Small Teaching. James M. Lang

Small Teaching - James M. Lang


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finds herself scratching her head and unable to come up with the answers, she will immediately see that she has to approach this course, and her learning, in a new way. She has to focus on conceptual understanding instead of the memorization of facts. If she hadn't encountered that first-day predictive activity, she might have spent the first five weeks of the semester, before the first major exam, focused entirely on repeating her high school study practices.

      Ultimately and perhaps most simply, predictive activities mimic something we normally ask of learners who are attempting to master a skill: requiring them to try before they are ready. We can all likely draw from our experiences with attempts to master skills of one sort or another, and we know full well that however much one might read in advance about throwing a football or painting a portrait or giving a speech, the real learning happens after we have thrown ourselves into the situation and made that first (unsuccessful) attempt. When I took a class to become licensed in scuba diving, we spent the first half of every session in a classroom taking notes on some skill we would have to practice in the pool. I typically jumped in the pool for the second half of class thinking I had that skill mastered, but within a few minutes the gaps in my knowledge were revealed, and I floundered around for a while, doing it completely wrong until the instructor swam over and gave me the help I needed, at which point the real learning began.

      The ideal grounds for small teaching activities related to prediction are the openings of a learning experience—a course, a learning unit, a class period. Consider the following models for leveraging predicting into the beginning of anything you might be teaching.

       Activating Prior Knowledge

      Our first small teaching strategy might therefore be the easiest one to implement in the book: before you teach something new to your students, ask them what they already know about it. You could do this in multiple ways that fit the frame of small teaching:

       Prior to introducing new content in a course, ask students to take a pre-quiz or respond to two or three questions about the subject matter on the course's learning management system and then summarize those results briefly at the start of the first or second class.

       At the start of any individual class period, ask students to write down what they think they already know about the subject for that day. Tell them to list three to five things they have learned in previous classes or from their life experiences, and have them pair up to compare notes. Solicit a few responses and build on them in the opening of your presentation of the new material.

       At the start of the semester, devote part of one class period to assessing students' current state of knowledge, either through whole-class or group activities or through a written pretest. Once you have heard what students have to offer in such an exercise and have gained a glimpse into their existing knowledge, you can strategize how to build upon it most effectively in the course.

       Polling Predictions

      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.


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