Making sense of cognitive science and education

Several years ago, I created this graphic, to help me think about and teach the essential stages of the learning process. I was quite amazed by the response to it, and it reassured me that others in the profession "see it" too. I kept adapting it and thinking with it, and I want to use it here to illustrate how it can further support thinking about the current relationships between the sciences of learning and education.

It shows four conceptual stages of learning, using a simplified "network model" that represents how knowledge is represented in long-term memory, and how working memory resources are utilized. Underneath is a list of suggested guiding principles for strategy choice. (find out more about the model here).

Now, here is a question: if the "cognitive science for educators" is a field of knowledge, where are we on the sequence of learning it? If you look at the "big idea" of every stage in this graphic (labeled underneath in color) that represents the main goal or even the essence of the stage, then where are we? Building blocks - do we know what are the most relevant pieces of evidence? Organization - do we know where each piece belongs? how it is supposed to be applied in practice? what are some good examples of implementation? Function - Can we use it systematically? (let's leave Robustness out for now).

I think we have many of the building blocks, and we (as a community) have explained and demonstrated how many of them work in practice, and also how to put them together and organize them into sequences (some examples below**). So while for isolated evidence-informed strategies we have gone a long way, when we look at the entire field, we are gradually transitioning from organization to function.

In the realm of learning, "making meaning", as I see it, is composed of two essential stages, organizing new concepts and connecting them to existing ones, and then investing effort in making them useful (more about it here). An important point is that in general, as humans, and as teachers more specifically, we love doing the first part, and sometimes overlook the second.

This is why it's remarkable, to be in exactly this transitional stage when it comes to making sense of the science of learning.

So the goal here is to extend the model of learning, which may make sense (=organizing), into a framework that will serve as a basis for evaluation and planning (=function). To do that it's important to realize that the cognitive process cannot be stripped from the additional learning-related processes in which it is embedded, like motivation, meta-cognition, and importantly, habit formation. From the cognitive sciences, we learn, over and over again, that effective strategies, those that benefit learners in the long term (and see above), are also inherently more challenging and less rewarding¹ (aka Desirable difficulties). Hence, when planning for the ultimate cognitive goals (like self-directed learning, critical thinking, and creativity), we have to scaffold not only the cognitive process but also those that intimately support and interact with it.

Importantly, those elements of learning also stand on the shoulders of giant researchers, and there is evidence that suggests factors that are essential in learning. Some of these factors are highlighted in the neighbouring image (resources are listed below).

One thing to notice is the timeline: the cognitive sequence depicts a sequence that goes from novice to increasingly advanced, and the suggested guiding principles advance accordingly (see image 1). The same is true for the other processes: motivation calls for closer attention at the initial stages, when purpose and value may not be clear yet. Metacognition is relevant when learners are experiencing challenges on one hand and are ready to reflect on their own thinking on the other (that is, not too early). Last, habits, become more important when learners are ready to enter some kind of practice routine, gradually replacing conscious monitoring with implicit more automatic actions.

Now, if we want to make these ideas functional, let's turn this map into a table, as the image depicts. It has the four learning stages as rows, dictating the sequence, and four columns for strategies that are based on evidence from the behavioral, cognitive, and social sciences. Next, we can list the different guiding principles, on the basis of resources that we trust. I tried to do it here - and you are welcome to interact. From the full table, we can choose and adjust the guiding principles to specific teaching and learning contexts and goals. It is important to make sure we are not skipping any cognitive stage and that we support learning with the most relevant principles. This can help us make informed decisions about when and how to invest our limited resources.

Here is one example of a teaching sequence, that can repeat itself and develop in a foreign language learning class. Note that a goal is clearly stated in the empty row at the top, that is, before we begin. Another thing to note is how the principles in different columns combine into the same teaching/learning technique (e.g. we use stories for better organization and meaning-making, and choose relevant everyday stories so they support motivation, etc.). It's probably the case that all teaching techniques include more than one purpose, and I hope this table helps us evaluate and plan purposefully.

Sims, S., Fletcher-Wood, H., O'Mara-Eves, A., Cottingham, S., Stansfield, C., Van Herwegen, J., & Anders, J. (2021). What Are the Characteristics of Effective Teacher Professional Development? A Systematic Review and Meta-Analysis. Education Endowment Foundation. & The EEF Guidance report

There were several attempts in the "cognitive science and education" field to organize ideas into functional and useful frameworks**, and in fact, I think that this is a sign of how mature the field has become (and where it still has to go). I wish to especially mention two recent publications: The first is the highly impressive Sims et al., (2021) meta-analysis of effective professional development programs². They present a pioneering, game-changing approach to the evaluation of CPD programs. It is based on evidence from the cognitive and behavioral sciences, rather than broader factors from educational research (that were not proven to be useful enough³). They suggest 22 mechanisms and classify them into 4 sequential categories that represent the learning process. Importantly, their assumption and suggestion is that a balanced CPD, which includes at least one mechanism from every category has a better chance to be effective (in a way that will be measurable by students' achievements). While I wholeheartedly recommend reading the review and recommendations, I wish to draw special attention to the categories they suggest (see image) and to the fact they span the entire learning process from acquiring knowledge to embedding a professional skill in a classroom environment.

McDaniel, M. A., & Einstein, G. O. (2020). Training learning strategies to promote self-regulation and transfer: The knowledge, belief, commitment, and planning framework. Perspectives on Psychological Science, 15(6), 1363-1381.

The other work by McDaniel (co-author of 'Make it Stick') and Einstein (2020) focuses on undergraduates' ability to apply effective practice strategies⁴. Following their experience of teaching the undergrads about effective strategies (like retrieval and distributed practice), and realizing that they are not applying them independently, they have suggested a four stages framework to support students in their pathways from learning about the strategies to applying them in their own learning. Here too, they are supporting their suggestion with evidence from the sciences of learning and behavior.

What is in common?

The two approaches, although different in some ways have a few important things in common:

1. They don't suggest new strategies but focus on organizing the evidence into a coherent, functional, and testable framework.

2. They are organized around sequential stages of learning, starting with knowledge and going all the way into planning and/or embedding routines of practice.

3. They include elements of cognition, motivation, meta-cognition, and habit formation, based on relevant research findings in these fields.

4. They suggest a framework that can be tested.

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