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Motivation Revolution?
Andrew Watson
Andrew Watson

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Here’s the magic question: how can teachers help motivate students?

After all, most of our students don’t lack the cognitive capacity to learn the material; instead, all too often, they lack the desire to do so.

Frankly, those of us who work in the classroom would LOVE some help from the world of psychology and neuroscience to understand what gets our kids energized…

Trinsic: In- or Ex-

For well over a decade, the field of Mind, Brain, Education has been guided and informed by the distinction between intrinsic and extrinsic motivation.

When I curl up with a crossword puzzle, for example, I do so for the crisp pleasure of problem solving. I don’t get anything from these puzzles, other than the joy of doing them. That’s intrinsic motivation.

Often, however, we undertake a particular activity to get something else from it. Perhaps I take a class in research methodology not because I’m fascinated by it, but because I know I need that credit to get my psychology degree. Or, I take it because my parents have made it a condition of helping with my college tuition. (Quirky parents, I know.)

In these cases, I’m driven by extrinsic motivation.

Of course, these motivations differ from person to person. I might go to an art museum because I love the works of Archibald Motley, Jr. (intrinsic), or because I want my boss to see me at the exhibit (extrinsic). You might go camping because the great outdoors refreshes your soul (intrinsic), or because a certain special someone might also be joining the group (extrinsic).

So, too, some of our students solve math problems because they are genuinely fascinated to discover the area under a curve; whereas others want to impress a classmate, or get a good grade, or earn admission to MIT.

The Whole is Greater than the Sum of the Parts?

What, then, do teachers do with this information? How does it help us to distinguish between extrinsic and intrinsic motivation?

At the very first Learning and the Brain conference I attended, Edward L. Deci offered one answer to that question. His answer is, in fact, the one you hear most often.

What happens, Deci wanted to know, when you add extrinsic and intrinsic motivation together? For example: if a student loves learning to spell new words for the pure pleasure of doing so (that’s intrinsic), what happens if I also give him a sticker for every ten new words he learns (that’s extrinsic)?

When Deci started exploring this question, no one had thought much about it. He remembers there was a vague sense that adding two kinds of motivation together should—common sense tells us—create even greater levels of motivation. But no one new how much, or precisely why.

Deci’s research, however, led to a surprising conclusion: extrinsic motivation undermines intrinsic motivation. That is: my enthusiastic speller will feel less enthusiastic once I start rewarding him. In Deci’s research, he is less likely to break out the dictionary on his own, and more likely to wait until I break out the sticker packs again.

How did Deci find this out?

In one well-known study [1], he had college students solve a particularly intriguing kind of puzzle—sort of an early Rubik’s cube. He then offered half of them a reward for solving more puzzles, while simply instructing the other half to do so. Third, he gave both groups some free time—and watched whether they continued to solve puzzles, or instead read magazines that he provided.

The result: the students who had been rewarded were less likely than the unrewarded group to continue solving puzzles.

That is: the extrinsic reward sapped intrinsic enthusiasm.

Classroom Implications

Deci’s remarkable finding provides a direct challenge to one of education’s most enduring traditions: grades.

When school folk try to justify grades as a useful incentive—they motivate our students!—Deci’s team can argue right back: yes, but at such a cost!

Even if grades do motivate (and, do they?), they undermine the love of learning that we want to instill. Students who once spent their free time obsessing about Civil War battlefields will now do so only for the promise of extra credit. What kind of motivation is that?

Deci and his frequent co-author Richard Ryan have an explanation for this effect. They argue that people are motivated by a desire for—among other things—autonomy. When you give me a grade for something that I already want to do, I feel that you’re trying to control me: that is, trying to reduce my autonomy.

In other words: your extrinsic rewards reduce my intrinsic drives by taking away my independence.

January 2017: Revolution

This account of motivation—and the tension between intrinsic and extrinsic rewards—has been common in the field of MBE for at least a decade. But in January, a new study came out which challenges this whole logical chain [2].

Two scholars at the University of Chicago—Goswami and Urminsky—ask this question: what if extrinsic motivation only seems to reduce intrinsic motivation because we’ve been measuring the wrong way? The problem is not in the motivation, but in our research paradigms?

Here’s their argument: when Deci gave those students another chance to solve puzzles, he measured their motivation immediately after they had completed the reward round. If their intrinsic motivation was only temporarily reduced, this research paradigm would have no way of capturing that result. After all, their desire to draw might bounce back. It might even come back more strongly than before.

To test this hypothesis, Goswami and Urminsky developed a new research method: one that gave participants multiple chances to demonstrate intrinsic desire to do something—before, during, and after a reward.

Participants in their study chose between solving a fun math puzzle (a problem that involved a little cognitive effort) and watching a short video (which involved no cognitive effort). In either case, this particular activity took only half a minute. They made this choice not a few times times (as in Deci’s study), but 30 times.

The first eight times, participants simply chose between solving a math problem and watching a video. Because the math problems were—in fact—fun to do, participants chose them almost 70% of the time.

During the next section of the study—ten more trials—half of the participants were given a small reward for choosing to do the math problem. (That is: an extrinsic reward was added to their obvious intrinsic interest.) Unsurprisingly, they now chose the math problems almost 90% of the time.

In the third round of the study—twelve more trials—the reward was removed. If, as Deci and Ryan predict, extrinsic rewards reduce intrinsic motivation, we would expect to see a persistent change. Participants should now prefer the video to the math problem, perhaps by a considerable margin.

What did Goswami and Urminsky find?

Round 3, Trial #4

Consistent with Deci’s study of college puzzle solvers, participants initially turned away from the math problems. Whereas 90% had chosen them during the reward round, only 50% did so during the next trial, and only 55-60% during the two trials after that.

But then, something remarkable happened.

Participants returned to the math. In fact, in trial #4 of the third round, more people chose math problems than those in the control group—who had never been offered a reward. In fact, for the remainder of the study—7 more trials—the participants who had been offered rewards chose math problems more often than the control group even though the reward was no longer available.

In other words: in this study, extrinsic motivation did not reduce intrinsic motivation. Instead, it (very slightly) increased intrinsic motivation.

To be sure of their results—and to test some other predictions as well—Goswami and Urminsky repeated versions of this study 4 more times, and consistently got the same answer.

Boom. Revolution.

Where Do We Go from Here? (Round 1)

Goswami and Urminsky’s study has quite literally just been published. Because their conclusions upend such widely known research, they will doubtless be debated, challenged, explored, perhaps contradicted.

In the meantime, what’s a teacher to do?

First: we can, I think, no longer say with such confidence that “extrinsic motivation reduces intrinsic motivation.” (Of course, it might—after all, lots of research suggests that conclusion.)

However, Goswami and Urminsky propose a new way of exploring this question, and I think we should admit the reasonableness of their critique and the usefulness of their methodology. We’ve got a chance to learn more, and we should take it.

For now, that means we should look frankly and honestly at the value of grades, prizes, and rewards. They might be beneficial, or harmful, or both; but we can’t be sure that their extrinsic motivation is harmful. (If you’d like some guidance in these discussions, you might look at Timothy Quinn’s book, On Grades and Grading.)

As a simple example: I’m married to someone whose interest in school was based ENTIRELY on grades, prizes, and competition. In at least this one case, grades provided an immensely useful extrinsic motivation that made up for a real lack of intrinsic motivation.

Where Do We Go from Here? (Round 2)

This research revolution might also inspire us to return to Deci and Ryan with fresh eyes and clearer understanding. Here’s what I mean:

In my experience, teachers who read up on this research often infer that students will naturally become intrinsically motivated to pursue schoolwork if we don’t get in their way. Because extrinsic motivation interferes with intrinsic motivation, the absence of extrinsic motivation will naturally produce intrinsic motivation.

But Deci and Ryan don’t say that [3]. In fact, they say quite the opposite: “it is critical to remember that intrinsic motivation will occur only for activities that hold intrinsic interest for an individual—those that have the appeal of novelty, challenge, or aesthetic value for that individual” (p. 59-60); as they say elsewhere, it is “catalyzed (rather than caused)” (p. 58).

Instead, Deci and Ryan accept that students simply aren’t intrinsically motivated to do many of the things that school asks them to do. It is not our job to cause them to be intrinsically motivated—because we can’t.

Instead, it is the teacher’s job to find healthy extrinsic motivators rather than unhealthy ones: “because many of the tasks that educators want their students to perform are not inherently interesting or enjoyable, knowing how to promote more active and volitional (versus passive and controlling) forms of extrinsic motivation becomes an essential strategy for successful teaching” (p. 55).

When they champion classrooms that foster autonomy, relatedness, and competence, Deci and Ryan are partly trying to allow intrinsic motivation to flourish. But, more often, they are trying to promote good kinds of extrinsic motivation—in which students recognize the value of the work that they are doing, and take it on willingly to benefit themselves and their world.

After all: I might not have taken that research methodology class with intrinsic enthusiasm, but the extrinsic motivation that got me through has been a great boon to my understanding of science.

 

  1. Deci, E. L. (1971). Effects of externally mediated rewards on intrinsic motivation. Journal of personality and Social Psychology, 18(1), 105. [link]
  2. Goswami, I., & Urminsky, O. (2017). The dynamic effect of incentives on postreward task engagement. Journal of Experimental Psychology: General, 146(1), 1. [link]
  3. Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary educational psychology, 25(1), 54-67. [link]

The Routine Advantage
Andrew Watson
Andrew Watson

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Following up on Rina Deshpande’s post looking at the benefits of cognitive routines, here’s a fun article about the upsides — and downsides — of creative changes to our daily habits.

In brief: it seems that Dave Birss broke his brain…

Ability Grouping: The Debate Continues
Andrew Watson
Andrew Watson

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A recent meta-analysis of 100 years of research (you read that right — 100 years) suggests that both ability grouping and appropriate grade acceleration benefit students.

Interestingly, the authors argue that ability grouping benefits students across the academic spectrum: “Overall, high-, medium-, and low-ability students benefited equally from ability grouping” (p. 889).

The authors of this study focus on academic benefits, and don’t look at studies that focus solely on social-emotional results. When it comes to grade acceleration, however, they do see a trend: “Numerous studies have investigated the peer dimension of acceleration and generally reported not only no harm but also small to moderate social–emotional benefits of academic acceleration” (p. 853).

For these acceleration programs, selection criteria make a real difference. At least one of the studies they review finds “socio-affective benefits for students selected on the basis of academic readiness and social and emotional maturity, but also cautions that these programs may be harmful to individual students who are arbitrarily selected on the basis of IQ” (p. 892-3).

In other words: we can’t rely solely on cognitive tests to make such placement decisions.

Given the passion surrounding this debate, I wouldn’t be surprised to see zealous push-back in upcoming weeks.

“Without data, you’re just another person with an opinion.”― W. Edwards Deming
Scott MacClintic
Scott MacClintic

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Data Informed Instruction

Early Steps

There are a few key steps to effectively incorporating MBE (Mind, Brain & Education) ideas and concepts into one’s daily teaching routine. The first key is the low hanging fruit, namely, educating oneself on the research about learning and the brain and what the research suggests are effective pedagogies. If you are reading this blog, you are probably already familiar with one fantastic resource for such information (shameless plug warning!)) – www.learningandthebrain.com

There are certainly plenty of resources out there and I strongly encourage you to seek them out. This first step is critical and has become easier in the last few years as more and more of the actual research is available online and more and more has been written for teachers as the target audience.

The second key step involves actually trying something new in your classroom, whether it is using more retrieval practice exercises [1], incorporating movement [2] or perhaps shifting to a more student-centered model for class discussions [3].

Quantum Leaps

But wait, your work is not done! Trying something new based on the conclusions of a research paper you read is certainly a big step but how will you know that the change you made was effective? What is your evidence that the change you incorporated actually improved student learning? THIS is the difficult part.

Analyzing the impact or effect of a new pedagogy is quite complex and requires the collection and analysis of data. While you may not be able to perform a double-blind controlled experiment–the gold standard in scientific research–you CAN analyze the impact of your intervention and use data to inform your teaching practice going forward.

So how do you collect data that can help you improve your  teaching practice?

I have found that one of the most useful tools for collecting data is one of the easiest to set up and use, but is frequently one of the least likely to be used by teachers – videotaping your class.

Watching a videotape of your class and objectively analyzing the tape for evidence of improved learning can be extremely enlightening, illuminating and humbling.

  • Did I really only give Hermione 2 seconds of wait time before I moved on to Draco?
  • Were the students really trying to take notes, listen to me deliver content and participate in the conversation simultaneously?
  • Did I really shake my head in disapproval as Luke responded to my question with an answer that was way off base?

I have yet to find a teacher who enjoys watching himself/herself on video but have found that most teachers who actually go through with it find the experience to be incredibly informative. Watching your video with a trusted colleague or Critical Friends group can be even more thought provoking  and lead to fruitful conversations about teaching and learning.

Data 2.0

I have been playing around with an exciting new  tool for data collection lately that has the potential to make the time consuming analysis of videotape seem like a thing of the past.  The app does a deep dive into an audio recording from class and provides me with nearly immediate data to analyze.

Here’s how it works: At the beginning of class I start an audio recording of the class on my phone and hit stop when the class is over. In the current  iteration of the app, I upload the audio file to be analyzed and within an hour or so, I receive a report back on the class. Right now, the report includes data in 5 minute increments on:

  • My talking speed (words per minute)
  • How many questions I ask
  • The types of questions I asked – How? vs Why? vs What?
  • Percentage of the time that I was talking vs. the students were talking

Questions that I have been able to think more critically about with this data include:

  • Was my student-centered class discussion really as student-centered as I thought?
  • Am I asking questions that require surface level knowledge (“what”) or ones that will lead to more critical thinking on the part of my students (“why,” “how,” “if”)?
  • Am I speaking too fast when giving instructions as I set up an activity?

The app is still in its development phase and there are bugs to be worked out before it will be available to a wider audience; but if you are interested in participating in the pilot, you can sign up here. Of all the data collection tools out there, I think that this app  has the potential to be an incredibly valuable tool for teachers as they attempt to evaluate the impact of changes in their practice.

For all of its potential uses, I do realize that their are potential dangers with the collection of this type of data. Who initiates the collection of the data? What if an evaluator or administrator wants to use the data? What are the privacy concerns about collecting this type of data? Who has access to the files and data?

All of these questions are important ones that need to be fleshed out to be certain; however, I believe that if properly used, this app has the potential to be a powerful tool for teachers who want to use data to inform their teaching as they incorporate new strategies and pedagogies.

  1. http://www.retrievalpractice.org/
  2. Donna Wilson, Move your body, grow your brain, March 12, 2014 [link
  3. Goldschmidt, M., Scharfenberg, F. J., & Bogner, F. X. (2016). Instructional efficiency of different discussion approaches in an outreach laboratory: Teacher-guided versus student-centered. The Journal of Educational Research, 109(1), 27-36. [link]

 

Interactive Teaching at Harvard
Andrew Watson
Andrew Watson

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Harvard’s Initiative for Teaching and Learning has posted videos of their most recent conference. The topic: interactivity.

As you listen to these Harvard professors, you might find yourself thinking: their students, and their teaching problems, sound a lot like my students and my teaching problems.

Pro tip: each video begins with a very generous introduction. If you skip ahead 3-5 minutes, you’ll get to the good stuff much more quickly…

It Ain’t What You Know, It’s…Oh, No, Sorry, It IS What You Know
Ian Kelleher
Ian Kelleher

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I sense that the tide is beginning to turn on the knowledge-versus-skills debate, ‘21st Century’ or otherwise. There is an increasingly confident voice shouting a phrase that teachers have shouted for the few thousands of years that there have been teachers: knowledge is really important.

Yes, even in this Googleable world, knowledge is important. We could patiently wait for the “importance of knowledge” pendulum to swing back, or we could, as evidence-informed professionals, boldly provide an epistemic nudge [1].

This post is a concise argument for the importance of knowledge, and offers some research informed ideas for teachers on how to build it.

I recently heard Robert Pondisco, senior fellow at the Thomas B. Fordham Institute, give a wonderful talk at ResearchED DC on the importance of a recommitment to teaching knowledge. During his talk, Pondisco eloquently painted the picture of President Obama during his first Inaugural Address, glancing down the length of the Mall to the Lincoln Memorial where Martin Luther King Jr. said those famous words not that long ago.

And then Obama delivered the words in this clip. It was a powerful moment in American history. And Pondisco posed the question: what knowledge would children need to have to understand the significance of these words at this moment? Would they have this knowledge? How would they have got in? Who might have it and who might not? How does this fit in the existing inequality gap? Pondisco’s questions offer a fascinating thought experiment into the importance of knowledge.

Acknowledge the limits of active working memory

Active working memory can hold fewer things for less time than most people realize. Though it is hard to measure, 7 things for 30 seconds for adults is a well agreed upon estimate [2]. For children the numbers are lower. And there is a trade off too – we can hold more things but for progressively less time.

How do these limitations fit my argument?

Having knowledge stored in long term memory frees up the active working memory to more effectively help with higher order thinking tasks. In other words, having stored knowledge helps us think.

Even project based learning needs knowledge

What about things like project based learning (PBL): the antithesis of the “lecture, lecture, test” mode of teaching? How important is it to be very purposeful in teaching knowledge when we want students to be on a voyage of independent exploration? It turns out that explicitly teaching knowledge in very deliberate ways is extremely important for PBL: make-or-break important, in fact.

I will tuck deeply into the deficiencies of PBL at a later date. But the crux of the research-supported argument is that for project based learning to have any measure of success, independent inquiry needs to be balanced with didactic instruction. Without foundational information, students lack sufficient knowledge and skills to be able to engage with the task.

In fact, failing to provide adequate support for knowledge and skills may actually contribute to the achievement gap, as students from disadvantaged backgrounds often enter school with deficiencies in knowledge and skills that are necessary for success in the project [3, 4, 5].

Part of pedagogical content knowledge, that highly interlinked combination of subject knowledge and how to teach it, is to know exactly what knowledge scaffolding students need in order to successfully launch into a project. So if we want to create great projects, which we do, we also need to be great at teaching knowledge – and great at discerning what knowledge that needs to be.

Teaching for stickiness

No matter where in the spectrum from direct-instruction-focused to project-focused we happen to be teaching, we need to get content knowledge to reliably stick in long-term memory. Fortunately there is robust research to guide us here. It suggests both things we should do and should not do.

Things Not To Do

(1) rereading notes

A trip down the aisles of Staples in August confirms what we already know – students love highlighters. But research suggests that the staple of studying, rereading notes or the textbook, is a terrible way to study. It tends to lead to what Brown, Roediger and McDaniel call “the illusion of fluency” [6], where students become so familiar with the text that they believe they know it before they actually do.

HIghlight

(2) misusing flashcards

Similarly, students tend to use flashcards in entirely the wrong way – which is hard for such a simple device. They tend to turn them over too quickly to see the answer. The key part is how one lingers in the moment of not knowing. The key part is the moment before you turn it over. Flashcards work best when students ponder difficult questions, even when the answers prove elusive.

Things To Do

(1) retrieval practice

Retrieval practice is this idea of trying to recall knowledge from memory. Even if a student is unable to, research suggests that the act of trying helps memory storage and recall. Retrieval practice can take many forms: self testing, proper use of flashcards or online tools such as Quizlet, or taking a sheet of paper and writing out everything you know on a subject.

But I am sure you can be creative and add to this list. The key is having students try deeply to recall, then  having them check this against their notes or model answers.

(2) spacing

There is great research around the spacing effect. That is, students should study, leave a gap, then study again. We can, for example, coach students to space their studying rather than use massed studying. Massed studying does not lead to durable learning.

Instead, allowing your memory to get a bit rusty between study sessions makes the next study session more challenging. In doing so, it helps create knowledge that is both more durable and more flexible. This is a concept that Clark and Bjork call “desirable difficulty” [7].

But what is the optimal spacing gap for your students, your subject, and the content you are teaching? This is a great idea for you to play with and do your own disciplined inquiry. (You might check out Scott MacClintic’s forthcoming article on gathering classroom data for suggestions.)

(3) formative assessments

Replace pop quizzes with no- or low-stakes formative assessments. As you give these quizzes, say something along the lines of, “this is for you to figure out where you are, for me to figure out where you are, and for us both to adjust what we do accordingly.” This technique is retrieval practice plus. A further benefit is that more of the brain restructuring associated with learning occurs when we struggle and when we get things wrong [8, 9]. Getting things wrong is an important part of learning, and we need to craft no- or low-stress opportunities for this to happen.

(4) interleaving

Interleaving is a way to deliberately build the spacing effect into how you design your courses. Instead of starting the year with unit one, followed, perhaps, by unit two then unit three, there is an alternative way to organize things that will promote learning. After moving on to a new unit, plan on revisiting the core knowledge at least a couple more times at spaced intervals later on [10].

(5) pre-testing

“Research suggests that starting a unit of study with a pre-test helps create more enduring learning. It appears to give students something on which to hang subsequent information. This test should, of course, not be graded, or if it is, it should be graded for effort rather than correctness.

The other point of this pre-test is to give the teacher an idea of where the level of the class generally is, and what knowledge each individual student brings with them already, so that the teacher can tailor subsequent classes to best match the needs of the class. It is important to avoid seeding boredom, and to avoid the potential skipping of foundational knowledge that could prevent future learning. These are two common toxic effects on learning” [11].

A thought on how these suggestions link to assessment

Since a little kid, I have always enjoyed words. Some are more fun to play with than others, of course, but one of the best is ‘facile.’ We often use it to refer to someone who appears so good at something they do it with an effortless ease. But its more nuanced meaning is to refer to a demonstration of thinking that at first glance seems neat, concise and elegant, but which on closer inspection is only neat, concise and elegant because it is oversimplistic, itself lacking in nuanced details.

So this article, I believe, leads us to a future one that needs to be written: how do we avoid facile demonstrations of knowledge by our students? How do we craft assessments that steer students away from this? Or, as Rob Coe and David Didau put it, where will students think hard in this lesson? But in the time before this second article is written, I encourage you to explore this idea yourself. And if you have ideas as to what should go in such an article, please let us know.

 

  1. Thank you, Troy Dahlke, for this playful term
  2. Cowan, N. (2008). What are the differences between long-term, short-term, and working memory?. Progress in Brain Research, 169, 323-338. [link]
  3. Education Endowment Foundation Analysis [link]
  4. Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75-86. [link]
  5. Kirschner, P. A., & van Merriënboer, J. J. (2013). Do learners really know best? Urban legends in education. Educational psychologist, 48(3), 169-183. [link]
  6. Brown, P. C., Roediher, H. L., & McDaniel, M. A. (2014). Make it stick: The science of successful learning. Cambridge: The Belknap Press of Harvard University Press.
  7. Clark, C. M., & Bjork, R. A. (2014). When and why introducing difficulties and errors can enhance instruction. In V. A. Benassi, C. E. Overson, & C. M. Hakala (Eds.), Applying the Science of Learning in Education: Infusing psychological science into the curriculum.  [link
  8. See this accessible research summary from Robert Bjork at UCLA
  9. Moser, J. S., Schroder, H. S., Heeter, C., Moran, T. P., & Lee, Y. H. (2011). Mind Your Errors Evidence for a Neural Mechanism Linking Growth Mind-Set to Adaptive Posterror Adjustments. Psychological Science21(2), 1484-1489. [link]
  10. Blasiman, R. N. (2016). Distributed Concept Reviews Improve Exam Performance. Teaching of Psychology44(1), 46-50. [link]
  11. Whitman, G. and Kelleher, I. (2016). Neuroteach: Brain science and the future of education. Lanham: Rowman & Littlefield.

To Ban or Not to Ban: A Usefully Provocative Answer
Andrew Watson
Andrew Watson

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For every enthusiastic voice championing the use of laptops in classrooms, we hear equally skeptical claims. College professors, in particular, have been increasingly vocal about banning distractions to ensure that students stay focused.

James M. Lang–a professor of English, who also also directs the Center for Teaching Excellence at Assumption College–pushes back against such bans.

In a striking comparison, he views problems with distracted laptop users the same way he views problems with cheating.

If lots of students are cheating on a particular assignment, Lang argues, then it’s time for us to change that assignment.

So too with laptop distractions. If lots of students are browsing FB posts, their disorientation lets us know that this current teaching method just isn’t working.

Lang’s argument implies that even if we take away the laptop, our teaching method hasn’t gotten any better.

Provocatively, this argument shifts an important responsibility from students to teachers; Lang, after all, tells us that students’ attention is as much our job as theirs.

Wisely, Lang offers specific classroom approaches to ensure that students use their laptops for good, not for ill.

Laptops in the Classroom: The Debate Continues…
Andrew Watson
Andrew Watson

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In at least this one college classroom, non-academic laptop use is inversely related to performance on the final exam.

Of course: school teachers may be able to supervise and control our students’ activities while using computers. In other words: this study is interesting to us, but shouldn’t be the final word in the debate.

[Hat tip: Daniel Willingham]

17 Ways to Fold Sheep
Andrew Watson
Andrew Watson

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Here’s a mental puzzle to start off your day:

Imagine you’ve got 17 sheep and four pens to put them in. Just for fun, you decide to put an odd number of sheep in each pen. How would you proceed?

As it turns out, this is quite a difficult problem. You might be inclined to tell me it’s impossible. The secret is…well, I won’t tell you the secret just yet. (Don’t look now, but there are some solutions down below.)

Your ability to solve this problem might depend on internal, mental characteristics. For example: more creative people typically find a solution more rapidly than less creative people.

At the same time, your ability – and, crucially, your students’ ability – might well depend on the external, physical actions used to solve the problem.

If you give your students a tablet on which they can write, draw, and erase, the chance that they’ll find a solution remains low. However, if you give them pipe-cleaner pens and little plastic sheep, the odds get a lot better.

In one study by Frédéric Vallée-Tourangeau [1], 0% of college students who used the tablet figured out the solution, whereas 43% of those who used the pipe-cleaners and sheeplets did so. (In a slightly different research paradigm, 17% of tablet users found solutions, vs. 54% of model builders who did.)

That is: manipulating meaningful objects increased the likelihood of success.

*          *          *          *          *

In recent years, researchers have increasingly focused on the topic of embodied cognition: the influence that our bodies (not just our brains) have on our thinking.

Susan Goldin-Meadow and Sian Beilock, for example, have studied the role that gestures play in cognition [2]. In one of their studies, a particular set of gestures helped some students learn math problems more effectively. (Intriguingly, students who said the wrong words but made the right gestures tended to learn more quickly than other students.)

Beilock’s recent book How the Body Knows its Mind: The Surprising Power of the Physical Environment to Influence How You Think and Feel offers a substantial introduction to this fascinating topic.

Vallée-Tourangeau’s just-published research – both the “17 Sheep” problem, and another study into mental math [3] – fits nicely under the heading of embodied cognition. After all, students who use their bodies a particular way think more effectively than students who use their bodies a different way.

*          *          *          *          *

What practical teaching advice flows from these insights?

First, we should recognize that this research is in very early stages, and specific teaching strategies haven’t yet been tested. At this point, we’re making plausible extrapolations, not relying on well-tested hypotheses. (Unless, that is, you’re teaching students how to fold sheep creatively.)

Second, this research pool encourages teachers to translate problems into objects both for step-by-step routines and for problems that require new insight.

Step-by-step routines: Vallée-Tourangeau’s mental math study shows that students who could move tiles around as they added digits in their head accomplished this task much more effectively than those who were forbidden from moving their hands.

Mental addition is – for most college students – quite a routine cognitive task. And yet, by combining bodily movement with cognitive efforts, students noticeably improved their performance.

Problems that require new insight: The solution to the “17 Sheep” problem requires a sudden AHA!, a flash of insight: the sheep pens might overlap with each other.

17 Animals

When Vallée-Tourangeau’s students thought about the “17 Sheep” problem in two dimensions, they had very little luck. When they thought about that same problem in three dimensions, however, that extra dimension prompted new – and successful – thought patterns. That is: physical objects made new insights easier to uncover.

This study suggests that we can help our students leap to surprising new ways of thinking by inviting them to move physical objects around.

Of course, the specifics of this suggestion have yet to be researched. They will doubtless depend on the subject you’re teaching, the students you’re teaching, and your own comfort with this kind of inventive extrapolation.

Despite these uncertainties, these researchers offer us exciting new approaches for teaching both basic procedures and complex insights.

Our students may well benefit from such strategies, and from our own classroom experiments.

 

  1. Vallée-Tourangeau, F., Steffensen, S. V., Vallée-Tourangeau, G., & Sirota, M. (2016). Insight with hands and things. Acta Psychologica, 170, 195-205. [Link]
  2. Goldin-Meadow, S., & Beilock, S. L. (2010). Action’s influence on thought: The case of gesture. Perspectives on Psychological Science, 5(6), 664-674. [Link]
  3. Vallée-Tourangeau, F., Sirota, M., & Vallée-Tourangeau, G. (2016). Interactivity mitigates the impact of working memory depletion on mental arithmetic performance. Cognitive Research: Principles and Implications, 1(1), 26. [Link]