Neuroscience and the Hype Cycle

Neuroscience and the Hype Cycle

Neuroscience and the Hype Cycle

Image: Wikipedia 
https://en.wikipedia.org/wiki/Hype_cycle[1]

I recently attended a major conference of learning professionals and was surprised to hear one of the keynote speakers say, “Neuroscience has nothing to offer educational psychology today.” While many in the room were applauding, I was a little shocked and disappointed. I get it. We’ve all seen the over-hyped, overly commercialized claims of people who are getting rich off their own flavor of “The Neuroscience of X” (Fill in any topic you wish and start making money.) But that doesn’t mean that all of neuroscience is worthless hype or too esoteric to be useful. Einstein’s Theory of General Relativity[2]destroyed Newtonian physics on the sub-atomic level, but Newton continues to be studied in school and his model is very effective for describing the works of the macro-atomic world. If we refuse to integrate new discoveries into our practice, we run the risk of becoming out of date and out of touch with the advance of science. The past decade has seen a growing interest in the application of neuroscience to teaching and training, along with the rise of whole new industry around the use of promise of neuroscience to change your life by changing your brain. Is any of it true? Well, that may depend on where you are in the “Hype Cycle.”

Understanding the Hype Cycle

Gartner, Inc., the research and consulting firm, has identified a pattern related to the introduction of new technology called the Hype Cycle[3]. It begins with the development of a new technology. Shortly after the technology is invented or discovered, there is a surge of interest and enthusiasm for the use of the technology. Wildly optimistic predictions about the use of the technology circulate and become part of the popular culture. Shortly after this “peak of inflated expectations,” there is a sudden plunge into the “trough of disillusionment” as scientists and the public begin to realize that much more work needs to be done before this exciting new technology can be fully implemented. Then a more gradual upward slope begins as practitioners methodically build the procedures to leverage this new technology safely and effectively. During this “slope of enlightenment,” scientists are actively working with the technology and adding to the pool of knowledge, but the public may still be primarily in the trough of disillusionment. Finally we reach a point Gartner calls the Plateau of Productivity. At this point scientists and public have a solid understanding of the promise and limitations of the technology and we begin to see significant benefits from the wider application of the tool.

Since the entire field of neuroscience was triggered by the use of Magnetic Resonance Imaging (MRI) to study live brain activity, understanding this curve can help explain why we have such a schizophrenic view of neuroscience in our field today. Unlike x-ray machine, which use radioactive waves to generate an image of the interior of the body, the MRI uses harmless radio waves[4] to stimulate the protons in the cells of the body to emit a magnetic charge. When the machine is turned off, we can take a snapshot of the magnetic transmissions and can use this data to generate images of the soft tissue in the body, down to very precise “slices.” In 1977, the first use of the MRI for scanning a human body took place. The MRI quickly became a powerful medical diagnostic tool for a wide array of illnesses. In 1992, fifteen years after the introduction of MRI device, the functional MRI (fMRI)[5] was first used to measure blood flow in the brain of a live human being. The fMRI differs from the traditional MRI machine in one significant respect. It has been calibrated to measure the amount of blood flow in different regions of soft tissue in real time. Since blood flow is believed to correlate with the amount of activity taking place in a given region of the brain, we now have a window into the brain so that we can watch it in the act of learning, remembering, or any other brain function. Other technologies and techniques followed rapidly, along with excited claims about how we can leverage our new understanding of the brain.

We are in the Trough of Disillusionment with Neuroscience

Recently the brain training system Lumosity[6]has been forced to revise their claims of delivering brain health through their online games and many experts have understandably urged caution in rushing to conclusions based on this very young science. I still believe that we can start applying neuroscience to help people learntoday. It just seems reasonable to me that any valid scientific approach to understanding the brain should have direct and practical applications to my work in instructional design and teaching. I also believe that we can trust ourselves to apply those conclusions to our work. We may even be able to add to the general body of knowledge in our field by sharing our work and sharing our data with our peers. I disagree with those who dismiss neuroscience as a modern form of “snake oil.” There actually are some valid uses of snake oil, after all. Of course, let’s use caution in the application and make sure we are working with data derived through the application of the scientific method. We can choose to ignore the promise of neuroscience simply because we have become aware of its limitations or we can use our wonderful brains to determine where and how we can start leveraging its discoveries. We may need to let go of some of our cherished practices in the light of new evidence. We may also find that many of our most respected models from educational psychology are further validated by the hard evidence placed before us through neuroscience.

Neuroscience Isn’t the Only Science that Illuminates the Learning Process

Neuroscience isn’t the only science that sheds light on the learning process; they all do. The science of learning is really an amalgam of nearly every science known today. At the very least, understanding how our brain works requires collating information from psychology, computer science, mathematics, biology, chemistry and quantum physics. There is also much that we can learn from mysticism, meditation and philosophy. If you share my passion for helping people learn, you’ll join me in applying evidence-based knowledge wherever we find it. Let’s not be picky about whether or not a given discipline is fashionable; let’s not reject certain evidence just because some of the witnesses come off as a little bit shady. If a body of knowledge has something to offer, I believe it is our duty to find a way to apply it to move the learning profession forward. Please feel free to disagree with me. All I ask is that you keep an open and inquisitive mind and use scientific evidence as the basis for your conclusions.

 

References

  1. ^https://en.wikipedia.org/wiki/Hype_cycle (en.wikipedia.org)
  2. ^Einstein’s Theory of General Relativity (www.nobelprize.org)
  3. ^Hype Cycle (www.gartner.com)
  4. ^harmless radio waves (science.howstuffworks.com)
  5. ^functional MRI (fMRI) (www.ndcn.ox.ac.uk)
  6. ^Lumosity (www.wired.com)

Read more http://www.2elearning.com/insights-blogs/blogs/entry/neuroscience-and-the-hype-cycle

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