Flash-forward to 2010. I’m working a project for a small South San Francisco biotech company. There are five of us on the consulting team, and three of us, including the project manager, are ex-Vitessians. As Phase One of the project winds downs, the project manager tells me that another ex-Vitessian is working full-time now at Lam Research, and that his group is looking to hire a full-time instructional designer. I thanked my project manager for the tip and contacted my former colleague about the opportunity. In July we had a couple of phone conversations, and his enthusiasm for the company convinced me that I should apply for the job. A phone interview and two in-person interviews followed, and in early September I began working for Lam Research’s Global Learning & Development group as their newest, full-time senior instructional designer.

Landing a good full-time, salaried position in the current job market can be kind of tough. I’d actually been looking, on and off, for several years, whenever working as an independent consultant seemed to be leading me into poverty. But, while I suspect my skills and portfolio helped seal the deal, I don’t believe I would even have been considered if it weren’t for the support I received from the inside from my former colleague from Vitesse.

The lesson I take away from this experience is that if you are looking for a job, one of the most important things you can do is to leverage your professional network.

Alternately fascinating and boring, this detailed summary of Pepperberg’s 20+ years of careful research into the cognitive and communicative capabilities of her avian subjects is primarily aimed at other scientists. It is not an especially difficult read—though I admit I did merely skim or outright skip over much of chapters 15 (signal analysis of parrot speech formants) and 16 (physiology of how parrots produce their vocalizations)—but it is a fairly dry, academic presentation.

Her results are quite interesting, though. Parrots have cognitive capacities that in many instances equal those of the Great Apes, which is certainly not a result one expects. “Bird-brain” may have to take on a new meaning synonomous with “smart.” Her main subject, “Alex,” can answer questions about quantity, color, shape, relative sameness or differentness of objects, and even about the absence of sameness or difference.

Of special interest is the method she used to train her subject birds. She developed her method, which she calls “Model/Rival” and abbreviates “M/R”, based upon studies of how the birds learned in their natural environment. In Model/Rival training sessions, a human trainer interacts with a human partner in the presence of the bird. The trainer asks the other human a question, such as “What color?” or “How many?” while presenting one or more objects. The other human acts both as the model for the bird and as a rival for the trainer’s attention. This Model/Rival either answers the question correctly (modeling the behavior for the bird), or answers it incorrectly and gets scolded. Trainer and model switch roles frequently, to prevent the bird from associating a question with a particular person.

This training method has been very successful, and I wonder if it would make an effective pattern for use in e-learning aimed at humans. I hope to try it out some day: “You and your annoying co-worker Bob are both bucking for the same promotion. Your boss will promote whichever one of you demonstrates the greater mastery over this material. Click Begin when you are ready to compete with Bob by answering the following questions. Don’t take too long, though, because if you don’t answer quickly enough, Bob will chime in with his answer.”

Well, maybe something like that anyway.

This book is part of the “Maps of the Mind” series, edited by Steven Rose. Other books I’ve read in this series, including James McGaugh’s Memory and Emotion: The Making of Lasting Memories and Rusiko Bourtchouladze’s Memories Are Made of This, have been excellent. So it was with high expectations that I started to read this book. Alas, it’s not especially well-written. I’ve read better books on aging (e.g., William Clark’s very good A Means To An End), and better books on Alzheimer’s disease (particularly William Shankle and Daniel Aman’s excellent Preventing Alzheimer’s).

Whalley focuses mainly on cerebrovascular disease (especially stroke) and Alzheimer’s disease. But his prose is that of a scientist—overly passive and couched in long sentences in which the point is often easy to lose.  This book just isn’t as clear or as organized as other books in this otherwise excellent series have been.

Like a lot of education books I’ve read, this one often devolved into a codification of simple common sense. However, the approach, while not often producing detailed or specific recommendations, was interesting. As we discover more about how the brain learns, books of this sort should become more useful.

Instructional theorists have all kinds of ideas about how people learn, about how to train people, and how to present information to enable the best learning and retention. But we don’t really know how the brain works. It’s as if we tried to learn how a car works by examining working automobiles, but without ever opening up the hood to see the engine. We’d be able to learn a few things—how the steering wheel works, the functions of the brake, clutch, and gas pedals, and so on—but would we ever be able to derive the principles of the internal combustion engine this way? In order to build a car, or even tune up the performance of an existing car, we’d really want to understand how the engine works.

Fortunately, judging from the number of books on the subject in the science section at my local bookstore, brain research is a hot topic. Many books, aimed at the lay reader, attempt to summarize what is known about the mind’s engine: the human brain.

Rusiko Bourtchouladze’s book, Memories Are Made of This, is a case in point. Bourtchouladze is the Director, Model Systems Department, at Helicon Therapeutics and a visiting scientist at Cold Spring Harbor Laboratory. Her research interest is in understanding the “biological building blocks of memory,” which is actually the subtitle of her book. Memories Are Made of This is part of the “Maps of the Mind” series edited by neurologist Steven Rose. Bourtchouladze’s book is the second book that I’ve read from this series, the other being James McGaugh’s Memory and Emotion: The Making of Lasting Memories. Both books were very interesting. “Maps of the Mind” looks like a series worth investigating further.

Bourtchouladze takes us chronologically through the history of ideas and research about memory. Beginning with ancient cultures who thought writing was a bad idea because it would allow men’s memories to atrophe, she gets us quickly to Ebbinghaus’s pioneering research into the memorization of nonsense syllables, and on into her own current research into the way genes code for the biological mechanisms of memory. Throughout this journey, she focuses on the experiments, so that we learn not only what is known about memory, but how we know it.

After a review of many high-level basics that would be familiar to most instructional designers who’ve taken an introductory instructional theory class, Bourtchouladze gets to the main thrust of her book: the biological basis of memory. Here, the key neurological components are the hippocampus and the amygdala. Bourtchouladze relates the many ingenious experiments with mice that established the central role of the hippocampus in spatial learning. Similarly, she covers in some detail the experiments which show the amygdala’s  role in emotional learning.

In the final section of the book, she explains a little about her recent research into the connection between gene expression and the biological mechanisms of memory.

In any book which tries to condense extremely detailed, complex science down to a nontechnical level, there is the risk that so much detail will be lost as to make the discussion that’s left practically meaningless. That does happen on occassion in Memories Are Made of This, especially in the genetics section at the end. But by and large, Bourtchouladze does an admirable job of explaining the science without overwhelming the reader.

As instructional technologists work on the problem of learning from the top down, and neuroscientists like Bourtchouladze tackle the problem from the bottom up, we can look forward to the day when the knowledge uncovered by the two groups meets in the middle. Then we’ll have a complete end-to-end understanding of how learning happens, from presentation straight down to the neurological and neurochemical changes that the learning induces in the learner’s brain. We’ll finally know how the engine works. Then we can begin the work of turbocharging it in earnest.

My answer is, I would like to get better at responding to clients who set direction or request designs that are not in the best interest of their learners. Many clients think primarily in terms of content presentation and not in terms of generating meaningful learning activities. When clients request e-learning that is barely more than a narrated PowerPoint presentation, or have a vision for an instructor led course in which the instructor drones on for 7 or 8 hours while working her way through 500 PowerPoint slides, giving the client what he wants is not in the best interest of his learners. Yet, it can be very difficult to educate clients quickly enough to give them the necessary insight as to why what they’re asking for is suboptimal. When clients feel (rightly or wrongly) that they are “under orders” from higher management (usually not present at the meeting), the task can be very difficult. You have to somehow simultaneously educate the client and convince him that his boss will be ok with a more ambitious (and effective) design. Depending on the relationship between the client and his boss, and the culture of their organization, this may or may not be possible. When it’s not, it puts the instructional designer in a tough position. I would like to get better at avoiding that position.

In fact, I’d love to hear how you solve this problem. If you have an approach that’s working for you, please use the comment link, below, to share it.

Let’s start a conversation!

I opened my talk with a few slides on Michael Allen’s criticisms of traditional “tell and test” learning. These criticisms are primarily that content-driven courses tend to be boring, and that the meaningful tasks aren’t usually covered until the course is almost over. Then I showed how Allen suggests fixing those problems by starting the course with a challenge that asks the learner to perform the final or near-final task that the course is teaching, while providing the “tell” portions of the course as supporting materials to help the learner master this challenge. By converting the “tell” portions of the course to subordinate material, Allen’s approach gives the learner a lot more motivation to process the course content than is typical in a more traditional content-centric course. I explained that it was with these ideas in mind that I approached the challenge of creating a highly activity-centric course for the biotech client.

At the end of my talk I listed a few resources my audience could check out if they wanted to learn more about this activity-centric approach. One of the links was to a then-upcoming webinar by Michael Allen. At that point, the Senior Director of Project Management turned to me and said, jokingly, “You should get a commission!”

I tell you this so you will know my bias—I’m a huge Michael Allen fan. The three books on e-learning that he’s written so far have been, by far, the most practical and interesting such books I have read. His latest, Designing Successful E-Learning, and his first, Michael Allen’s Guide to E-Learning, are particularly great. If, like me, you’ve spent the last several years designing corporate e-learning, these books will likely change your view about what good e-learning should strive to do and how it should go about accomplishing its goals. Allen’s principles, like “Put the learner at risk” or “Don’t start at the beginning” or “Test before telling” run counter to much ingrained practice in the industry. But radical though they are, the principles he lays out are, I think, exactly what is needed to shake e-learning out of its doledrums and take it to the next level where it can be of genuine value to the learner. Read these books and you’ll never want to design e-learning the “old” way ever again. And even though his focus is on e-learning, I find the core ideas in his books translate well to the design of highly interactive classroom courses too.

Last week, I attended Allen’s webinar. Now it’s online as an archive (see: Context, Challenge, Activity, Feedback). Check it out. It’s excellent, and the demo he shows is compelling. It doesn’t depend on fancy 3D animation or first-person shooter-style immersive graphics. It’s mainly constructed out of static photos and some clever recontextualization of simple multiple-choice questions. The power is in the instructional approach, not the delivery technology per se.

If you enjoy this webinar, you might like to view the archive of Allen’s earlier webinar on Stages of Change.

Many medical institutions and practitioners now practice a form of medical care called “evidence-based medicine.” In evidence-based medicine, the folk wisdom of doctors is not considered adequate. Instead, the question of which treatments are most effective for a given pathology must be answered by reference to the best available evidence, as published in reputable scientific journals.

Although they don’t use the term “evidence-based,” Clark and Mayer are nevertheless promoting a kind of “evidence-based instructional design.” As with evidence-based medicine, there are both pros and cons to this approach. On balance, though, e-Learning and the Science of Instruction presents with clarity a good sampling of research relevant to instructional designers. Some chapters also have useful things to say to other members of typical e-learning production teams, such as creative designers in charge of look and feel decisions.

Overall, the book is a wonderful summary of relevant research on learning, complete with recommendations for how to apply the research results to practical decisions that instructional designers must make, e.g., whether to use a voice-over narrator to read verbatim on-screen text or not; whether to describe pictures or animations with on-screen text alone, with audio narration alone, or with a combination of on-screen text and audio narration; whether to address the learner directly using a 2nd person narrative point of view, or to stick to a more formal 3rd person point of view, and so on.

The difficulty, not addressed in the book, is in deciding how generalizable the research results are. (This is also a problem in evidence-based medicine.) Using research results to defend designs that are insufficiently similar to those in the actual study runs the risk of turning the science of instruction into an authoritarian quagmire. Cornell University mathematician Steven Strogatz eloquently describes this problem in The End of Insight. Strogatz worries that, in the future, science may give us answers to certain problems without giving us an understanding of why those answers are true. For problems in human learning, because our understanding of the brain is so limited, we don’t have to wait for the future—we already have studies that tell us that certain things work better than others, without deep, insightful explanations as to why. As Strogatz writes, “When the End of Insight comes, the nature of explanation in science will change forever. We’ll be stuck in an age of authoritarianism, except it’ll no longer be coming from politics or religious dogma, but from science itself.”

To avoid this problem, we need to constantly re-evaluate what we are doing. We must use the evidence from learning research as a starting point, but not follow it slavishly if it seems to be leading us to design learning that isn’t maximally effective.

That said, I think e-Learning and the Science of Instruction is an extremely valuable resource, well worth the time of anyone tasked with designing online instruction.

This year I’ve been teaching a couple of Instructional Technologies classes at my local university, and one thing I’ve noticed is that beginning instructional designers tend to think that the content presentation portions of their designs are where all the learning takes place, while the tests are neutral events that merely assess what was learned.

In this fascinating report, published in the February 15, 2008 issue of the journal Science, Karpicke and Roediger show that testing is not a neutral event. In fact, for improving long-term retrieval, testing can be even more important than studying.

They divided learners into 4 groups. Each group was given a list of 40 Swahili vocabulary words, along with their English equivalents. Then, in a series of alternating sessions, learners in each group were asked to first study the vocabulary list, and then were tested on it.

The first group, designated ST, studied all 40 words during each study session and was tested on all 40 during each test session.

In the second group, designated SnT, learners dropped words from their subsequent study sessions after they were correctly recalled during a test session. However, they continued to be tested on all 40 words at every test session.

The third group, designated STn, studied all 40 words at every study session, but were tested only on those words not yet recalled in a previous test session.

In the final group, designated SnTn, words were dropped from both study sessions and subsequent test sessions as soon as they were recalled correctly in a test session.

After 4 {study session, test session} pairs, the ST group had experienced 160 study events and 160 test events. The SnT group experienced, on average, 76.8 study events and 160 test events. The STn group experienced 160 study events and, on average, 83 test events. And the SnTn group experienced, on average, 77.4 study events and 77.4 test events.

One week later, learners in each of the 4 groups were tested on the complete list of 40 words. Which group do you think performed best on this long-term recall test?

As the authors point out, one possibility is that, after a word has been correctly recalled, a learner’s study time might be better spent focusing on learning the remaining words in the list. Alternatively, perhaps the learner will forget the word if it’s dropped from the study session. If testing is a neutral event, then dropping words from test sessions should have no important impact.

What they found was that the two groups that were consistently tested on all 40 words showed a greater than 150% improvement in long-term recall, compared to the two groups who dropped terms from test sessions.

At the same time, there was practically no difference in long-term recall between the two high-scoring groups (ST and SnT), even though the ST group underwent about 80 more study events than the SnT group. So all that extra studying led to no real gain and was essentially wasted effort.

Similarly, there was practically no difference in long-term recall between the two low-scoring groups (STn and SnTn), even though the STn group underwent about 80 additional study events compared to the SnTn group. Again, all that extra studying led to no practical gain.

The authors conclude: “Repeated retrieval practice enhanced long-term retention, whereas repeated studying produced essentially no benefit.” [p. 967]

So testing is not a neutral event.