Cognitive Design

Mathematics education needs more cognitive design.  A lot more and fast.

Most math is presented in a way that grates against how our minds really work and leads to student frustration and failure.  The clearest signal of this is that students often ask “how does this relate to the real world” and claim they just don’t get math or even hate it.  The world runs on math and hate is a strong emotion.

And it is not just math.  STEM or science, technology, engineering and math education is under intense scrutiny in the US right now.   STEM education is linked to US competitiveness and appears to be failing by many measures especially in K-12. Without a large and creative STEM knowledge base it will be very hard to be a major economic player in the 21st century.

So I am also on the look out for new points of view on STEM education, especially those that are optimized for how our minds really work.   For example,  the New York Times has a recent OP-ED piece,  How to Fix our Math Education, that presents such a view.  They point out that our current approach to teaching math is very theoretical and that we should consider the development of quantitative literacy or reasoning.   To quote:

“Imagine replacing the sequence of algebra, geometry and calculus with a sequence of finance, data and basic engineering. In the finance course, students would learn the exponential function, use formulas in spreadsheets and study the budgets of people, companies and governments. In the data course, students would gather their own data sets and learn how, in fields as diverse as sports and medicine, larger samples give better estimates of averages. In the basic engineering course, students would learn the workings of engines, sound waves, TV signals and computers. Science and math were originally discovered together, and they are best learned together now.”

Our minds do naturally reason quantitatively.  Leveraging that to teach the abstract principles and reasoning of math is good cognitive design.   There is great power in mathematical understanding and quantitative reasoning. What we need to do is design experiences where students feel that power in their gut.

On-line enrollment ends September 20. 

I am often asked by students interested in cognitive design about the best classes to take. I always recommend at least one class in artificial intelligence (AI). An introduction to AI is necessary to make good decisions about the role of smart artifacts and machine intelligence on any cognitive design project.  Once a niche, smart artifacts and various degrees of sophistication are appearing everywhere.

Starting this Fall (10 weeks from Oct 10 to Dec 26), you will be able to take a top-flight introductory class in AI from Stanford for free.  It is the full version of the course including graded assignments and exams and the ability to ask questions as if you were a Stanford student.  If you pass you will receive a letter of completion that includes your rank.  More importantly, you will gain insight into the workings and limitations of of machine intelligence.

The class does assume an understanding of probability and linear algebra.  It will take about 10-15 hours of effort a week. If you don’t know AI and are serious about cognitive design, I suggest you complete this course.

Androids or human like robots are growing in numbers. We see them in video games and films as well as in the real-world as service bots.    Some androids gives us the creeps others we like. A brain scanning study just reported from UC San Diego, Your Brain on Androids, helps to explain this difference.  It turns out that androids that look too human but don’t also move in a perfectly human way, give us the creeps. On the other hand, androids that move more like robots and look more like robots are fine.

Our brains expect a match between the level of human-like appearance and motion

Not a surprise to readers of the cognitive design blog. If it looks human but moves robot we have colliding mental models and cognitive dissonance.  If the visual differences are subtle and we cannot put our finder on the source of cognitive dissonance it could get creepy.  The importance of the UC San Diego study is that they saw this in our neural hardware and were able to study the range of the effect.  The finding are summarized in terms of the “uncanny valley effect” when our feelings about an android suddenly go negative because it looks too human.

From a cognitive design perspective, this finding about the mismatch between appearance and motion could generalize across artifacts to produce opportunities for innovation.   For example, looks like a car but does not move like a car. The challenge is to find a way to leverage it to produce interest or positive mental energy.  In this example, a human doing a robot dance has nearly 6 million view.

 Source of Image: UC San Diego news release.

Deadline for submission is August 3, 2011 by 5pm EDT 

STEM or science, technology, engineering and mathematics is a big driver of innovation and economic progress in the US. Providing high-quality public education in STEM is therefore vital to growing the US economy.  Our global rankings in STEM education have been slipping and elective enrollment in STEM areas has been falling.  The old model of STEM fails to meet the psychological needs and demands of 21st century students in the US.

Teaching and learning STEM involves all dimensions of our minds – intellectual, emotional, motivational and volitional and therefore retooling it is a major cognitive design challenge.   Making real progress in public STEM education requires designing new learning processes optimized for how the minds of US students really work.

One approach to improve STEM education is to more deeply involve professionals, companies and other community resources with STEM expertise in the learning process. To help bring focus to this approach, Changemakers working with the Carnegie Corporation and The Opportunity Equation has launched a STEM competition around the theme:

“Partnering for Excellence: Innovations in Science + Technology + Engineering + Math Education, an online collaborative competition, will spur creative ways for companies, universities, and other organizations with expertise in the STEM fields to partner with the public schools that need their talent. We are looking for models that bring STEM expertise into public schools, thereby using resources from the private and not-for-profit sectors in new ways to further student learning designed with a “long term, part time” approach (see visual below)”

As of this post there are a 101 entries. The deadline for submission is 5pm ET on August 3rd.  While there are several cash prizes to win, the real value might be in the community-based feedback you received on your proposal.

Over the last 30 years or so  cognitive science has empirically shattered many of our basic assumptions about how the mind works.  For example, we traditionally viewed human memory as a passive observe-store-record device that objectively captured information about the world. Now we understand memory as actively being constructed (rather than recorded) from information, expectations and mental models. We dynamically create our understanding of the world, we don’t document it like a tape recorder.

To see how dramatically our understanding of what we hear is shaped by the expectations we have, take six minutes to experience Stairway to Heaven Run Backwards.

Priming effects or other features and functions that create expectations before perceptions, are powerful cognitive design techniques.  We make perceptions we do not have them.

Technology review has a provocative article on Lovotics (Love + Robotics) that introduces the “new science of engineering human, robot love.”  Looking beyond industrial, service and social robots, we have lovotics or devices designed for the emotion of love.   One is pictured below.

Check out this two minute video on its design and operation. Even if this may be a bit extreme, there is little doubt that robotic devices on many types are evoking emotional states in people. Human-robot relationship management is on the rise.

Interested to hear from readers on the cognitive design of human-robot emotional relationships.

The Economist and the global innovation marketplace Innocentive, have teamed up to offer a $10,000 prize to anyone that develops a novel metric for measuring tends in Human Potential.

More specifically, the metric or index should measure how well a region or a country is able to unleash and leverage intellectual energy for social and economic progress.

One example is the Gross National Happiness metric. Your metric does not have to be fully developed but you need to be able to explain how to collect that data to calculate it.

 The deadline for entries in June 20th and the winner will have expenses paid to present at the Ideas Economy conference on Human Potential in September.

For most organizations knowledge management (KM) means trying to get employees to share knowledge amongst each other or for codification into an on-line repository. By one report, firms spent $70 billion dollars on KM systems in 2008. A huge investment in knowledge sharing with little to no return. The reason? Generally employees don’t want to share knowledge, or if they do they have already figured out how to do it.

This issue is explored rigorously for the first time (as far as I know), in a just published article in the Journal of Organizational Behavior on Knowledge Hiding in Organizations. The researchers found that employees tended to engage in three modes of knowledge hiding including evasive hiding, rationalized hiding and playing dumb.  While engaging in knowledge hiding is driven principally by mistrust there are individual and organizational psychographic factors involved as well.

The prevalence of knowledge hiding despite a huge technology investment to the contrary signals that we cannot ignore the underlying cognitive psychology of knowledge work if we want to create value with KM.

It is time to step back from our technologically-driven and psychologically oversimplified approaches to KM and ask – what is knowledge and how can we manage it based on how minds really work?  KM needs a good dose of cognitive design STAT.

Talk about out doing the change in millennium.

With population growth, the use of fossil fuels, atomic bomb tests and the like human activities are having a deep and lasting impact on the Earth.  No news here but some leading intellects are arguing that the impact is so deep we must declare a new epoch of geologic time. They call it the Anthropocene (Man made) era and it:

“…represents a new phase in the history of both humankind and of the Earth, when natural forces and human forces became intertwined, so that the fate of one determines the fate of the other. Geologically, this is a remarkable episode in the history of this planet.”

For a great overview check out the theme issue of The Philosophical Transactions of the Royal Society:

The Anthropocene: A New Epoch of Geological Time? Follow the link to the journal and all the articles are free on-line.

The introduction might be of most use to designers. Assuming the Anthropocene has merit, there is likely no stronger argument to be made for the value and importance of design. We could even be so bold as to call it the Design Epoch.  Less technical but meaning the same thing, namely made by people.

I did a post earlier introducing MIX the Management Information Exchange, an exciting attempt to use open innovation to reinvent management for the 21st century.  They are running a series of prizes, called M-prizes, to help focus the creativity of the crowd.  

I submitted an entry, To Engage and Impassion Employees we Must Learn to Manage Mental Energy, to the M-Prize for Human Capital Management.  Here is the summary:

“A key to unleashing human capability in the workplace is to develop a management discipline geared toward creating intangible as well as economic value by meeting the psychological needs of key stakeholders.  Such a management discipline must be based on a modern scientific understanding of how minds work and will need to provide frameworks for estimating, measuring, creating and optimizing mental energy.”  

Check it out and leave comments.  There are currently 65 other entries that are worth a peak. I will summarize the results from a cognitive design perspective and do additional posts.