Trump speech spoke often about countries in the Middle East and was negative about these countries.
  4. Both candidates spoke positively about their family members,
  5. Hillary Clinton was positive about “young people,” “small businesses,” “good paying jobs,” and “better lives.”
  6. Donald Trump was positive about the “American People,” “United States,” “new wealth,” and a “truly great mother.”

The Empires of the Future are the Empires of the Mind

What were the core topics covered in each speech? According to Watson, Trumps speech mostly covered societal unrest and war, and children. Watson wasn’t confident that Trump’s speech was about government. Perhaps Watson has an ironic point. Clinton’s speech, by contrast was about foreign policy, war and unrest, and education. Watson was confident about all three topics for Hillary’s speech.

Screen Shot 2016-08-24 at 4.26.17 PM

Hillary Clinton’s Acceptance Speech Word Cloud

We’re All Quite Mad Here! You’ll Fit Right In

When Watson examined the top 5 concepts relating to each speech, here’s what it found:

Donald Trump’s top 5 concepts in his Acceptance Speech:

  1. Hillary Clinton
  2. Bill Clinton
  3. Barack Obama
  4. Illegal Immigration
  5. United States

Hillary’s Clinton’s Top 5 concepts in her Acceptance Speech:

  1. Joe Biden
  2. United States
  3. Barack Obama
  4. President of the United States
  5. Donald Trump

Wow! I have watched, listened, and read Hillary’s speech several times now, and I cannot understand how the top concept Watson identified was Joe Biden. Above the grand old USA. That’s a big miss.  Also surprising is that Bill Clinton was #2 on Donald Trump’s list.

Come On, Group Hug! You Too, Anger.

Watson examines the same 5 emotions as the Pixar animated film, Inside Out: Fear, Joy, Disgust, Anger, and Sadness. While humans have many more emotions, both Pixar and Watson limit their evaluation to these five. Watson found the emotions presented in the acceptance speeches both conveyed Anger and Fear. The other three emotions (Sadness, Disgust, and Joy) didn’t rise high enough to be considered significant. Sadly, Watson disgustingly didn’t find either speech to be joyful.

No Great Mind has Ever Existed Without a Touch of Madness

We are at the late dawn of cognitive systems, and by using Watson to interpret the presidential candidates’ acceptance speeches we are giving it an arduous task that exposes how well it works as well as areas requiring advancements in interpretation both for the computer, for the analyst, and the reader. For the list below, I examined Watson’s interpretation, then re-read the speeches to try to understand what Watson was thinking and if it was correct or erroneous.

Watson’s biggest misses were:

  1. Hillary Clinton’s sentiment about America was negative.
  2. Hillary Clinton was negative about Bernie Sanders.
  3. Hillary Clinton was negative about the President and vice president.
  4. Donald Trump was neutral about President Obama.
  5. Donald Trump was negative about Americans, country, and America.
  6. Donald Trump was negative about law enforcement officials.
  7. Donald Trump was neutral about African American youth.
  8. Hillary Clinton was positive about Trump picture frames.
  9. Hillary Clinton was negative about police officers.
  10. Hillary Clinton’s top concept was Joe Biden.
  11. Donald Trump was neutral about Fred Trump
  12. Hillary Clinton was neutral about Bill Clinton.
  13. Hillary Clinton was negative about First Lady Michelle Obama.
  14. Hillary spoke negatively about Joe Biden
  15. Hillary Clinton was negative about “real change.”
  16. Donald Trump was positive about “Special interests.”
  17. Donald Trump’s 2nd most relevant concept was Bill Clinton.

When Gunpoint is a Country

Watson assigns entities to a category, and some of these categories were incorrect. Watson assigned the White House to be an Organization in Donald Trump’s speech, but a Facility in Hillary Clinton’s speech. In Donald Trump’s Speech, Watson found America to be a continent, and Gunpoint to be a country. In Hillary Clinton’s Speech, Watson misidentified New York state as a city even though the sentence where it was mentioned said, “the great state of New York.” Watson also identified the Secretary of State as a “Field Terminology” rather than a JobTitle. (It understood President to be a JobTitle.)

Note: FieldTerminology appears to be the category when Watson knows an entity is an unnamed thing.

Watson, the Case is a Foot

Understanding meaning isn’t as easy as we humans give it credit for. Computer scientists will tell you that the most valid results come from providing enormous data sets for a cognitive system to learn from (big data analytics), and then allow it to identify patterns that develop over time. Giving a single speech is likely to provide atypical results. Since this is an atypical U.S. presidential election, it seemed appropriate to ask Watson to weigh in.

Cognitive systems are an emerging technology. I’ve worked with semantic matching engines for over a decade and know much about their horrific abilities to misinterpret and misunderstand. It’s easy to poke fun at them and find their deficiencies relative to human understanding. However, it’s even more amazing to see what they can do and what they do get right.  IBM is aligning their business to the rise of cognitive systems, and it’s making a difference. IBM Watson Healthcare is helping improve healthcare performance at a local and global level. IBM Watson is beginning to focus on helping improve education, and is making inroads into banking.

Elementary, Dear Watson

After all Watson’s analysis of the candidate’s acceptance speeches, where does it leave me? Where does it leave you? Us?

Watson conclusively found Donald Trump’s speech to be significantly more negative than Hillary Clinton’s.  It did an amazing job of correctly extracting and interpreting much of the speeches text with the whimsical, endearing, and head-scratching exceptions noted above. Overall, Watson leads us to the two questions we really want the answer to: “Who will win?” and “What will that mean?”


Data Summaries

The tables below are directly taken from Watson’s search results. Notes are indicated to help address any confusion and anomalies.Watson Presidential Test - Entities

Watson Presidential Test - Keywords 

Watson Presidential Test - Targeted Segment

Watson Presidential Test - Concepts

Watson Presidential Test - Taxonomy


Watson Presidential Test - Emotion



Are we at the cusp of actually achieving a comprehensive education-to-employment cloud?

The Institute for Higher Education Policy has published a fantastic infographic mapping a rubric’s cube of the relationships between workforce, post-secondary, and  employment data. This provides unparalleled opportunities for innovation, insights, and deep analytics to significantly improve the education-to-employment and pathways to prosperity systems.

As many of you know, I’ve long advocated for advancements in the systems to assess the unified data.  IBM’s Watson cognitive system approach offers an immense opportunity to significantly improve the system. Their integration of big data, analytics, artificial intelligence, semantic learning, audio and text analysis and transformation, emotional intelligence, and visual learning coupled with big data analytics has already shown extreme value in advancing healthcare. IBM just announced their launch of Watson Education to apply the same platform to the field of higher education and vocational training. They are working with Pearson on developing a system, and have several outlier partners working on trying to change the game. The same technologies can, and will one day, be applied to workforce and education-to-employment. Anyone who wants to learn more or undertake a project to apply Watson to big data, give me a call at (984) 212-2285 or email at

In partnership with the Workforce Data Quality Campaign (WDQC) and the State Higher Education Executive Officers Association (SHEEO)PostsecData, an initiative of the Institute for Higher Education Policy, released an infographicMapping Postsecondary and Workforce Information Gaps in State Data Systems, that explores the data that exists in and is missing from State Longitudinal Data Systems (SLDS).

SLDS match data from different state sources about individuals over time and serve as an important resource for state policymakers, researchers, and the public. While there are challenges to filling in the information gaps that exist in these systems, stakeholders need these privacy-protected data to understand how individuals progress through K-12, postsecondary education, training, social service programs, and the workforce to help people access credentials, employment, and higher earnings in the states.

Click here to learn more about the data that do and do not exist in SLDS and learn more about the Institute for Higher Education Policy.

Click here to view the infographic

About the Institute for Higher Education Policy

The Institute for Higher Education Policy (IHEP) is an independent, nonprofit organization that is dedicated to increasing access and success in postsecondary education around the world. Established in 1993, the Washington, D.C.-based organization uses unique research and innovative programs to inform key decision makers who shape public policy and support economic and social development. IHEP’s web site,, features an expansive collection of higher education information available free of charge and provides access to some of the most respected professionals in the fields of public policy and research.