This is a rather rambly account of something small I tried that worked out. I’m hoping that it might be of use/interest to other folks (or, at least, maybe some of the references will be). Oh, and it has a bit of my philosophy on class attendance. (I’m sure you were curious!) Continue reading “BYOD … or bring me your questions! It’s all good.”→
Learning styles (the idea we each have a preferred style, such as visual or auditory, and that those should be catered to for effective learning) are a myth. This shouldn’t need to be said again. Other people have said it well. (You can skip below for a list of references.)
But it’s a tenacious, popular myth. I understand how attractive the idea is … when I was a neophyte graduate student in a TA training workshop, I remember the satisfaction of completing a learning styles inventory (like this: http://www.personal.psu.edu/bxb11/LSI/LSI.htm & this: http://www.learning-styles-online.com/inventory/ & this: http://www.educationplanner.org/students/self-assessments/learning-styles.shtml & I really need to stop because this is just irritating me …) and figuring out that I was a “kinaesthetic” learner. Of course! Of course, I was a science grad student, and this made sense! We do experiments! I learn by doing! (I didn’t think about the fact that I could probably have found a rationale for being a “visual” learner …) It was an easy way for me to think about my learning! And to justify why I didn’t perform so well in some courses … those ones were not tailored to my learning style! (Woe to those poor nasal learners … )
That was back in 1994.
Now there is ample evidence that teaching towards preferred learning styles does not seem to actually help people learn. Even trying to reliably categorize people into preferred learning styles is fraught with issues. Meanwhile, many teachers/professors and students waste time and energy on this, efforts they could be directing elsewhere. (Check out the book “Make It Stick: The Science of Successful Learning” by Brown, Roediger and McDaniel for a good overview of what we DO know about teaching/learning based on recent cognitive science research.)
Sarah L. Eddy and Kelly A. Hogan (2014) recently published a paper “Getting Under the Hood: How and for Whom Does Increasing Course Structure Work?”, a nice example of the next wave of discipline-based educational research (DBER) that goes beyond asking “Does active learning work?” to explore details of how active learning interventions actually work, and differential impacts on sub-populations of students. Here, Eddy and Hogan describe their results of a study based on the work led by Scott Freeman at the University of Washington (see Freeman et al. 2011, Haak et al. 2011).
I just finished my intersession course (yay!), and am trying to catch up on some reading. Schinske and Tanner’s “Teaching More by Grading Less (or Differently)” paper, recently published in CBE-Life Sciences Education includes lots of good stuff: a brief history of grading in higher ed, purposes of grading (feedback and motivation to students; comparing students; measuring student knowledge/mastery) and ending with “strategies for change” to help instructors who want to maximize benefits of grading while reducing the pitfalls. There are many interesting points and suggestions in this paper, and hopefully it will be one of the ones we discuss in an upcoming oCUBE journal club meeting.
In the meantime … anyone else want to chat about some of the stuff discussed in the paper? <:-)
Stanger-Hall conducted a study with two large sections of an introductory biology course, taught in the same term by the same instructor (herself), with differences in the types of questions used on tests for each section. One section was tested on midterms by multiple-choice (MC) questions only, while midterms in the other section included a mixture of both MC questions and constructed-response (CR) questions (e.g., short answer, essay, fill-in-the blank), referred to as MC+SA in the article. She had a nice sample size: 282 students in the MC section, 231 in the MC+SA section. All students were introduced to Bloom’s Taxonomy of thinking skills, informed that 25-30% of exam questions would test higher-level thinking*, and provided guidance regarding study strategies and time. Although (self-reported) study time was similar across sections, students in the MC+SA section performed better on the portion of the final exam common to both groups, and reported use of more active study strategies vs. passive ones. Despite higher performance, the MC+SA students did not like the CR questions, and rated “fairness in grading” lower than those in the MC-only section. (I was particularly struck by Figure 4, illustrating this finding.)