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!

Continuing my reports from the contributed paper session on teaching with clickers I helped coordinate at the Joint Mathematics Meetings back in January…

“Using Prediction and Classroom Voting via Clickers to Address Students’ Overreliance on the Representativeness Heuristic,” Tami Dashley, University of Texas-El Paso [Slides]

Tami Dashley is a graduate student in math education and a student of Kien Lim, one of the organizers of the contributed paper session. She shared some of her thesis research, an investigation into the connection between classroom voting with clickers and certain misconceptions students have about probability. Her work focuses on the representativeness heuristic, which she defines as “determining the likelihood for events based on how well an outcome represents some aspect of its parent population.”

Tami gave the following example: Suppose you toss a coin six times, getting a sequence of heads (H) and tails (T). Which of the following is more likely to occur: TTHHTH or HTTHHH? Someone using the representativeness heuristic would say that TTHHTH is more likely to occur since it includes an equal amount of heads and tails, just like the coin does. The other option includes more heads than tails, so it would not seem as likely to someone using the representativeness heuristic. Actually, both of those outcomes are equally likely (each occurring with probability 1/64), so the representative heuristic is a misleading one in this example.

The issue is that the representativeness heuristic is useful in some cases, but not useful in all cases. The misconception that many students have is that it’s always useful.

How to help students stop over-relying on the representativeness heuristic? Tami has been investigating the use of prediction questions, ones that ask students to predict an outcome or probability without actually computing anything. For example, students might be asked to determine which of several outcomes is most likely to occur. Since students need not be as precise when responding to prediction questions, they have some cognitive processing power freed up to focus on concepts. Clicker questions are a natural match here, since they allow students to commit to their predictions and compare their predictions to those of their peers. Then discussion of the incorrect answer choices provides an opportunity to deal with misconceptions.

Tami conducted her research in a high school setting, using three groups of students. Her “control” group received a lesson exploring the representativeness heuristic that didn’t ask the students to predict any probabilities. A second group was asked several prediction questions but didn’t use clickers to respond to the questions. The third group used clickers to respond to prediction questions during the lesson. Tami used pre- and post-tests to determined the efficacy of these three different lessons.

Tami found that her “control” group did pretty well on the post-test compared to the two experimental groups. However, most of their success came from what she called a “learned response.” In this case, many of the students picked up on the fact that “all of the above outcomes are equally likely” is often the correct answer to questions exploring the representativeness heuristic. (These are what students might call trick questions!) When Tami looked at performance on questions where “all of the above outcomes are equally likely” was, in fact, not the correct answer, the prediction-with-voting group performed better than the control and prediction-only groups.

I was very impressed with Tami’s research design and the subtlety with which she explored student misconceptions in this teaching context. I don’t believe that Tami has published this work yet, but I look forward to reading it when she does.

Image: “Heads and Tails” by Flickr user canonsnapper, Creative Commons licensed

I’ve often said that those teaching in the social sciences have the most options for using clickers.  Both content and opinion questions are typically on-topic in a social science course, giving these instructors the ability to use clickers in just about any way imaginable.  Case in point: The video below by Russell James, who teaches in the housing and consumer economics program at the University of Georgia.

James covers a lot of ground in this video.  He shares examples of several types of clicker questions he uses, including student perspective questions (sometimes used to connect student opinions with results from national opinion polls), experiment questions (in which students participate in experiments designed to illustrate certain economic behaviors), and prediction questions (in which students predict the outcomes of research experiments from the literature).  James moves very quickly in this video, so be ready to pause it in order to read his sample questions.

James mentions other uses of clickers, too, such as taking a minute at the end of each class to ask students the kinds of rating questions that typically appear on end-of-semester course evaluations.  He says this is the “number one” use of clickers that has transformed his teaching, since it generates regular data on his teaching effectiveness.  James mentions a use I would call a monitoring question–asking students to click in when they’ve finished a particular task.  He notes that this lets him know when it’s time to move on after an activity and that the count of students who have finished displayed on-screen sends a message to students who aren’t keeping up with their peers.

James also describes a game he calls “clicker wars.”  In this game, often used to review for exams, he divides his students into groups, perhaps based on gender or class year.  Each group is then divided into teams of two or three students each, and each team is given a single clicker.  James then poses questions to his students, and each team must come to consensus on its answer.  If a team misses a question, they’re out of the game as a team, but can still help other teams in their group.  The winning team gets some kind of prize at the end of the game, and the winning group gets a prize, too, although a lesser one.  James says this gives students a lot of incentive to stay engaged in the game throughout.

James also suggests a few ways to handle students who cheat with clickers by bringing their absent friends’ clickers to class, making it appear that those friends are present.  Most of James’ suggestions I’ve mentioned here on the blog before, but he had a novel one, too.  He suggests taking a digital photo of the class as a deterrent.  If a student’s clicker says that student was present but the student isn’t in the photo, that becomes an honor code violation.  James says that telling students you’re doing this will prevent some cheating.

Thanks to Russell James for sharing his creative ideas for teaching with clickers!

A couple of weeks ago, Stephanie Chasteen posted a series of blog entries on her ScienceGeekGirl blog from an American Association of Physics Teachers (AAPT) conference.  One entry describes a session she attended that focused on interactive lecture demonstrations in physics courses.  If you’ll think back to a physics or chemistry course you’ve taken, you can probably remember a class session or two in which your instructor performed some kind of demonstration at the front of the classroom.  Research data shared at the AAPT session indicate that students learn a lot more from these demos when they do more than just watch them.  Having students interact with the demo somehow increases learning.

One way to have students interact with a lecture demo is to have them respond to a clicker question that asks them to predict the outcome of the demo.  This helps create a “time for telling” about the demo, particularly if most students predict incorrectly.  Since the students have thought about the demo and have committed to their prediction, when that prediction turns out to be incorrect, the students are ready (cognitively and affectively) to hear an explanation of the demo.

One of the presenters shared an interesting result.  Stephanie writes:

However, the learning gains don’t seem quite as high when they use clickers.  They conjecture that the clickers don’t require students do actually do ray tracing, etc., as much as when they don’t have clickers.  (My thought on that is that you shouldn’t present the clicker answer choices until they’ve done the ray tracing and other cognitive work required to arrive at an answer).

Stephanie’s suggestion would, I think, be echoed by Jennifer Imazeki, the economics instructor I blogged about recently, who takes that very approach with some of her clicker questions.

Stephanie also writes that one of the presenters at the AAPT session, David Sokoloff, is “looking for people who would like to use some of their clicker interactive lecture demonstration.”  Email him at sokoloff at uoregon dot edu if you’re interested.

Here’s another example of a slideshow that combines great visuals with a few short sentences and phrases to explain something.  The “something” in this slideshow is teaching with clickers, naturally.

This slideshow is by Sidney Eve Matrix of Queen’s University.  She does a great job of using visuals in her presentation.  My favorite image is probably the overflowing glass on slide 19.  It’s a beautiful image that works very well as a metaphor for Sidney’s point on that slide.

I attended a presentation by Daniel King, a chemistry faculty member at Drexel University, at a recent conference.  He’s been using clickers for several years in both large, introductory courses and small, upper-level courses, and I thought it might be interesting to share some of his approaches to doing so here on the blog.

Daniel shared several types of clicker questions he uses.  He uses clicker questions to assess students’ knowledge of course prerequisites at the beginning of lessons in which those prerequisites will be used.  He likes to stimulate students’ interest in topics before discussing those topics by asking clicker questions that have non-intuitive correct answers, creating “times for telling.”

Daniel also has students predict the outcome of classroom demonstrations as a way to engage them in those demonstrations.  He noted that many students don’t pay attention to demonstrations until something dramatic happens; his prediction questions engage them earlier in the process.  He also frequently uses the think-pair-share / peer instruction method, engaging students in small-group discussions about difficult questions.

As for grading clicker questions, Daniel prefers to grade on effort and not to penalize students for incorrect answers.  This is because (a) his questions are often designed to introduce students to topics and thus aren’t likely to be answered correctly by many students and (b) he doesn’t want his students to worry about their grade when responding; he wants them to be thinking about the chemistry.

The first semester he included clicker questions in his students’ grades, he counted them toward 5% of his students’ grades as a participation grade.  Students would earn these points by answering at least 75% of the clicker questions during the term.  He found, however, that a number of students who ordinarily wouldn’t attend class starting coming to class just to earn these participation points.  This was problematic because they were often disruptive (chatting among themselves instead of paying attention) and because they frequently responded to clicker questions without thinking about those questions, making it difficult for Daniel to interpret the results of his questions.

To alleviate these problems, the next semester, Daniel awarded 5 bonus points to the final exam scores of students who answered at least 75% of the clicker questions.  This reward wasn’t sufficient to motivate students to attend class if they really didn’t want to, but it did reward the effort of those students to came to class and participated regularly.

Daniel provided some insight into his decision-making process regarding when to move on after a clicker question.  He said it depends on the reasons he has for asking the question.  If the question is meant to assess students knowledge of a concept or technique they’ll need to understand in order to follow the rest of class, he’ll spend time discussing the question unless 85% or more of his students answer it correctly.  If only 50% of students answer a question correctly that he thinks they should have answered correctly had they spent some time studying, he’ll tell the 50% of students who missed it to hit the books and move on with his lesson.

Daniel shared several other aspects of his use of clickers, including his use of a couple of clicker questions early in the semester that most students answer incorrectly to teach students that the most popular answer is not necessarily the correct one.  He’s clearly thought a lot about his teaching choices when using clickers, and he did a great job of articulating his reasons for his choices during his presentation.

I just ran across an interesting interview with Linda Hancock, director of the Wellness Resource Center at Virginia Commonwealth University.  In the interview, she describes her use of clickers during sessions for incoming first-year undergraduates.  For example…

So I can take a group of 300 freshmen and say “How many people do you think smoke daily?” and they think everybody’s smoking cigarettes because smokers are always standing out front of the buildings. “How many of you are daily smokers?” It’s like seven to eight percent.

This is a great combination of a student experience question (“Are you a daily smoker?”) with a prediction question (“How many of your peers are daily smokers?”).  The student experience question alone would have some impact, but that impact is magnified by the prediction question.  This technique is also used by Resa Walch and Amanda Tapler, two Elon University health sciences instructors I interviewed for my book.

In the interview, Linda Hancock goes on to provide another example and to note that the immediacy of the data collected via clickers helps it have more impact.