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This is the tenth of a
series of IAE Newsletters exploring educational aspects of the current
cognitive neuroscience and technological revolution. Bob Sylwester
(Newsletter # 75) and Dave Moursund (Newsletter # 76) provide two
introductory articles. Newsletter #77 and subsequent newsletters are mainly being written by guests. However, Sylwester and
Moursund also intend to contribute to this emerging collection.
For the most part, these articles will focus on cognitive neuroscience.
However, Dave Moursund will provide Information and Communication
Technology follow-up commentary to the articles. In addition, readers
are invited to send their comments using the Reader Comments directions
near the end of this newsletter.
We encourage you to tell your colleagues and students about the free
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Appropriate 21st Century Education:
Using Computers to Translate Educational
Theory into Practice
Emeritus Professor, University of Oregon
I taught in the College of Education at the University of Oregon for
many years. This College of Education is a powerhouse in educational
I taught preservice teachers who already had extensive educational
coursework and I also taught many inservice teachers. With each new
batch of students, I liked to start out by pointing out the hundreds of
educational research studies and papers that have come from the UO, and
that this is a very small percentage of nationwide and worldwide
educational research. I would then pose the following question for
Give examples of educational
research that has made a significant difference in the quality of education
of students you are preparing to teach or have taught.
I was always disappointed by the paucity and quality of answers. My
students did not seem to think in terms of how education is being
improved by educational research and translating this research into
effective, everyday teaching practices. They had little insight into
roles of computers in this translation process.
Theory Into Practice: A Personal Example
A number of years ago one of my grandsons and his parents were living
in my home. At the end of the second grade this boy’s report card
indicated he had made no progress in reading during that year.
Somewhat by luck and happenstance, my summer reading for that summer
included the Sally Shaywitz’s book Overcoming
Dyslexia (Shaywitz, 2003). As I read the book, I soon decided
that my grandson had dyslexia. Subsequent testing indicated he was
severely dyslexic. A long intervention included about an hour a day of
one-on-one help from well-trained and educated specialists. I am happy
to report that recently my grandson was inducted into the high school
national honor society and is well prepared to go on to college.
This is a good example of translating educational research theory into
practice. My grandson’s K, 1, and 2 teachers did not recognize his
dyslexia problem. And, once recognized, the school system was slow to
mount a strong intervention. The Individual Education Plan (IEP) planning
process and implementation were slow and did not initially commit the necessary
resources. Fortunately, I knew the right people in the school
district leadership, and the end result was good.
This example illustrates a major challenge in our educational system.
In summary, the challenge consists of:
Early detection of a problem.
High quality research that has focused on the problem leading to
the production and wide dissemination of effective methods for
detection and solution.
High fidelity implementation of a solution. There is also the
issue of cost effectiveness. Our overall educational system has limited
resources and so must balance the use of these resources among many
different worthy demands.
Wide Scale Detection and Solution
It is my opinion that my grandson’s dyslexia problem should have been
detected by his K or 1 or 2 teachers, and immediately been referred to
Recently I have been reading about dyscalculia. Roughly speaking,
dyscalculia is to learning arithmetic as dyslexia is to learning to
read. The comorbidity of these two learning disabilities is about 60%
(Mills, 2011). Both dyslexia and dyscalculia strongly affect perhaps
six to eight percent of the population. Both can be detected at an
early age. Quoting from Mills, 2011):
… about 60% of those
diagnosed with either dyscalculia or dyslexia have
the other condition as well Further, it was already known that
dyslexics had significant problems with math as well as with reading.
Landerl's studies, however, showed clearly that the two conditions,
dyscalculia and dyslexia, had completely different cognitive profiles
and the symptoms were additive
in the combined ("co-morbid") group.
This suggested strongly that the two conditions affected different
Dyslexia has been much more thoroughly studied than dyscalculia.
Multi-sensory intervetions have proven successful. Uses of
computers range from providing dyslexic students a with a word
processor having a good spelling checker (see http://www.dyslexia-parent.com/oregon.html) to use of computer software designed to help poor readers (see the work of Nadine Gaab described at http://www.youtube.com/watch?v=mG8pZx9O-y8).
Wouldn’t it be nice if cognitive neuroscience researchers could
identify the specific brain area associated with dyscalculia and
develop interventions that would alleviate the problem? The good news
is that this has been accomplished.
Early research is summarized in (Attridge et al., n.d.). Quoting from
There is evidence that
humans and some non-human animals have an innate
Approximate Number System (ANS) that allows us to rapidly, but only
approximately, represent numerosity. Children and adults appear to use
these representations to compare, add and subtract non-symbolic
quantities with above-chance accuracy.
Furthermore, it has been suggested that the ANS may be the basis of
formal mathematical ability in humans, and a relationship between
individual differences in ANS acuity and mathematical ability in
children has been demonstrated. Following from this hypothesis,
interventions have been designed to strengthen the relationship between
ANS representations and symbolic number representations in children,
with the hope of improving their mathematics skills.
Mills (2011) presents more recent research on the detection as well as
success of computer-based interventions.
In this document he also reviews various poorly designed and/or poorly
Intelligent Computer-Assisted Learning
We know a great deal about reinforcement schedules in learning,
immediate feedback, wait time in accepting student responses in
teaching, study skills, and so on. However, consider the challenge of
training/educating millions of precollege teachers to implement such
ideas with high fidelity. It is clear to me that our preservice and
inservice teacher education system is not up to this task.
However, such research-based practices can be implemented in
well-designed computer-assisted learning systems. Modern systems of
this sort are often called Highly Interactive Intelligent
Computer-Assisted Learning (HIICAL) systems. In a variety of teaching
environments such systems are proving to be considerably more effective
than traditional teaching by traditional teachers (Moursund, 2012).
This educational progress is based on our increasing understanding of
the capabilities and limitations of human and computer brains
(Moursund, 2011). High quality HIICAL is not a magic drug (like an
antibiotic) that cures some diseases. However, HIICAL is gradually
becoming the tool of choice in a variety of education and training
Good progress is occurring in educational neuroscience (Sousa, 2010). I
have mentioned a few areas in this IAE Newsletter in which computer
technology can help in solving some major educational problems.
Generally speaking, educational improvement interventions that are
partially or fully computerized lend themselves to:
Easy gathering of data during the intervention process.
Incremental improvement based on an analysis of the intervention
Of course, data gathering about summary results and long-term residual
impact face the same problems that researchers face in dealing with
non-computerized interventions. Information and Communication
Technology is not the “be all end all”. As an example, consider stress
related to growing up in poverty and other challenges students face in
and outside of school. Merely providing students with computers to use
at home and at school does not address these sources of stress. Or,
consider what we now know about roles of good diet and adequate
exercise as they relate to the human brain. While computers may help a
little in this problem area, they are far from being a solution.
Shaywitz, Sally (2003). Overcoming dyslexia: A new and complete
science-based program for reading problems at any level. New
York: Alfred A. Knopf.
Sousa, David (Editor) (2010). Mind, brain, and education: Neuroscience
implications for the classroom. Bloomington, Indiana: Solution
David Moursund earned his doctorate in mathematics from the University
of Wisconsin-Madison. He taught in the Mathematics Department and
Computing Center at Michigan State University for four years before
joining the faculty at the University of Oregon.
A few highlights of his professional career include founding the
International Society for Technology in Education (ISTE), serving as
its executive officer for 19 years, and establishing ISTE’s flagship
publication, Learning and Leading with Technology. He was a major
professor or co-major professor for more than 80 doctoral students. He
has authored or coauthored more than 55 academic books and hundreds of
articles. More recently, he founded Information Age Education (IAE), a
non-profit organization dedicated to improving teaching and learning by
people of all ages throughout the world.
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