An interesting article in EdWeek last month about new methods for teacher preparation caught my eye. It described an approach focused on giving teachers a specific repertoire of competencies through structured training and practice before they’re let loose on classrooms. What’s reassuring (and maybe puzzling this didn’t happen earlier) is how close this new approach to training teachers is to what research says works best for learning.
The article describes the approach as based on results from learning science (e.g., Daniel Willingham’s Why Don’t Students Like School, referred to in an earlier blog) and specific in-class competencies identified as helping students most (e.g., Doug Lemov’s Teach Like a Champion, developed in conjunction with the Uncommon Schools, which is a progenitor of the Relay School – something like half those competencies can be connected to learning science research). The typical instructional sequence presents the new capability, has the teachers-in-training practice it on each other, and then practice in a classroom. Teacher-students in the Match program gradually take on more and more teaching responsibilities, and are coached regularly by an observer who gives feedback on the techniques, following up at the next observational session. Very much focused on treating teaching as the real-time performance act/art it truly is.
This fits very well the approach we at Kaplan have extracted from the learning science literature and are applying across a wide range of topics and age ranges, from 10 year olds to 70 year olds, from entry-level work in health care to more sophisticated graduate studies. When we are working at our best, we provide essential information, then demonstrations (including worked examples), followed by intense practice and feedback. We try to structure the sequence of instruction so that key procedures and knowledge components that are best automated get extensive practice throughout the instruction – as you learn new things, you keep practicing the essential things that need to become more automated to free up room for the new things.
The underlying learning science has to do with the intertwined relationship between working memory and long-term memory when you exercise mastery. Working memory is the skinny, flexible, verbal part of our minds – it can do almost anything, but slowly, and not too many things at once. It draws deeply and effortlessly on whatever is encoded in long-term memory, which is the non-conscious, fluent, huge repository of a vast array of patterns, procedures, facts, processes, and more – it’s what we take for granted, what seems “obvious” and “easy” to a more expert mind.
An expert facing a challenge (e.g., a teacher facing a confused classroom about a complex topic) is running working memory at full capacity – and how big that “full capacity” is, is defined by what can be drawn on effortlessly from long-term memory. So, as a simpler example, a young high-schooler with stronger skills writing a paragraph is focusing working memory on paragraphs and sentences, with the individual sentences, words, and letters requiring almost no conscious attention. However, a struggling student in the same class may not have mastered composing sentences in a clear way – or even picking words, or individual issues of grammar and spelling. Such a student ends up spending much of working memory on those issues, unable to focus on the larger structural issues that the more advanced student has (working memory) capacity to focus on.
The EdWeek article describes some concerns by other educators that perhaps focusing so much on a repertoire of competencies is making teachers into mere “technicians” – that, perhaps, teachers should be left to develop their own art, their own way, using anthropology and sociology as their lodestones for what they do.
In fact, the learning science above gives the reason why there’s no need to choose. The way to enable teachers to focus working memory on effectively solving larger issues for their classes is to get them to automate competencies (while applying concepts and principles) to clear out working memory for just that kind of thinking and problem-solving. This is completely parallel to accomplished artists, musicians, dancers, athletes, managers, and more who’ve spent countless hours deliberately practicing basic decisions and tasks (and often still do that) before moving to the richer strategic improvisation and communication tasks that characterize their later expertise.
The trick (as laid out in one my favorite references, Clark and Mayer’s E-Learning and the Science of Instruction) is getting the right sequencing of the decisions and tasks into the training. You have to make sure complex tasks for a novice are broken up into “small enough” chunks (essentially defined by what you assume is embedded in long-term memory) that are given enough practice and feedback to reach mastery. The goal over time is to embed as much as possible into long-term memory, freeing up working memory for the next level of complexity and judgment. The very best students and experts do this anyway on their own - if you arrange instruction to do this with all students, many more of them can reach their goals.
This approach to building mastery – providing clear descriptions of decisions and tasks, teaching the requisite conceptual knowledge components that go into these, good demonstrations, and then plenty of practice and feedback – has plenty of evidence (see that Clark and Mayer reference) that it works for students. New teachers are learners too – we should give them as much support as we can, just as we want them to do for their students.
While it might seem odd (fill in other adjectives as desired) that it’s only now, in 2010+, that use of these decades’ old research results are even being discussed in teacher training, it’s great to see them being applied at last to K-12 teachers.
Next stop: faculty in higher education! ;-)
Comments