In Memory: Seymour Papert — from; with thanks to Mr. Joe Byerwalter for this resource


Seymour Papert, whose ideas and inventions transformed how millions of children around the world create and learn, died Sunday, July 31, 2016 at his home in East Blue Hill, Maine. He was 88.

Papert’s career traversed a trio of influential movements: child development, artificial intelligence, and educational technologies. Based on his insights into children’s thinking and learning, Papert recognized that computers could be used not just to deliver information and instruction, but also to empower children to experiment, explore, and express themselves. The central tenet of his Constructionist theory of learning is that people build knowledge most effectively when they are actively engaged in constructing things in the world. As early as 1968, Papert introduced the idea that computer programming and debugging can provide children a way to think about their own thinking and learn about their own learning.


Also see:

  • AI and Computer Learning Lion Seymour Papert Dies at 88 — from by  Barb Darrow
    Seymour Papert, the MIT professor who helped blaze the trail for artificial intelligence and computer-aided education for children at a time when no one saw the potential for using these massive machines for such purposes, died Sunday at the age of 88 in East Blue Hill, Maine.


“In this particular art class they were all carving soap,” he continued, “but what each student carved came from wherever fancy is bred, and the project was not done and dropped but continued for many weeks. It allowed time to think, to dream, to gaze, to get a new idea and try it and drop it or persist, time to talk, to see other people’s work and their reaction to yours — not unlike mathematics as it is for the mathematician, but quite unlike math as it is in junior high school.”


  • Seymour Papert, 88, Dies; Saw Education’s Future in Computers — from by Glenn Rifkin
    Seymour Papert, a visionary educator and mathematician who well before the advent of the personal computer foresaw children using computers as instruments for learning and enhancing creativity, died on Sunday at his home in Blue Hill, Me. He was 88.



He added, “In the past, education adapted the mind to a very restricted set of available media; in the future, it will adapt media to serve the needs and tastes of each individual mind.”




From DSC:
Though the title of Ashley Coolman’s blog posting out at mentions technology in it, the article is largely not about technology at all — but rather about the benefits of active learning. That’s why I’m highlighting it here.


Enabling active learning through technology — from by Ashley Coolman


To many, it seems as though any learning can be considered active. Is a student taking notes not actively engaged in a class, especially when compared to their peers sleeping or playing on their phones in the back of the room?

The problem here is that while the note-taking student may be engaging with the class and professor, they are not engaging with the material. When furiously scribbling notes, students are more focused on getting every word down rather than evaluating, understanding, and analyzing what it is they are writing. They have engaged with the lecture, but not the material being relayed — which is the most important part.

In a study on active learning called “Active Learning: Creating Excitement in the Classroom”, the researchers stated:

“Surprisingly, educators’ use of the term “active learning” has relied more on intuitive understanding than a common definition. Consequently, many faculty assert that all learning is inherently active and that students are therefore actively involved while listening to formal presentations in the classroom. Analysis of the research literature (Chickering and Camson 1987), however, suggests that students must do more than just listen: They must read, write, discuss, or be engaged in solving problems. Most important, to be actively involved, students must engage in such higher-order thinking tasks as analysis, synthesis, and evaluation.” (Bonwell and Eison 1991)

It is the degree and form by which students are actively engaging that matters. It is “learning by doing” that students really need.


Active learning is any learning activity in which the student INTERACTS or ENGAGES with the material, as opposed to passively taking in the information.


Furthermore, Cornell University found that research suggests learner attention starts to wane every 10–20 minutes during lectures. Incorporating active learning techniques a few times throughout class can encourage more engagement.*

*A side note from DSC:
A tool like
Socrative may come in useful here.


The blog posting from Smart Sparrow also linked to this resource:



The problem is that lecture-based learning is not like filling a jug — you just don’t catch it all. Learning from lectures is more like holding out your hands and trying to keep the imparted knowledge from spilling through the cracks in this tidal wave of new information. Ultimately, students will catch some of the water, but most of it will be lost.


A side note from DSC to Calvin College faculty members:
If you doubt the immediately preceding quote, see if you can *fully* recall exactly what last Sunday’s sermon was about — including all examples, details, and wisdom that the preacher was trying to relay.

Ultimately, it’s about impact. What strongly impacts students stays with students — and isn’t that true for all of us?



Ashley lists the following resources re: active learning at the end of her posting:

  1. Using Active Learning Instructional Strategies to Create Excitement and Enhance Learning
  2. Active Learning: Creating Excitement in the Classroom
  3. Where’s the evidence that active learning works?
  4. How Does Active Learning Support Student Success?
  5. How To Retain 90% Of Everything You Learn




Connecting the education community with research on learning — from


When designing a program or product, many education leaders and ed-tech developers want to start with the best knowledge available on how students learn. Unfortunately, this is easier said than done.

Although thousands of academic articles are published every year, busy education leaders and product developers often don’t know where to start, or don’t have time to sift through and find studies that are relevant to their work. As pressure mounts for “evidence-based” practices and “research-based” products, many in the education community are frustrated, and want an easier way to find information that will help them deliver stronger programs and products — and results. We need better tools to help make research more accessible for everyday work in education.

The Digital Promise Research Map meets this need by connecting education leaders and product developers with research from thousands of articles in education and the learning sciences, along with easy-to-understand summaries on some of the most relevant findings in key research topics.


Also see:











From DSC:
If you can clear up just short of an hour of your time, this piece from PBS entitled, “School Sleuth: The Case of the Wired Classroom” is very well done and worth your time.  It’s creative and objective; it offers us some solid research, some stories, and some examples of the positives and negatives of technology in the classroom. It weaves different modes of learning into the discussion — including blended learning, online learning, personalized learning and more. Though it aired back in October of 2015, I just found out about it.

Check it out if you can!






Also see:

  • Schools push personalized learning to new heights — from
    For most schools, reaching the next level of digitally driven, personalized learning is far from reality. Still, some schools are extending their digital reach in significant and sometimes groundbreaking ways, as the stories in this special report illustrate. They are making moves to integrate a variety of technologies to track how students learn and to use the resulting data to expand the use of hands-on, project-based learning. The goal is to build never-ending feedback loops that ultimately inform the development of curriculum and assessment. Plus, big data and analytics are gradually making their marks in K-12 education. This special report outlines the progress schools are making to use digital tools to personalize learning, but also raises the question: Are they reaching far enough?
  • A Pedagogical Model for the use of iPads for Learning — from







Brain Based Learning and Neuroscience – What the Research Says! — from by Will Thalheimer, PhD

Excerpts (emphasis DSC):

The world of learning and development is on the cusp of change. One of the most promising—and prominent—paradigms comes from neuroscience. Go to any conference today in the workplace learning field and there are numerous sessions on neuroscience and brain-based learning. Vendors sing praises to neuroscience. Articles abound. Blog posts proliferate.

But where are we on the science? Have we gone too far? Is this us, the field of workplace learning, once again speeding headlong into a field of fad and fantasy? Or are we spot-on to see incredible promise in bringing neuroscience wisdom to bear on learning practice? In this article, I will describe where we are with neuroscience and learning—answering that question as it relates to this point in time—in January of 2016.

Taken together, these conclusions are balanced between the promise of neuroscience and the healthy skepticism of scientists. Note however, that when these researchers talk about the benefits of neuroscience for learning, they see neuroscience applications as happening in the future (perhaps the near future). They do NOT claim that neuroscience has already created a body of knowledge that is applicable to learning and education.

The field of workplace learning—and the wider education field—have fallen under the spell of neuroscience (aka brain-science) recommendations. Unfortunately, neuroscience has not yet created a body of proven recommendations. While offering great promise for the future, as of this writing—in January 2016—most learning professionals would be better off relying on proven learning recommendations from sources like Brown, Roediger, and McDaniel’s book Make It Stick; by Benedict Carey’s book How We Learn; and by Julie Dirksen’s book Design for How People Learn.

As learning professionals, we must be more skeptical of neuroscience claims. As research and real-world experience has shown, such claims can persuade us toward ineffective learning designs and unscrupulous vendors and consultants.

Our trade associations and industry thought leaders need to take a stand as well. Instead of promoting neuroscience claims, they ought to voice a healthy skepticism.



Also see:




The future belongs to the curious: How are we bringing curiosity into school? — from User Generated Education by Jackie Gerstein


A recent research study found a connection between curiosity and deep learning:

The study revealed three major findings. First, as expected, when people were highly curious to find out the answer to a question, they were better at learning that information. More surprising, however, was that once their curiosity was aroused, they showed better learning of entirely unrelated information that they encountered but were not necessarily curious about. Curiosity may put the brain in a state that allows it to learn and retain any kind of information, like a vortex that sucks in what you are motivated to learn, and also everything around it. Second, the investigators found that when curiosity is stimulated, there is increased activity in the brain circuit related to reward.  Third, when curiosity motivated learning, there was increased activity in the hippocampus, a brain region that is important for forming new memories, as well as increased interactions between the hippocampus and the reward circuit. (How curiosity changes the brain to enhance learning)




From DSC:
Jackie’s posting reminded me of what Daniel Willingham asserts:  “Memory is the residue of thought.”  | “We remember what we think about.”

So to me, if you can’t get through the gate — get someone’s attention — you have zero chance of getting into their short-term memory, and thus zero chance to get into that person’s long-term memory.



Along these lines, if a student is curious about something, their motivation level increases and they actually THINK about something. (What a concept, right?!)

But the point here is that what a student thinks about now has a chance to make it into that student’s memories…thus, creating a variety of hooks on which to “hang future hats” (i.e., make cognitive connections in the future).





Addendum on 11/24/15:

[Re: Emily Pilloton, founder and executive director of Project H Design] Her talk focused on three aspects of learning:

  • Seeking > Knowing. Pushing beyond your comfort zone is the way to challenge yourself. As mentioned above, Pilloton believes in experiential learning, in challenging students with big projects where they will learn new skills as needed to complete the project.
  • We > I. Teams and building trust in your teammates is critical. All of Pilloton’s projects are so big that no one person can complete them alone. By being forced to make decisions and learn to work as teams, group members realize that as a collective, they can achieve much more than they could individually.
  • Curiosity > Passion. Encouraging curiosity is more important than helping people find their passion. Pilloton argued that it is hard for many young people to know their passion. If we encourage curiosity and give students the opportunity to push the boundaries of what they think is possible, we provide them the opportunity to both build confidence and find their passion.





Chapter 2 of the Daniel Willingham’s book entitled,  Why Don’t Students Like School: A Cognitive Scientist Answers Questions About How the Mind Works and What It Means for the Classroom, lays out the best case for the liberal arts degree that I’ve ever seen or read about.

First of all, a description of the book:
Easy-to-apply, scientifically-based approaches for engaging students in the classroom
Cognitive scientist Dan Willingham focuses his acclaimed research on the biological and cognitive basis of learning. His book will help teachers improve their practice by explaining how they and their students think and learn. It reveals-the importance of story, emotion, memory, context, and routine in building knowledge and creating lasting learning experiences.

  • Nine, easy-to-understand principles with clear applications for the classroom
  • Includes surprising findings, such as that intelligence is malleable, and that you cannot develop “thinking skills” without facts
  • How an understanding of the brain’s workings can help teachers hone their teaching skills


From DSC:
Though more tangential to my main point here, I really appreciate Daniel’s bridging the worlds of research and teaching. He is knowledgeable about the relevant research that’s been done out there, and he uses that knowledge to inform his recommendations for how best to apply that research in the classroom. Often, it seems, these two worlds don’t get connected.  I also like how he models solid ways of teaching. For example, he knows that repetition helps, so he summarizes/repeats his main points throughout a chapter.

Speaking of chapters, here are some of my notes from chapter 2:

  • Factual knowledge must proceed skill. (p. 25)
  • We need factual knowledge before we can practice critical thinking or have the ability to analyze something (p. 25)
  • “Thinking well requires knowing facts, and that’s true not simply because you need something to think about. The very processes that teachers care about most — critical thinking processes such as reasoning and problem solving – are intimately  intertwined with factual knowledge that is stored in long-term memory…” (p. 28)
  • Critical thinking processes are tied to background knowledge (p. 29)
  • Thinking skills and knowledge are bound together (p.29)
  • “The phenomenon of tying together separate pieces of information from the environment is called chunking. The advantage is obvious: you can keep more stuff in working memory if it can be chunked. The trick, however, is that chunking works only when you have applicable factual knowledge in long-term memory.” (p. 34)
  • “Thus, background knowledge allows chunking, which makes more room in working memory, which makes it easier to relate ideas, and therefore to comprehend.” (p.35)
  • “…we don’t take in new information in a vacuum. We interpret new things we read in light of other information we already have on the topic.”  (p. 36)
  • “Not only does background knowledge make you a better reader, but it also is necessary to be a good thinker.” (p.37)
  • “When it comes to knowledge, those who have more gain more.” (p. 42)
  • “When it comes to knowledge, the rich get richer. (p.45 )
  • “…having background knowledge in long-term memory makes it easier to acquire still more factual knowledge.” (p. 44)
  • “Knowledge…is a prerequisite for imagination.” (p.46)
  • “The cognitive processes that are most esteemed — logical thinking, problem solving, and the like — are intertwined with knowledge.” (pgs. 46-47)


From DSC:
So the saying that “you get what you pay for” again turns out to be true.  That is, you will likely pay more for a 4-year liberal arts degree than what you will pay for a 10-12 week bootcamp.  But if you go to a bootcamp and come out knowing only how to code using programming language XYZ, you have far fewer cognitive “hooks” on which to hang new hats (i.e., new information).

A liberal arts degree covers and provides a great deal of knowledge — and it builds upon that knowledge with higher order skills. Such a degree provides a broader foundation of knowledge that creates numerous hooks on which to hang new hats in the future. 

These reflections regarding foundational knowledge and having hooks to hang new information on (and make new connections with) reminds me of Bloom’s Taxonomy.  Factual knowledge was the foundational layer of his original taxonomy:






So it seems to me that the size/breadth of the foundational layer that’s been built from a liberal arts degree is far broader and deeper than a foundational layer obtained from attending a bootcamp.  The numerous number of cognitive hooks that it provides will help a sharp, hard-working graduate of a liberal arts program be able to not only understand the business at hand, but to practice creative thinking, to practice critical thinking, and to be able to innovate.

I’m not saying that a graduate of a bootcamp can’t do some of those things as well. (I also think that bootcamps can definitely have a place in our learning ecosystems.) But chances are that such a person has already built a broader foundation of remembering and understanding to draw upon.


What do you think, am I off base here or does this thinking accurately reflect
one of the areas in which a liberal arts degree is important and provides real, lasting value?


Every learner is different but not because of their learning styles — from by Clive Sheperd


I’ve been reading Make it Stick: The Science of Successful Learning by Peter Brown and Henry Roediger (Harvard University Press, 2014). What a great book! It provides a whole load of useful tips for learners, teachers and trainers based on solid research.

Finishing this book coincides with The Debunker Club’s Debunk Learning Styles Month. And learning styles really do need debunking, not because we, as learners, don’t have preferences, but because there is no model out there which has been proven to be genuinely helpful in predicting learner performance based on their preferences.



Learning Styles are NOT an Effective Guide for Learning Design — from


Strength of Evidence Against
The strength of evidence against the use of learning styles is very strong. To put it simply, using learning styles to design or deploy learning is not likely to lead to improved learning effectiveness. While it may be true that learners have different learning preferences, those preference are not likely to be a good guide for learning. The bottom line is that when we design learning, there are far better heuristics to use than learning styles.

The weight of evidence at this time suggests that learning professionals should avoid using learning styles as a way to design their learning events. Still, research has not put the last nail in the coffin of learning styles. Future research may reveal specific instances where learning-style methods work. Similarly, learning preferences may be found to have long-term motivational effects.

Debunking Resources — Text-Based Web Pages



Learning Styles Or Learning Preference? — from by Justin Ferriman

Excerpts (emphasis DSC):

There are fewer buzzwords in the elearning industry that result in a greater division than “learning style”. I know from experience. There have been posts on this site related to the topic which resulted in a few passionate comments (such as this one).

As such, my intent isn’t to discuss learning styles. Everyone has their mind made up already. It’s time to move the discussion along.

Learner Preference & Motivation
If we bring the conversation “up” a level, we all ultimately agree that every learner has preferences and motivation. No need to cite studies for this concept, just think about yourself for a moment.

You enjoy certain things because you prefer them over others.

You do certain things because you are motivated to do so.

In the same respect, people prefer to learn information in a particular way. They also find some methods of learning more motivating than others. Whether you attribute this to learning styles or not is completely up to you.



How to respond to learning-style believers – from Cathy Moore


First, the research
These resources link to or summarize research that debunks learning styles:



Are Learning Styles Going out of Style? — from by Bruce Murray

Excerpt (emphasis DSC):

Their first conclusion was that learners do indeed differ from one another. For example, some learners may have more ability, more interest, or more background than their classmates. Second, students do express preferences for how they like information to be presented to them… Third, after a careful analysis of the literature, the researchers found no evidence showing that people do in fact learn better when an instructor tailors their teaching style to mesh with their preferred learning style.

The idea of matching lessons to learning styles may be a fashionable trend that will go out of style itself. In the meantime, what are teachers and trainers to do? My advice is to leave the arguments to the academics. Here are some common-sense guidelines in planning a session of learning.

Follow your instincts. If you’re teaching music or speech, for example, wouldn’t auditory-based lessons make the most sense? You wouldn’t teach geography with lengthy descriptions of a coastline’s contours when simply showing a map would capture the essence in a heartbeat, right?

Since people clearly express learning style preferences, why not train them in their preferred style? If you give them what they want, they’ll be much more likely to stay engaged and expand their learning.



Do Visual, Auditory, and Kinesthetic Learners Need Visual, Auditory, and Kinesthetic Instruction? — from by Daniel T. Willingham

Excerpt (emphasis DSC):

Question: What does cognitive science tell us about the existence of visual, auditory, and kinesthetic learners and the best way to teach them?

The idea that people may differ in their ability to learn new material depending on its modality—that is, whether the child hears it, sees it, or touches it—has been tested for over 100 years. And the idea that these differences might prove useful in the classroom has been around for at least 40 years.

What cognitive science has taught us is that children do differ in their abilities with different modalities, but teaching the child in his best modality doesnt affect his educational achievement. What does matter is whether the child is taught in the contents best modality. All students learn more when content drives the choice of modality. In this column, I will describe some of the research on matching modality strength to the modality of instruction. I will also address why the idea of tailoring instruction to a students best modality is so enduring—despite substantial evidence that it is wrong.


From DSC:
Given the controversies over the phrase “learning styles,” I like to use the phrase “learning preferences” instead.  Along these lines, I think our goal as teachers, trainers, professors, SME’s should be to make learning enjoyable — give people more choice and more control. Present content in as many different formats as possible.  Give them multiple pathways to meet the learning goals and objectives.  If we do that, learning can be more enjoyable and the engagement/motivation levels should rise — resulting in enormous returns on investment over learners’ lifetimes.


Addendum on 6/17/15:


Addendum on 7/14/15:


From DSC:
Learning is messy.  Teaching & learning is messy. 

In my experience, teaching is both an art and a science.  Ask anyone who has tried it and they will tell you that it’s not easy.  In fact, it takes years to hone one’s craft…and there are no silver bullets. Get a large group of Learning Theorists together in the same room and you won’t get 100% agreement on the best practices for how human beings actually learn.

Besides that, I see some issues with how we are going about trying to educate today’s learners…and as the complexity of our offerings is increasing, these issues are becoming more apparent, important, visible, and costly:

  • Professors, Teachers, & Trainers know some pieces of the puzzle.
  • Cognitive Scientists, Cognitive Psychologists, and Neuroscientists know some other pieces of the puzzle.
  • Learning Theorists and Instructional Designers know some other pieces of the puzzle.
  • Learning Space Designers know some other pieces of the puzzle.
  • And yet other specialties know about some other pieces of the puzzle.

But, in practice, how often are these specialties siloed? How much information is shared between these silos?  Are there people interpreting and distilling the neuroscience and cognitive science into actionable learning activities? Are there collaborative efforts going on here or are the Teachers, Professors, and Trainers pretty much on their own here (again, practically speaking)?

So…how do we bring all of these various pieces together? My conclusion:

We need a team-based approach in order to bring all of the necessary pieces together. We’ll never get there by continuing to work in our silos…working alone.

But there are other reasons why the use of teams is becoming a requirement these days: Accessibility; moving towards providing more blended/hybrid learning — including flipping the classroom; and moving towards providing more online-based learning.

We’re moving into a world whereby lawsuits re: accessibility are becoming more common:

Ed Tech World on Notice: Miami U disability discrimination lawsuit could have major effect — from by Phil Hill
This week the US Department of Justice, citing Title II of ADA, decided to intervene in a private lawsuit filed against Miami University of Ohio regarding disability discrimination based on ed tech usage. Call this a major escalation and just ask the for-profit industry how big an effect DOJ intervention can be. From the complaint:

Miami University uses technologies in its curricular and co-curricular programs, services, and activities that are inaccessible to qualified individuals with disabilities, including current and former students who have vision, hearing, or learning disabilities. Miami University has failed to make these technologies accessible to such individuals and has otherwise failed to ensure that individuals with disabilities can interact with Miami University’s websites and access course assignments, textbooks, and other curricular and co-curricular materials on an equal basis with non-disabled students. These failures have deprived current and former students and others with disabilities a full and equal opportunity to participate in and benefit from all of Miami University’s educational opportunities.

Knowing about accessibility (especially online and via the web) and being able to provide accessible learning materials is a position in itself. Most faculty members and most Instructional Designers are not specialists in this area. Which again brings up the need for a team-based approach.

Also, when we create hybrid/blended learning-based situations and online-based courses, we’re moving some of the materials and learning experiences online. Once you move something online, you’ve entered a whole new world…requiring new skillsets and sensitivities.

The article below caused me to reflect on this topic. It also made me reflect yet again on how tricky it is to move the needle on how we teach people…and how we set up our learning activities and environments in the most optimal/effective ways. Often we teach in the ways that we were taught. But the problem is, the ways in which learning experiences can be offered these days are moving far beyond the ways us older people were taught.


Why we need Learning Engineers — from by Bror Saxberg

Excerpt (emphasis DSC):

Recently I wandered around the South by Southwest ed-tech conference, listening to excited chatter about how digital technology would revolutionize learning. I think valuable change is coming, but I was struck by the lack of discussion about what I see as a key problem: Almost no one who is involved in creating learning materials or large-scale educational experiences relies on the evidence from learning science.

We are missing a job category: Where are our talented, creative, user-­centric “learning engineers” — professionals who understand the research about learning, test it, and apply it to help more students learn more effectively?

So where are the learning engineers? The sad truth is, we don’t have an equivalent corps of professionals who are applying learning science at our colleges, schools, and other institutions of learning. There are plenty of hard-working, well-meaning professionals out there, but most of them are essentially using their intuition and personal experience with learning rather than applying existing science and generating data to help more students and professors succeed.


Also see:

  • Why you now need a team to create and deliver learning — from by Mary Grush and Daniel Christian
    Higher education institutions that intentionally move towards using a team-based approach to creating and delivering the majority of their education content and learning experiences will stand out and be successful over the long run.”


Addendum on 5/14/15:

Thinking different(ly) about university presses — from by Carl Straumsheim

Excerpt (emphasis DSC):

Lynn University, to further its tablet-centric curriculum, is establishing its own university press to support textbooks created exclusively for Apple products.

Lynn University Digital Press, which operates out of the institution’s library, in some ways formalizes the authoring process between faculty members, instructional designers, librarians and the general counsel that’s been taking place at the private university in Florida for years. With the university press in place, the effort to create electronic textbooks now has an academic editor, style guides and faculty training programs in place to improve the publishing workflow.

© 2016 Learning Ecosystems