Читать книгу Small Teaching - James M. Lang - Страница 15

The use of classroom polling—whether you go high-tech with programs like Poll Everywhere or low-tech with colored index cards or even just raised hands—presents a very simple route to making prediction part of your course lectures, as Derek Bruff points out in his book Teaching with Classroom Response Systems: Creating Active Learning Environments (Bruff 2009). His chapter “A Taxonomy of Clicker Questions” points to the power of prediction to increase comprehension in addition to the benefits it should provide in boosting memory of individual facts and concepts. For example, Bruff gives an example of a math instructor at a small college who “shows his students a graphing program that allows him to vary a parameter in a function, such as the parameter ω in the function sin (ωt), and asks his students to predict what will happen to the graph of a function when he changes that parameter. After the students vote with their clickers, he demonstrates the correct answer using his graphing program” (p. 85). Students cannot answer questions like this with simple plug-and-chug–type knowledge; they have to possess a conceptual understanding of the problem to make an accurate prediction. The failure or success of their predictions enables them to re-model that conceptual understanding, which is of course the most important learning the course should induce.

Bruff also notes that classroom polling can support the opportunity for instructors to ask students for predictions behind the screen of anonymity, which can be useful in certain contexts. He provides an example of a health and wellness course at another university in which instructors want to draw attention to student perceptions of drinking on campus. The instructors first ask the students how many alcoholic drinks they consumed at their last social occasion, but then they also ask students to predict what they think the responses of their peers will look like. “The differences between the predicted votes and the actual votes,” explains Bruff, “are often surprising to students because it turns out that students are not always as risky as they think they are” (p. 86). The benefit of such a quick prediction exercise is the rich discussion that follows: “This activity can lead to a productive class-wide discussion of social perceptions of risky behavior and the role that marketing, in particular, plays in those perceptions” (p. 86). Such discussions, in other words, can encourage the students to reflect on why their predictions were incorrect—and the role that social media or beer commercials might play in driving their perceptions of their peers' consumption of alcohol. The potential screen of anonymity provided by clickers obviously can serve a useful purpose when asking students to make predictions based on their own personal behaviors. It also could prove useful anytime you feel students might not want their predictions shared publicly, either because they want something kept private or because they feel they might be embarrassed by making a wildly incorrect prediction in front of their peers (or in front of you).