For fear of not being able to understand my scribbled, hand-written notes a few months down the line, I have decided to write up my ALT-C experience on the blog again. This is my ‘processing’ method… read on, it’ll all make sense. This post is a brief summary of just a handful of the key points expressed by Eric Mazur, Professor of Physics at Harvard University, for the opening keynote at ALT-C 2012 in Manchester.
The scientific approach to teaching: Research as a basis for course design
Keynote, ALT-C 2012, 11 September 2012, Manchester, UK.
- ALT-C 2012 Crowdvine Page
- Eric Mazur’s Education Research
- YouTube of Keynote
- Eric Mazur: Academic Profile | Twitter
As you will be able to watch the Keynote back via ALT-C’s YouTube channel I’m not going to go into detail about the data examples that Mazur presented (though they are very interesting and will be worth watching or reading through via the research page linked above). To grossly simplify his presentation, Mazur provided a host of evidence to support the argument that certain types of lecturing style do not encourage learning, and having a better understanding of how your learners learn can be used to improve your teaching practices.
I’ll briefly describe Mazur’s key points first, then summarise my take below.
Some of the key points
- The brain activity in lectures is equivalent to that of watching TV. Infact, both watching a TV and sitting in a lecture involve less brain activity than being asleep.
- A scientific approach to understanding how learners learn can improve our teaching methods (not reliant upon anecdotal data). Drawing upon the infamous quote “the plural of anecdote is not data” to suggest that student comments on feedback forms (commonly only completed by those that have either a negative view or very strong positive view) or the perceptions of lectures are not enough to understand whether a learning intervention actually makes a difference. (I’m afraid I couldn’t verify the original source, and indeed Google seems to suggest a number of people saying this including Brinner, Kotsonis and Wolfinger; Mazur cites Lee Shulman.) Essentially, we should be finding out about our students, not just through evaluation forms but analysing performance and their experience of learning.
- Confused students are good students. As examples of a scientific approach, Mazur asked his students to rate how ‘confused’ they were by the course content. He plotted that actually, the more a student admitted they were confused (and hence questioning), the more likely they were to achieve the correct answer in an exam. As such, we should be encouraging our students to address their concerns and welcome confusion to help them more fully understand. Those students who say they have no worries, are more likely to be hiding a lack of deeper understanding.
- Pay attention to incorrect answers from students. The evidence for the above comes from analysis of students exam responses. Mazur encourages time to be spent trying to work out the method behind students incorrect responses, to highlight potential misconceptions and how they may have arisen. Rather than simply writing ‘No!’ in big red letters next to incorrect work and moving on, spending the time to find out where things went wrong can feed into a redesign of delivery of content or activities to tackle common (or not so common) forms of error.
- Demonstrations alone in lectures does not necessarily improve learning. Mazur researched the learning impact of practiacl demonstrations in lectures (Physics lecturers get to do live demos). Whilst demonstrating and asking students questions or involving them in a small group activity to discuss the demo proved beneficial, simply demonstrating did not. This, Mazur explains, is due to cognitive dissonance. If you have a preconceived idea about how a physical effect is going to pan out, and you see a demo which proves the contrary, you are more likely to remember the demonstration incorrectly – creating a memory to fit your preconceptions, rather than remember the facts presented before your eyes. His analysis of students incorrect responses worryingly showed this, in that students remembered seeing something they didn’t.
- Students need time to process new information soon after receiving it. This follows on from Mazur’s observations about demonstrations. He describes that traditional lectures “hold the mind captive” with “no time to let the mind wander… and make necessary connections.” This very much comes from the angle that learning and understanding is a process of making new connections in our minds. If a lecture continuously presents for an hour, there is little time for these connections to be formed before the new information is lost or remembered incorrectly. Thus, Mazur includes ample time away from knowledge transfer with facilitated discussion and small group activities.
I enjoyed Mazur’s keynote, simply because he talked about much of what I would consider to be a good teacher. Whilst there is always a certain irony about a keynote presentation that argues against the traditional ‘talk at the audience’ lecture model, I do enjoy the debate. Anyone who hasn’t watched Donald Clark’s tirade on the lecture course model should spend their next free lunch hour watching it. Mazur’s keynote was a lot more evidence-based, just as critical, but with some actual tips on how to improve if you are stuck with the lecture room model for your courses.
Teaching isn’t about content delivery, it’s not about showing your expertise, but it’s about understanding your learners and in doing so enable them to understand new ideas. The focus was on lecture-based courses, but is equally transferable to the world of elearning where instead of lectures, much is (sadly) simply a transfer of knowledge via text or encouraging clicking on next buttons, and the design is to funnel information into the brains of those staring at the computer screen. This is the online equivalent to the sage on the stage, who is motivated to ‘teach’ by sharing his expertise. What could be said of the ‘best’ teachers is that they put their egos to one side, letting the students come to their own conclusion rather than forcing one upon them.
Providing opportunities for questions from confused students, challenging students preconceptions, showing method for answers rather than just the final result, and designs which encourage processing of new information, are all achievable if we are willing to accept that elearning does require as much facilitation as its campus-based counterpart. Whether this be simple, tried-and tested discussion-based learning, or more adventurous and complex serious game-based learning, elearning holds the potential to avoid falling into the lecture-hall trap that face-to-face teaching can sometimes become ensnared in.