Cognitive Science Connections Part III

The third and final installment in this short series of posts connecting content from my cognitive science class to my personal learning and professional context – Tier II reading intervention for grades 3-6 in a small public elementary school.

Knowing is not enough – we must understand. A good friend asked me just the other day what was so wrong with the “memorization/regurgitation”

Answering questions on a worksheet does not necessarily translate to fluent use of numbers in other settings. Image courtesy of

method for learning. (He works in a school and prospective families were being given a tour. The staff member conducting the tour repeated this phrase multiple times when answering a parent question about the teaching philosophy at that school.) Thanks to this class, and a particularly helpful PD session in January, I have a response! Memorization does not equal understanding. The teacher leading the PD session gave math fact fluency as an example. Let’s say Jordan, a third grader, has memorized her math facts, but when presented with a story problem, she is unable to call upon that “knowledge” to solve it. Jordan isn’t really fluent with her math facts, then. A student is truly fluent, truly “knows” their facts when she can flexibly solve problems by taking apart and putting together numbers (within a good time frame, but that is a different discussion). Perkins’ (2009) number one criteria for understanding is performance – a student’s ability to think and act creatively and flexibly with knowledge they have learned (fluency).

Teachers, especially at the elementary age where content is mostly foundations of literacy, math, and thinking, can fall into the trap of memorization being good enough – especially if it helps students pass the yearly high-stakes standardized test. I sometimes find myself gliding over students’ shaky understandings just because of time crunches (I see them for 25 minutes a day). But if I keep Perkins’ teaching-by-wholes principles in mind, I can find teaching moves that will help me stay on the path of teaching for understanding. One of these moves is formative assessment – most often I will ask for a thumbs up/thumbs down/thumbs sideways to show how comfortable a students feels about their ability to apply what we’re learning on their own. This lets me decide what my next step is: more modeling, more guided practice, more practice with less assistance from me, etc.

The biggest obstacle I encounter in teaching for understanding is the fact that I have no ready way to assess if my students are applying their learning in intervention to their work in their classroom. I spend a good amount of time working with students on identifying and writing about main ideas. They may be able to talk and write about it well in group – even independently – but I can’t easily follow up with them outside of intervention. Lack of time is the key issue. In the future, I’d like to see schedules shift so teachers, paras, and specialists have regular times to talk with each other about their students’ progress.

Teach how to play the game: uncover the hidden games and learn how to learn. Learning – in school and in life – is full of “hidden games,” the processes, frames of mind, knowledge, and strategies needed for success that aren’t visible on the surface. Perkins (2009) gives the example of statistics in

Students have this chart by their side when practicing written responses to questions about texts they read.
Students have this chart by their side when practicing written responses to questions about texts they read.

baseball. School is full of hidden games. Everything from how to participate in class to how to behave in the hallway to how to get on the teacher’s good side can be considered a hidden game. In terms of academics, hidden games can be strategies to solve word problems or, for struggling readers, how to understand an author’s implications in a poem. In intervention, the hidden game I run across most frequently is “how to answer questions about what I read (written response to text).” Written response to text is one way teachers check for understanding, and it is ubiquitous on standardized tests. Students don’t necessarily know they need to provide text evidence to support their thinking, and even if the question prompts them to, they may not know how to go about it. Explicit modeling of the steps of responding to these questions, including providing sentence frames, is the best way I’ve found to uncover this particular hidden game.

The second part of learning how to play the game is learning how to learn. Professional athletes know how to learn their craft: they need to review tape, talk with coaches, and practice weaker aspects of their game. Students need similar skills when it comes to learning their craft – learning throughout life. How do we learn how to learn? Sometimes we pick it up by watching and mimicking others, think of the child at the basketball hoop practicing her free throws because she wants to play for UCONN in college. Sometimes it is taught to us explicitly. I well remember eight grade social studies where the teacher guided us through five or six different ways to take notes to prepare us for high school. In intervention,  I model how to learn from text by sharing the different ways good readers think about what they read. While Perkins (2009) says he would prefer this instruction be woven into a whole learning experience, this does not work for students in intervention. They are with me because normal classroom instruction was not enough, therefore I need to make “learning how to learn” more explicit. Yet I am now keeping in mind the end goal – to reintegrate explicit instruction into the whole game of reading, to have my students transfer their focused practice to their general classroom work.

The “extended brain” and dynamic systems theory have implications for the future of education. Human learning is not confined to the brain. The body and the environment are involved in perception and cognition (Chalmers, 2011; Chemero et al., 2007). Vygotsky and Bronfenbrenner hinted at this idea when they theorized that learning takes place in social contexts (Bronfenbrenner’s Microsystems and Mesosystems, n.d.; Onchwari et al., 2008).  The dynamic systems theory states that human learning is comprised of a multitude of variables that change and influence each other over time (Port, 2002). These variables are both in the environment – noise, light, safety – and embodied in the individual – motivation, health, even brain architecture. The dynamic systems model can also be applied to whole school systems (Abersek et al., 2012). Home life, hunger, safety, health, access to books, clothing, availability of appropriate materials at school, etc. impact learning. By extension, these variables impact performance on standardized tests. This letter was written by a group of New York Teachers of the Year in response to Gov. Cuomo’s latest education reform proposal. They eloquently point out how these variables are outside of teacher and school control, yet greatly influence how students grow and behave in school. If our law makers deign to address the foundational issues of poor performance – i.e., address certain variables in the system – we will see achievement rise. Abersek and Bregant (2012) devoted  a good amount of their article to explaining the mathematical process used to (hopefully) model dynamic systems. This means that there one day may be an equation to model how these variables impact academic performance! That would be immensely valuable (honestly, it was a bit of a headcanon for me)! Then, instead of targeting test scores and teacher evaluation, our legislators may finally be able to see what we have know all along – that one off-kilter variable in a child’s system can throw off their learning.

My first question in response to this wonderful possibility is – how soon will the model be available?! More realistically, will it be possible? The multitude of variables surrounding learning is so vast – and includes the behavior of other humans who have their own dynamic systems – can factor analysis truly whittle these down to a feasible number with which to create an equation?

Abersek, B. & Bregant, J. (2012). The architecture of a school system according to the theory of dynamical systems. Problems of Education in the 21st Century, 46, 7-14.

Bronfenbrenner’s Microsystems and Mesosystems. (n.d.). Retrieved from

Chalmers, D. (2011, June 12). Is your phone part of your mind? – TEDxSydney – David Chalmers [Video file]. Retrieved from

Chemero, A. & Silberstein, M. (2007). Defending Extended Cognition. Retrieved from

Onchwari, G., Onchwari, J.A., & Keengwe, J. (2008). Teaching the immigrant child: Application of child development theories. Early Childhood Education Journal, 36(3), 267-273.

Perkins, D. (2009). Making learning whole: How seven principles of teaching can transform education. San Francisco, CA: Jossy-Bass.

Port, R.F. (2002). They dynamical systems hypothesis in cognitive science. Encyclopedia of Cognitive Science, 1, 1027-1032.

Strauss, V. (2015, February 9). ‘You have made us the enemy. This is personal.’ – 7 N.Y. teachers of the year blast Cuomo. The Washington Post. Retrieved from


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