Derek Bruff

On Friday, I was invited to give a presentation to DigitalVU, a group of web developers and other technology folks at my university. They asked me to talk about technologies useful for engaging students in a classroom or audience members at a presentation. I talked about some tools for enhancing the visual component of one’s presentations (the Presentation Zen approach, Flickr, Compfight, Prezi) as well as classroom response systems (clickers, ResponseWare, Google Moderator) useful for facilitating interactions and discussions in the classroom.  Below you’ll find my Prezi from the talk, and if you head over to the DigitalVU blog, you’ll find some relevant links.

More thoughts inspired by Clay Shirky’s new book, Cognitive Surplus: Creativity and Generosity in a Connected Age…

In Chapter 4 (“Opportunity”) Shirky describes some of the research on the Ultimatum Game. This simple game involves two players, a “proposer” and a “responder.”  The proposer is given some amount of money, say, 10 dollars. She decided how much to keep and how much to give to the responder. She proposes this arrangement to the responder, who can then either accept it (so that each player gets the money as per the proposal) or reject it, in which case no one gets any money.

You might expect the proposer to maximize her winnings from the game by offering the responder only one dollar and keeping the other nine for herself. And you might expect the responder to accept this since one dollar is still free money. However, research shows that proposers tend to be a little more generous than that, usually offering the responder four or five dollars instead of just one. And when a proposer offers only a buck or two, the responder usually rejects the deal. Variations on the game (more money, more anonymity between the proposer and the responder, and so on) show the same general trends–people are less selfish and more generous than you might think.

Why? Shirky points toward the social implications of offering someone a bad deal. With people we know and with whom we interact regularly, we’re not likely to offer them a bad deal and if they offer us a bad deal, we’re likely to refuse it as a sort of social punishment. Shirky writes, “In the Ultimatum Game, people behave as if their relationship matters, even if they are told it doesn’t, even if they are assured it doesn’t, even if they only have a single interaction with an unknown partner.” As a result, players tend to be generous and not selfish.

Moving from the experimental to the observational, Shirky describes some of the work of economist Elinor Ostrom, who has studied how groups of people manage common property, such as farmers and fishermen who have to share physical resources like rivers. In these settings, if someone acts too selfishly and uses too much of a common resource, everyone else in the group suffers. What Ostrom has found is that when groups like these are allowed to govern themselves, they tend to behave in generous ways, just like players in the Ultimatum Game. In fact, her research indicates that self-management, in some case, works better than external management through government or market interventions.

What implications do these findings have for group work in a college or university course? One reason instructors are often hesitant to assign in-class or out-of-class group is the free rider problem. What if you have a group member who doesn’t contribute to the group effort but is rewarded the same as everyone else in the group? The research Shirky describes indicates that free riders should be relative rare, that students in a self-managed small group should be on the whole more generous with each other than selfish. Why then worry about free riders? Why implement group work policies designed to punish free riders when small groups should be able to manage themselves?

Ostrum’s research gives some clues. She identifies a few key ingredients present in groups that manage themselves well.

“Mutually visible action among the participants” – Shirky doesn’t offer many details on any of these ingredients, but I can imagine that if group members are able to operate in secret (like a fisherman who takes more than his share of the fish in a river under the cover of darkness) then they can’t be held accountable for actions that hurt the group. It’s my experience that groups of students working together on projects have a pretty good sense of who’s contributing what to the group effort, so I don’t see this is a big problem. Perhaps it’s a good idea, however, to give students tools by which they can see each others’ contributions more explicitly, particularly when they’re not together face-to-face. For instance, you might have students use a wiki to gather and organize their project notes, since most wikis will track and make visible when and how users contribute.

“Credible commitment to the shared goals” – This, I think, is the kicker. What kind of shared goals does a group of students working on a project have? Might they all want to achieve a certain grade on the project? Perhaps, but if you have some students gunning for an A and one student fine with a B, that’s not really a shared goal. And getting a good grade isn’t a particularly powerful motivation, not compared to the intrinsic desires to be autonomous and competent and to connect and share. What if students all wanted to learn something in particular (some area of knowledge or a set of skills) or to accomplish something meaningful? Those might be stronger motivations, but how can an instructor encourage those kinds of goals?

Here’s one example from YouTube celebrity (and Kansas State anthropology professor) Michael Wesch: a course on digital ethnography, organized more like a research group than a class, in which students spend the first three weeks exploring the field so as to develop an overarching research question for the course. Wesch has set the course up to tap into those intrinsic motivations I just mentioned in significant ways. I suspect that his students indeed have a “credible commitment to the shared goals” that they themselves helped develop. Unfortunately, this example suffers from what I find to be typical of Michael Wesch’s teaching innovations–it’s clear that it works well in his courses but it’s not so clear how the ideas would transfer to other teaching contexts.

“Group members’ ability to punish infractions” – Shirky seems to indicate that this element isn’t as critical if the other two elements are in place. He writes, “The easiest infraction to deal with is the one that doesn’t happen, so having members internalize a sense of right and wrong when dealing with irrigation or fishing rights becomes an essential tool.” In the context of, say, shepherds sharing grazing land for their flocks, one shepherd who overgrazes can suffer penalties both social (being shunned or ridiculed by the other shepherds) and economic (being shut out from access to the shared land). The social consequences of being a free rider are enough to discourage many students from letting their groups down, but not in all cases. That’s why, perhaps, it’s advisable to set up group work so that groups can also impose “economic” punishments on free riders. Some instructors do this by having a portion of each student’s grade determined by peer evaluation, so that a free rider will get dinged by his peers in the group.

I think I’ve heard of some instructors going one step beyond this by letting groups kick out members who don’t carry their weight. This seems a better match to the “Don’t bring your flocks around here anymore!” punishment. A free rider who is kicked out of his group no longer has access to the shared resource in question–the knowledge, skills, and hard work of the group members. I can see this “nuclear solution” working, I think. A group member would really have to be dragging down the group to be kicked out, since kicking a member out leaves the remainder of the group with fewer people and thus fewer resources. Presumably, the ejected student would still be able to submit an assignment, but he wouldn’t have access to peers for assistance–he would have to complete the work all on his own. This would be a strong motivation for students to contribute in useful ways.

I was glad to read Shirky’s summary of research indicating people tend to be more generous than we think. As an optimist (if not an idealist), that warms my heart. I hope it balances some of the skepticism I sometimes see from instructors regarding group work and the threat of free riders. I’m encouraging to set up a few simple mechanisms by which student groups can manage themselves, then trust them to do so well.

What’s your experience with the free rider problem? How do you encourage your students to establish meaningful shared goals when starting group projects? What kind of tools do you give students to manage themselves?

Image: “Battling Fuel Prices” by Flickr user Brian Auer, Creative Commons licensed

Back in June (which feels so very long ago), I did a series of posts on applications to teaching from Dan Roam’s book, The Back of the Napkin. I’ve got at least one more post about Roam’s book in me, and this one deals with the differences between novices and experts.

In Chapter 5 of his book, Roam tells the story of Lila, a training manager coming into a new organization, a company selling high-end chocolate. The company had a variety of existing practices for training new and veteran employees alike, and Lila’s task was to refine those practices and scale them up as the company expanded significantly. But when Lila requested information on the company’s training practices from the existing training team, she was overwhelmed with materials–course outlines, lesson plans, calendars, org charts, test results, you name it. It was clear that her new team knew their training practices inside and out because they had an answer to all of her questions. She just couldn’t understand those answers because she lacked the big picture of the training initiatives at the chocolate company.

Enter Dan Roam, visual problem solver. He spent the day with Lila and her team, walking them through his 6W framework–who / what, how much, where, when, how, and why. (See my earlier post for a few more details on this framework.) During the course of the meeting, the big picture that Lila needed became clear through a series of drawings including bar graphs, timelines, flow charts, and doodles. Finally, Lila could see the forest for the trees, which let Lila and her team move forward.

Reading this story, I couldn’t help but imagine my calculus students sitting in Lila’s position, overwhelmed by graphs, formulas, theorems, and all the info typically packed into a calculus course. That put me in the position of Lila’s new team, since I know how to connect all those bits of calculus into a coherent whole. The challenge for me, as it was for Lila’s team, is to communicate that big picture and help my students integrate all those formulas and theorems into a well-organized mental model of differential and integral calculus.

The cognitive science literature, particularly the classic How People Learn, tells us that experts in a particular domain think differently than novices do.

• Experts organize their knowledge in ways that support both recall and understanding.
• Given that organization, experts can quickly retrieve knowledge relevant to a problem at hand.
• For the same reason, experts notice patterns that novices often don’t and can slot new information easily into their existing mental models.
• All of this allows experts to respond adaptively to new situations, transferring their knowledge and skills to new contexts with relative ease.

Here’s an example of an expert at work that illustrates these ideas:

Notice how this expert knows the big picture in her domain? And how this enables her to see patterns and solve problems that mystify the novice in this example? (Betcha didn’t think I’d work in a Devil Wears Prada clip on this blog…)

How can we help our students develop the kinds of mental models and big pictures that will help them move from novices to experts? Dan Roam would argue that visual thinking can help, and I’m inclined to agree. Here’s an example from an undergraduate course…

Last year, Ayla Pamukcu, one of the grad students in the Teaching-as-Research Fellows program I helped facilitate, noted how much the students in her Earth Materials lab struggled to identify unknown minerals. To help her students better understand the concepts involved in this task and apply that understanding more effectively, she had them create flow charts describing the steps frequently taken in the process of identifying an unknown mineral. The flowcharts started out very simple and not very helpful, but as the students refined their flowcharts over the course of several weeks, many of the student flowcharts became quite sophisticated, reflecting a big picture understanding of the ideas involved in this task that was made evident by the students’ performance on mineral identification tasks near the end of the semester. The better student flowcharts looked a lot like the flowchart that Dan Roam created for Lila and her team seen on page 93 of his book!

How might visual thinking, particularly visual tools that show the relationships between ideas, help your students see the forest for the trees in your courses?

Image: “Magic! between the trees” by Flickr user fatboyke, Creative Commons licensed

Last week I facilitated a faculty workshop titled “Assessment of Student Learning: Grading Effectively and Efficiently,” just in time for the start of classes. Below are my slides from the workshop, and if you head over to the Vanderbilt Center for Teaching blog, you can find a few thoughts from participants about the challenges of grading as well as a few strategies for grading, including the use of rubrics, light grading, multiple-choice questions, and test corrections.

Here’s the next installment in my series (parts one, two, three, and four) on Clay Shirky’s new book, Cognitive Surplus: Creativity and Generosity in a Connected Age.

In Chapter 4 (“Opportunity”), Shirky discusses the fundamental attribution error, “the desire to attribute people’s behavior to innate character rather than to local context,” in the context of the rise of file sharing via Napster in the 1990s. He notes that some people (notably the recording industry) claimed that the rampant piracy of MP3 music files was a sign that young people of that generation were less ethical than those of previous generations. Shirky notes that other people described the same behavior not as an indication of moral bankruptcy but as a sign of a new ethos of sharing and community.

Shirky writes that both of these views are examples of the fundamental attribution error, that these views assign beliefs to people to explain behavior that is actually better explained by changing opportunities. Shirky writes:

“Napster spread for three much more prosaic reasons: (1) digital data is infinitely and perfectly copyable at zero marginal cost; (2) people will share if sharing is simple enough, and we generally resist being spiteful [by not sharing] under the same conditions; and (3) Shawn Fanning [creator of Napster] designed a system to link (1) and (2) via the right incentives.”

I think this is a reasonable analysis of the rise of “file sharing” (such an innocuous euphemism) but Shirky somewhat surprisingly misses an important aspect of this topic. On the very next page after the above passage, Shirky introduces the notion of negative externalities, the negative consequences of our actions felt not by us but by others. However, Shirky doesn’t apply this idea to the file sharing / music piracy example. Sure, college kids were willing to share their MP3 files and they probably didn’t want to be “spiteful” by not sharing their music with their friends down the dorm hall, but they didn’t consider how their actions might affect other people, like the song writers and musicians involved in the creation of the music being shared through Napster. Those negative externalities (the loss of royalties that these creative people depend on for their livelihood) weren’t often considered, since we’re generally fine with sharing what we have when the cost of that sharing is born by people we don’t know personally. Living in Nashville, I do happen to know some of those people personally, so I have a different perspective on this!

The solution to “file sharing” that the recording industry applied was to sue random college kids who used Napster. While that might “unlink” reason (1) and (2) above, as Shirky writes, it doesn’t address the negative externalities involved. Since I’m higher education, I’ll suggest a different solution to the file sharing / music piracy problem: Education. That is, education about negative externalities. Instead of imputing on those who share their MP3 files some kind of immortality, why not educate them about the systems we use in the US to produce music, the people involved in those systems, and (here’s the math educator in me speaking) some basic numeracy? (Sure, that song writer or session musician might only two get cents per CD that’s sold, but when you sell 100,000 CDs, that adds up to $2000!)

I’ll go out on a limb here and say that there’s something to this idea of using education about negative externalities to foster “collective action.” For example, I don’t know many people personally who will be affected by rising sea levels as the planet warms up, but as I’ve learned about the consequences around the world of rising sea levels, I’ve been motivated to live a little greener.

Are there other aspects of higher education where these ideas shed some light? Remember that student who was almost expelled for creating a Facebook study group for his chemistry class? Is it a fundamental attribution error to assume he was less ethical than other students in the course just because he went online with his study group? The other 146 students in the online group didn’t face expulsion, after all. As Shirky writes, “Facebook lowers the cost of social coordination among its users.” Was the “cheating” that went on in this online group any different, ethically, from the “cheating” that occurred in prior years in face-to-face study groups?

Speaking of cheating, should discussions with students about plagiarism perhaps focus on educating them about the negative externalities that result from plagiarism? Not thinking about some song writer’s income is akin to not worrying about a writer’s intellectual property, I think. I’m teaching a first-year writing seminar this fall, and I’ve been tasked with teaching my students about plagiarism, so this topic is something I’m sure I’ll be thinking about a lot in the near future.

What your thoughts on these topics? Did Shirky miss the boat in his analysis of “file sharing”? Can you think of other examples where we impute character flaws to people (students) when changing opportunities better explain their behavior? And can education help people (students) change their perspectives on negative externalities?

Image: “T’ Jolly Roger, aye.” by Flickr user Nick Humphries, Creative Commons licensed

Here’s the next installment in my series (parts one, two, and three) on Clay Shirky’s new book, Cognitive Surplus: Creativity and Generosity in a Connected Age.

In Chapter 2, Shirky described the means by which people are now able to pool their cognitive surplus for the greater good. In Chapter 3, Shirky described various motivations people have for engaging in such collaborative action. In Chapter 4, Shirky moves on to discuss the opportunities that people have to do so, although Shirky doesn’t add much new to his argument in this chapter. In brief, Shirky argues that changes in opportunities allow people to act in new ways on motivations they’ve always had.

For example, Shirky points out that those in Generation X (people born between 1965 and 1982) had a reputation for being slackers in the late 1980s and early1990s. They seemed to turn into entrepreneurs in the mid 1990s, however. Did their motivations change? No, Shirky says, it was the economic climate that changed. “In a recession [such as the one that followed the 1987 market crash], taking a dead-end job and conserving costs by hanging out with friends and drinking cheap beer are perfectly sensible responses.” When the economy picked up, Gen Xers put away their Playstations and Nirvana albums and got to work, just they would have done earlier if they had been able to.

Stated slightly differently, Shirky’s argument is this: We shouldn’t make assumptions about people’s motivations based entirely on their past behavior, that we need to factor in the contexts in which that behavior was enacted. As Shirky notes, we used to memorize all our friends’ phone numbers, but that’s not because we wanted to spend those brain cells in that way. We just didn’t have cell phones with on-board memory to relieve us of that burden. Shirky provides a few other examples, and then writes:

“We did those things for decades or even centuries, but they were only as stable as the accidents that caused them. And when the accidents went away, so did the behaviors.”

This raises the same question I raised in my first post on Cognitive Surplus: Are there activities in which higher education faculty engage that seem inherently valuable that are only accidentally valuable?

Robert Talbert commented that the face-to-face lecture might just be such an activity, and it would seem that Bill Gates, New York University, and Anya Kamenetz (author of DIY U) are thinking the same thing. Might recorded lectures available online make the traditional college lecture a thing of the past, an activity that was only valuable when great lectures were hard to come by? Perhaps, but it’s not that recorded lectures haven’t been available before the last couple of years. Have you flipped through a SkyMall catalog in the last decade or so? Vendors like the Teaching Company have been making college lectures available (albeit on VHS and DVD) for years now. And educational documentaries have been a staple on PBS for a long time.

What kinds of opportunities to view recorded lectures have changed in the last few years that might produce a significant shift away from the traditional face-to-face lecture? I see two big ones–the long tail of online videos and the on-demand nature of online videos. If you want to learn about a science topic, you no longer have to be at the mercy of NOVA‘s programming schedule (what and when). You can probably find something useful online. (Start by seeing if there’s something on the topic at the Khan Academy.) Will the on-demand long tail of online videos (a shift from scarcity to abundance) make the college lecture obsolete? Perhaps, but I see a few significant roadblocks:

1. As Chris Anderson noted in The Long Tail, long tails require mechanisms for finding interesting or useful items. Search tools, recommendation engines, and referrals from friends are necessary to help people find items of value in the long tail of whatever. We’ll need to see such tools (and powerful ones) before the long tail of online lectures can displace face-to-face lectures.
2. Not only can it be challenging to find something relevant in a long tail, but it can also be difficult to evaluate its quality. When the long tail consists of artifacts of pop culture (movies, music, and so on), evaluating is relatively easy: Do you like what you hear or see? Do your friends like it? But evaluating the quality of a source of information like an online lecture requires information literacy and critical thinking skills that students might not have. Sure, online lectures from NYU are likely to be on target, but how do you go about evaluating a site like the Khan Academy?
3. Robert Talbert mentioned a few things that online lectures do better than face-to-face lectures, like letting viewers pause and rewind and watch on mobile devices at times of their choosing. But are there aspects of face-to-face lectures that are both significant (perhaps critical) and also missing from online lectures? For example, watching a 60-minute lecture online takes a fair amount of motivation for a student. Might being in the same room as a speaker provide a level of motivation that’s hard to replicate online, at least for some students? (The reliance on highly self-motivated students appears to me to be the biggest weakness in the DIY U idea, although I haven’t read Kamenetz’s book yet, so I could be wrong. However, Robert seems to be with me on this.)
4. There’s also the accreditation issue. According to TechCrunch, Bill Gates “believes that no matter how you came about your knowledge, you should get credit for it.” Until we have systems in place to give that kind of credit, the traditional college diploma will still be very important to students. And since those diplomas are handed out by college and universities, that puts a lot of power in the hands of faculty. How comfortable might a student be in skipping linear algebra class and catching a Gil Strang lecture online when Professor Strang isn’t the one handing out grades?
5. I’m a big fan of the explanatory power of a lecture provided it’s a time for telling. However, as Robert Talbert tweeted, “Bill Gates said that in five years the best LECTURES will come from the web. Not the best ‘education.’ Big diff.” There’s a lot more to learning than just hearing someone explain something really well. Students need opportunities to test and receive feedback on their understanding to refine their learning over time. Some of that testing and feedback can come through other learners, but it helps to have an expert in the mix from time to time, too.

What do you think? Do you see any of these five potential roadblocks as potentially significant? Any of them not really relevant? Should I just go and read DIY U before I post on this topic again?

Lots more on Shirky’s Chapter 4 later, including a couple of big problems I have with the chapter.

Image: “Empty” by Flickr user Shaylor, Creative Commons licensed

Syndicated from Teaching with Classroom Response Systems

Earlier this week, I gave a virtual presentation at the Muskegon Community College Math and Technology Workshop organized by Maria Andersen. The participants were all math instructors spending the week at MCC learning from Maria and others about various uses for educational technology in math instruction.

I’ve blogged often about teaching math with clickers here, but I don’t think I’ve shared slides from any of my presentations on this topic. Since Maria asked me to put my slides on Slideshare for the workshop participants, I thought I would share them here.

I recently put together a workshop on using visual thinking techniques in the classroom for a group of graduate students at my teaching center. Here’s a brief outline of the talk:

• Presenting Visually
  • Complement, don’t clutter.
  • Use metaphors.
  • Show relationships and patterns.
• Interacting Visually
  • Ask students to select images.
  • Ask students to create images.
  • Capture discussions graphically.

See the Prezi I created for the session, embedded below, for examples and links.

For more ideas on this topic, see the visual thinking guide I helped put together.

Syndicated from Teaching with Classroom Response Systems

Back in May 2010, I led a webinar on teaching with clickers as part of the CIRTLcast series for the Center for the Integration of Research, Teaching, and Learning (CIRTL), an NSF-sponsored network of six universities interested in preparing future science, engineering, and mathematics faculty. The full webinar was 60 minutes, and you can access the audio recording and my slides in the CIRTLcast archive. However, CIRTL has done a great job taking some excerpts from the session and packaging them as a 10-minute YouTube video, complete with a transcript!

In the video, you’ll hear me talk about using clickers to generate small-group and classwide discussion, create “times for telling,” encourage metacognition, facilitate peer assessment, structure class time, turn quizzes into learning experiences, and make class more fun. Clickers can be used very effectively to engage students in the learning process during class, and this short video is a nice introduction to these uses of clickers.

Thanks to CIRTL for giving me the opportunity to present this webinar and for putting together this great video!

Syndicated from Teaching with Classroom Response Systems

There’s a lively discussion happening on the POD Network listserv this week on teaching large classes. The discussion detoured into a discussion of teaching with clickers. In responding to one of these posts, Louis Schmier wrote:

“Well, Ron, clickers might get feedback and active and collaborative involvement, but learning? Technology is a tool, not a panecea. The basic problem with large class as Ron defines it, is that it violates the basic Aristotelian tenet of KNOWING those in your audience and tailoring yourself so that those in the audience get it, understand it, and retain it.”

This comment struck me as interesting, so I responded to it on the listserv. I’m including my response here on the blog (with a couple of extra links for clarity), in case those not on the listserv find it helpful.

Anton [Tolman] has responded very eloquently to Louis’ concerns about classroom response systems, but I can’t resist weighing in myself. First, there’s plenty of evidence that “active and collaborative involvement” often leads to student learning, so if clickers are indeed fostering more student engagement during class, that sets the stage for more student learning.

And as for the idea of “KNOWING those in your audience and tailoring yourself so that those in the audience get it, understand it, and retain it,” once you get past 15-20 students, it becomes very difficult to do those two things—assessing your students’ learning during class and practicing “agile teaching” by responding to what you find out about their learning on the fly–without a tool like a classroom response system. In fact, these are two teaching tasks that clickers are incredibly well-suited to support.

Imagine you have a single student in your office asking for help in your course. It’s relatively easy to “diagnose” that student and get a sense of what the student understands and doesn’t understand, then to tailor some one-on-one instruction to help the student resolve his or her misunderstandings. If you have 2-3 students in an office hour setting, you can probably do the same thing, although you’re already juggling 2-3 different “private universes” at this point, which can be challenging.

When you move to the “small” class setting, say, 8-10 students, you now have 8-10 “private universes” to try to uncover and respond to. Sure, there could be some similarities among your students in terms of their prior experiences, misunderstandings, and perspectives on course material, but you’ve still got 8-10 different students to build your learning environment in response to. Given 50 or 75 minutes and plenty of discussion, you’ve got a good shot at this, however.

Now move to a bigger class, say 15-20 students. At this point, it’s tough to have enough “air time” for all the students during class. This makes the juggling of “private universes” very challenging. Small group discussions can help (outsourcing some of this work to the students themselves), as can pre-class assignments. But during class, you’ve got quite a task if you want to be responsive to all your students’ various learning needs.

(Here you have my answer to Jeanette [McDonald]‘s question. When is large large? I would say 15-20 students. At that point the dynamics shift in very significant ways.)

Now imagine more students—30, 50, 100, or 500. The challenge of responding to that many unique “private universes” is truly daunting! You have to start making some assumptions about commonalities among those private universes. Clickers are wonderful tools for getting a sense of the validity of those assumptions! You pose a multiple-choice question where the answers are crafted to tie into what you suppose are common understandings (correct or not) and perceptions about the topic at hand, you have the students think about (and maybe discuss in small groups) the question, then you poll them and find out which of the understandings and perceptions are *really* the most common.

The resulting bar chart tells you how to spend the next 5-20 minutes of class time: responding to the student views of the topic that are most common. This “agile teaching” allows you to make the best use of limited class time by responding to as many “private universes” as you can in the time available.

Some caveats: You could miss a very common student understanding or perspective completely when you write your clicker question! The more experience you have with the topic and with students learning about the topic, the less likely this is to happen, but it’s still something to watch out for. That’s why it’s helpful to have some kind of classwide discussion about the question, giving students whose views aren’t represented in the bar chart a chance to share.

You also won’t get to the “long tail” of student views this way. What about the two students in a class of 100 who voted for option D? Will you have time to address that minority view? Maybe not during class, but perhaps after class in some fashion.

I’m also assuming here that you’re teaching a large class! The debate over whether or not classes should have 100 students is secondary to my point here. My point is that *given* a large class, a classroom response system is an excellent tool for understanding one’s students (in the aggregate) and tailoring one’s instruction to one’s students.

Lots more on these ideas (with examples from real classrooms!) in the “agile teaching” category on my blog.

The discussion on the listerv continued productively from here. It’s worth checking out.

Image: “O is for Occipital Lobe” by Flickr user illuminaut / Creative Commons licensed