How a large-scale digital analysis of teacher comments led to a new understanding of why some people excel, and how we can use this information to shape educational environments and close gaps in student preparation.
What are the habits and dispositions associated with success in school? What behaviors and character traits lead to growth and development? And how do these dispositions, these “non-cognitive skills,” relate to the science of learning--how do they inform, overlap with, or shape the cognitive functions of attention, encoding, storage, and retrieval?
In the end, are habits and beliefs more important than the mechanics of the mind? Or are the mechanics what drive our character?
These questions lay at the heart of a task force I led that set out to address gaps in student preparation as they entered our school. Researching these questions, however, researching character and performance, is tricky, because behaviors and character traits are not quantitative. They are qualitative; they’re descriptive. Typically, we describe our state of mind, we don't quantify it, because it's difficult to measure a state of mind. As we set out on our work, we didn’t have a rubric; we didn’t have metrics to assess character systematically, and as a result we didn’t have any ways to analyze student behaviors based on any pre-existing quantitative measures. So how could we seek to correlate character with success?
In the end, are habits and beliefs more important than the mechanics of the mind? Or are the mechanics what drive our character?
These questions lay at the heart of a task force I led that set out to address gaps in student preparation as they entered our school. Researching these questions, however, researching character and performance, is tricky, because behaviors and character traits are not quantitative. They are qualitative; they’re descriptive. Typically, we describe our state of mind, we don't quantify it, because it's difficult to measure a state of mind. As we set out on our work, we didn’t have a rubric; we didn’t have metrics to assess character systematically, and as a result we didn’t have any ways to analyze student behaviors based on any pre-existing quantitative measures. So how could we seek to correlate character with success?
In short time, we realized that we did have descriptive information embedded in the end-of-term comments that teachers write for students each trimester. Every trimester, teachers write 100-150 words about each of our students, and we discovered that our database of these comments runs back to 2003. So, we were able to research and index every comment written by every teacher for every student... for nine years.
For 600+ students taking 5+ classes per term, 3 terms per year, it turns out that teachers at Deerfield write 1.6 to 1.7 million words per year, for a total of 14 million words over nine years. This is a rich source of qualitative, descriptive data. But the vastness of this data created a new challenge for us: how could we access this information meaningfully and efficiently? Reading would take ages, even with a team. How could we manage this?
The strategy we landed on was to use word frequency lists, which count the number of times words appear in a body of text. These kinds of lists have been used to identify habits in writing and to prove authorship of certain texts. For our needs, we discovered that we could use word frequency lists to identify which words we use in our comments for different demographics of students. By identifying the words we use in comments for our stronger students (as defined by GPA) and which words we use in our comments for our weaker students, we could begin to understand what behaviors, habits and character traits we recognize and laud in our top students, and what behaviors, habits and character traits we encourage and promote in our students who struggle.
(We also ran this data through rigorous statistical analyses, which don’t make for good blog reading. Contact me if you're interested in this, and we can speak more.)
Qualities of Success
The results were fascinating:
In our weaker students, we found we wrote about three traits: consistency, sufficiency, and focus. As a faculty, we want our students to be able be consistent, to sustain good work, day in and day out. We also promote sufficiency; through repeated use of words like “enough” and “more,” we found we encourage our weaker students to engage more fully, to produce more than the bare minimum. And, in an age of distraction, we found we encourage students to focus, whether in their work habits or in their academic thinking.
In comments for our top students, we wrote about different, but similar, habits. We described their grit, their tenacity. We described their creativity. And we described their natural curiosity about their work. Our writing about our top students appears to reflect traits that contribute to these students’ success.
These were rich results, and they provided manifold opportunities for next steps; how might we, for example, create environments that promote foundational skills of consistency, sufficiency, and focus while also allowing opportunities for curiosity, creativity, and grit? And since completing research, we've been exploring this new question and developing programs to engage and encourage these skills.
Striking Parallels
But what was even more interesting was the relationship that emerged between the qualities of stronger and weaker students. It didn’t strike us at first, but after reflection, we recognized that the habits demonstrated by the strong students are natural extensions, natural amplifications, of the habits encouraged in the bottom:
- In our weaker students, we encourage focus, more careful attention, while our top students showed curiosity, which is the intrinsically-motivated direction of attention.
- We encourage sufficiency in our weaker students--being more productive, doing more than just the minimum--and the top students demonstrated creativity, with is the overflow of productivity, the creation of novelty.
- And while we encourage consistency in the weaker students, the top students demonstrated grit, which is consistency tested on a harder surface.
Looking at these traits in this way, we began to see a spectrum of habits and behaviors in which the foundational skills we aim to develop in weaker students lead directly to the qualities associated with high-performing students. This, in turn, can inform the language we use in our conversations, the habits we promote in classes, and the kinds of lessons we develop. If we keep the teaching of these dispositions in mind, then perhaps we can scaffold the kind of behaviors that lead to success.
Curiosity, Creativity, Grit... and Cognitive Science
Curiosity, Creativity, Grit... and Cognitive Science
But how does this fit with cognitive science? I share all this now, because it wasn’t until much later that I recognized that what makes these different habits and traits important (at least in the context of school) is that they reflect different cognitive stages in the learning process:
- Focus and curiosity are traits that promote the direction of attention, without which the entire learning process flounders.
- Sufficiency and creativity are traits that promote rich encoding. Through producing work, through writing, through interacting with content, through creating--through all these productive habits, we encode information richly.
- And consistency and grit are traits that promote recursive, repeated experiences diving into and through the whole cognitive cycle. When we hurl ourselves back into our work again and again, we’re focusing our attention, encoding information, letting it percolate in storage day in and day out, and retrieving it regularly. We’re using working memory and long-term memory. We’re mixing new material with old material, refocusing our attention and starting the learning cycle again and again.
This was a revelation, and it reconciled for me the growing gulf between cognitive and non-cognitive skills. Cognitive and non-cognitive skills are intimately related, each informing the other, and this recognition has provided a new lens for understanding our learning, on both the micro (daily) scale and the macro (behavioral) scale.
And the Unification of our Pedagogies...
But this was only the beginning. We had looked at (and continue to look at) the development of habits of mind as a way into academic success, and the search has yielded fruitful results.
Now, though, we are looking to see how these qualities might undergird our curriculum. How might we promote foundational behaviors and habits (consistency, sufficiency, focus) in our foundational classes, while still allowing opportunities for characteristics of excellence (curiosity, creativity, and grit) in all our classes?
~
But building curricular models around character is only one pedagogical approach to curriculum design. How do other pedagogical approaches engage the cognitive process? If a cognitive model for learning can help us understand the relationship between the many wide-ranging dispositions that our students hold--if it can even unify them into a singular framework of learning--can the same be done with pedagogical philosophies? What could we learn from this?
This, coming up in the next post.
To have future posts delivered to your inbox, choose "subscribe" from the bar on the right side of the screen.
Introduction:
- Cognitive Science: The Next Education Revolution (Part 1 of 14)
- A Cognitive Model for Educators: Attention, Encoding, Storage, Retrieval (Part 2 of 14)
- Attention: the "Holy Grail" of Learning (Part 3 of 14)
- Encoding: How to Make Memories Stick (Part 4 of 14)
- (Interlude) Long Term Memory and Working Memory (Part 5 of 14)
- Storage I: How Memory Works - Redux (Part 6 of 14)
- Storage II: Sleep and Memory (Part 7 of 14)
- Retrieval: Getting and Forgetting (Part 8 of 14)
- Cognitive Design: Essential Questions for Educators (Part 9 of 14)
- Character and Success... and the Cognitive Model (Part 10 of 14)
- Towards a Unification of Pedagogies (Part 11 of 14)
- Why Old School and New School Aren't in Conflict (Part 12 of 14)
- Technology, The Brain, and Teaching (Part 13 of 14)
Apple image from Wikimedia commons.
Comments
Post a Comment