A failure to disagree
As we saw in the last Think Tank, Nobel Prize winner Daniel Kahneman has arguably done more than anyone to popularize the study of cognitive biases. His work, brought together in the monumental but readable Thinking, Fast and Slow, has had a profound impact on academic and mainstream views of human cognition. Less well known is what he has taught us about expertise. Despite attracting less fame outside academia, Gary Klein is another influential contributor to the study of decision making. For years, the two were viewed as opponents. Their article Conditions for Intuitive Expertise: A Failure to Disagree is a masterclass in the exploration of different perspectives in what is termed “adversarial collaboration.”
As they put it, Kahneman is a representative of the Heuristics and Biases (HM) school of thought, which emphasizes our mental rules of thumb and how they lead us astray. Klein is from the Naturalistic Decision Making (NDM) school, which tells a more positive story about similar subjects. When studying expertise, HM researchers are inclined towards the study of stock market gurus and political pundits and how they fall victim to the same cognitive biases that bedevil novices. Meanwhile, the NDM camp studies firefighters and nurses and finds their expertise yielding intuitive judgements and pattern recognition that beginners can’t compete with.
Kahneman and Klein both agree on a precondition for the development of effective expert judgments: an environment which is regular enough to produce valid cues.
The language classroom meets Kahneman and Klein’s precondition. Language teaching isn’t a game of roulette, the outcome of which we have absolutely no control over. It’s not carpentry or computer programming either, where there is a complete cause and effect connection between actions and results. It’s more like gardening or poker, where we don’t have all the information and can be surprised, but what we do has a major impact on outcomes. Patterns abound in language teaching; just think about the ways that speakers of different L1s tend to struggle with different aspects of English, as outlined in Smith and Shaw’s indispensable Learner English. Such patterns aren’t always present, but they occur with some regularity.
This begs the questions: what distinguishes novices and experts? And how do we move from being one to the other?
My earliest memory of language teaching work involves me asking a middle-aged married Pakistani couple to run between mini-whiteboards, brainstorming vocabulary. The classroom in the language school in Manchester, England, could accommodate perhaps twelve students, and although I had expected eight, I only had two. I pressed on with the activity, watching with disappointment as the husband’s speed soon declined. Unsurprisingly, I didn’t see much of the couple after that class. I’m embarrassed just writing this, 11 years later. What on earth was I thinking? Why was I making them run?
One of the principles laid out in the witty, accessible Why Don’t Students Like School? by Daniel Willingham is that “cognition is fundamentally different early and late in training” (page 97). So, rather than asking what I was thinking, it might be better to ask how I was thinking.
Novice and Expert cognition
Willingham synthesizes cognitive science research into activities such as chess, physics, and, helpfully, teaching, and describes two core differences between experts and novices:
- Compared to novices, experts have more space in working memory, using large, chunked units of background knowledge.
- Experts perceive deep underlying features of a situation and therefore think in the abstract. Novices struggle with abstractions, focusing more on surface features.
I was definitely thinking like a novice that day in Manchester. I was incredibly wrapped up in my lesson plan and its stages. There was either no Plan B or, if there was, I lacked the mental capacity to switch to it. I was focused on what I would do, rather than why I was doing it, and didn’t know how to change plans when it became clear that the situation wasn’t as expected. I might not have even spotted the difference between the situation I had anticipated and the situation that presented itself.
While revisiting this is mildly mortifying, I know not to be too hard on myself. I was thinking like a novice because that’s what I was.
Between then and now
The years since that first day have been very kind to me professionally. In Manchester I taught learners of all ages, L1s, and levels, studying for a variety of purposes. I taught with textbooks and then experimented enthusiastically with forgoing textbooks and teaching unplugged. I built up a private tutoring business, teaching in learners’ homes, my own apartment and in coffee shops around the city. In those days I carried a mini-whiteboard, a scrapbook of photographs, and a die at all times. For another company, I taught week-long courses for young learners in schools around Europe (mostly Austria), ending most weeks with a student show for parents and local dignitaries. Some weeks I felt embarrassment, others pride, and sometimes a combination of both.
I then taught conversational English classes with university students in Tokyo, repeating the same lesson six times a day. The lessons would be perfected by around the third or fourth iteration, and then decline as fatigue set in. I pursued further in-service training in Buenos Aires, Argentina. In the UK and then China, I taught and later developed English for Academic Purposes (EAP) programs. Back in the UK I developed and taught Humanities modules for international students—primary research methods, international relations, critical reading skills, social sciences for postgraduates. As a manager, I observed hours of other teachers’ practice and gave feedback on what I saw.
These experiences were wonderful: they were socially enjoyable and emotionally rewarding. I suspect they were also cognitively beneficial, good conditions to develop expertise. But what kind of expertise?
Types of expertise
Willingham’s division is between novices and experts, but a further distinction is helpful. In the mid-1980s, Hatano and Inagaki, from the University of Hokkaido, outlined two types of expertise: routine and adaptive. Their paper Two Courses of Expertise states that routine experts “are outstanding in terms of speed, accuracy, and automaticity of performance” while adaptive experts have “flexibility and adaptability to new problems” (page 5).
Take my cooking as an example. The meals I’ve made have improved since subscribing to a company which sends me weekly ingredients and recipe cards. I follow the steps on the cards and almost always make an enjoyable dish. I enjoy the process and have found that, over time, I’ve become better at following the recipes; quicker at reading them and less often confused. However, I’ve been doing this for around three years now and it is notable how little I’ve learnt about cooking. I’m still unable to look in the fridge and devise a tasty meal, instead falling back on making the same old omelet that I’ve been making for years. In Hatano and Inagaki’s terminology I have routine expertise but lack adaptive expertise.
Hatano and Inagaki suggest that adaptive expertise is the result of practice plus “active experimentation,” meaning the systematic examination of variables, either through direct manipulation or close observation of variations occurring naturally. In contrast to my activities in the kitchen, looking back at my time in the classroom I see various features of my work that either implicitly or explicitly called for this approach.
The first is that my work involved repetition with variation. My earliest teaching didn’t involve much repetition of lessons, but my work in Europe, Japan, and China did. The peak was in Japan, repeating the same lesson five or six times per day. The work in Europe and China typically involved teaching the same material to at least two classes. While sometimes draining, overall repetition is beneficial for developing the automatic competence of routine expertise. Furthermore, repeating lessons with different groups introduced what Hatano and Inagaki call “built-in randomness.” ‘Variation is probably a preferable term when it comes to the world of students, but the central idea is the same: the teacher is repeating the same activities with different students, likely getting slightly different results each time, and then doesn’t have to wait long to try again with a modified approach or emphasis. The teacher gets lots of feedback and then promptly gets another opportunity for correction or further development. Because the students change but the aims of the lesson remain constant, the teacher is nudged into thinking about the underlying features of the lesson and the adjustments needed for the particular learners in the room.
The second feature of my work pushing me to actively experiment was its low-stakes nature. Hatano and Inagaki suggest that in a low-stakes environment, playful experimentation is more likely, while in a high-stakes environment a “safety-first” approach is prudent. With a few exceptions, for my early students English was just something they wanted to get better at. They generally did not study it as a formal requirement for visas, work, or study. The result of this relatively low-stakes introduction was that I knew failure was survivable and I had the freedom to experiment with my approach.
The final aspect I can identify is that in most of my work places value was assigned to understanding. The managers and colleagues who I gravitated towards took English language teaching seriously, but not solemnly. At various times there were conferences and seminar groups to attend. I also looked for opportunities to become part of a wider community of teachers by joining teaching associations and using online resources. Hatano and Inagaki argue that adaptive expertise thrives in a culture where “understanding…is emphasized as a goal” because in such a culture, people are encouraged to actively experiment. Moreover, in discussing their work with others, people try to explain success and failure, promoting them to “select, integrate and elaborate potentially relevant pieces of preconceptual knowledge, probably relying on mental experimentation” (page 8). In other words, with the encouragement of those around them, they start thinking like adaptive experts.
If, as Willingham suggests, expertise involves extracting underlying patterns from concrete situations, then there should be some useful takeaways for would-be or novice English teachers and those who train them. Here are a few:
First and simplest is to look for opportunities to teach and to watch others teach. Take on as many hours as you feel able to manage, especially in the early days. Organizing peer observation can be as simple as asking a manager or striking up a conversation with a like-minded colleague. Alternatively, there is also a world of recorded classroom teaching examples online. A good place to start is the compilation created by the teacher, trainer, writer, and blogger Sandy Millan.
A related suggestion is to seek out repetition with variation. Ask potential employers whether you’ll repeat lessons. If not, look for ways to repeat types of activities or build routines which can then be adapted lesson to lesson. Another valuable question for possible employers is how many students you’ll see. Consider the demographics of your students (e.g., L1, age, educational level, etc.) but note that you can expect diversity in almost any group. Remember though that variation comes not only from students but also from you, the teacher. You might find yourself with no choice but to actively experiment, but you can also make a point of trying new things.
A vital aspect of these suggestions is to reflect. Recall that adaptive expertise is about developing underlying, abstract, conceptual knowledge and so means developing an understanding of hows and whys not just whats. As with my cooking, simply teaching or observing lessons supports routine expertise but not adaptive expertise if there is no analysis of how and why things work or don’t. There are numerous methods and tools for reflection that lead to analysis. Willingham suggests pairing up with a colleague to video record, watch, and discuss one another’s lessons. The recording serves to provide more objective data than impressionistic human memory. A less resource-intensive approach is to keep a diary or start a discussion group with co-workers.
Another piece of advice is to join communities which value understanding. These include a school with an ethos and time and resources for Continuous Professional Developmenta peer group with colleagues, and a more formal association or membership organization. Within communities like this, by default you’ll be thinking about teaching in a sharper and more analytical way.
I started this article with an embarrassing early memory and a note of reproach for my younger, novice, self. I clearly wasn’t the right teacher for the students who I made jog around the room and I hope they found a teacher that was a better fit. For me, I have no regrets. It was only by making mistakes that I got any better at teaching. Episodes like this were shaky early steps on my journey to the one area of adaptive expertise that I feel able to claim. For novice teachers and their mentors, I believe that understanding expertise and putting this knowledge into practice can make the journey more direct, but no less rewarding.
Jamie Emerson (MA, DELTA) has taught, designed, and managed English courses since 2012 in the UK, Europe, South America, and Asia. He has written for a variety of academic and trade publications and spoken at numerous conferences. He works for Advance HE, a member-led charity for the Higher Education sector.