Around 2012ish, a new movement rode into the UK (school) educational scene. It came with the banner of "evidence-based", to counter the previous movement. I'm not writing to contend whether the movement was right or wrong, but to offer a perspective of what it may be.
My view differs to the major slogans of the movement as it took force. Let this movement be called EduCogSci. It was claimed to be a movement of objective reason, empowering teachers with the science of cognition and the evidence it produces.
Instead, I see this movement as a game (von Foerster 2003) with an invented rule set.
Like chess, there is a rule set that allows and prohibits certain activities. When presented with this rule set, people are then free to explore what is possible within it. They can discover new moves and become very proficient at playing the game over time.
EduCogSci, is similar. The claim is that its principles are objectively taken from research. Yet, nothing is objective when it involves humans. There is a subjective selection process when choosing what theories to read and apply. Yet, differently to chess, the rule set is a bunch of assumptions that are implicitly shared by people through language.
Then, when the term "evidence-based" is uttered, it often means that someone has read about a theory, or read some experimental research. And from there, made a bold hypothesis about what to do about it in their (complex) classroom, and (complex) school.
Bold hypotheses and exploration are a good thing. So is reading scholarly literature and interpreting data on learning. We must then get our ideas out there and put them to the test. But, we must also recognise that they are hypotheses, and how they play out in complex systems is yet to be seen.
The EduCogSci game, as I see it, is a loose rule set that was socially created mainly from readings of cognitive load theory, the novice-expert concept, the research on retrieval practice, and models of memory based, principally based within the information processing paradigm of classical cognitivism. Cognitive science is actually a much larger field than these ideas alone, which highlights the act of selection carried out. For example, enactive cognitive science, based on the biology of cognition, doesn't figure.
And again, this isn't to say that these ideas can't be applied to classrooms. It isn't to say that they haven't informed my practice. They have. It is to highlight that a selection takes place, no matter who you are. This post applies then, just as much to any other educational movement as it does to EduCogSci.
Everyone will have slightly different rule sets and assumptions of course. The way a shared rule set emerges as a movement is through language. In speech, posts and blogs, the looping repetitiveness of social interaction brings certain terms into common dialogue and into mind. Language and ideas are entwined. For example, EduCogSci brought with it phrases such as: "Knowledge is everything" "Knowledge=Understanding" "Memory is the residue of thought" "Shed Loads of Practice" "Knowledge begets knowledge".
From here, teachers started to explore the possible moves to take within this rule set. And over the years, people have blogged, and written books, on the proficient moves they've learnt. Just as a chess master may write about how they play their game.
What's crucial to recognise is that other games are possible. They could have totally different rule sets, or they could be variations of the EduCogSci game. When we see the variation in possible games, then we can make sense of these pedagogy games themselves. We also make better sense of the rules we've been playing by.
Let me give an example. My interpretation of the last decade of the EduCogSci game, problem-solving-before-instruction was a move that was prohibited by the rule set. No one, of course, would say "You've broken the rules", but they may comment on how your students won't learn so much. In other words, it's not possible to get to that idea when starting with the assumptions they think with.
Yet two meta-analyses suggest that in secondary education problem-solving-before-instruction was more beneficial than the reverse for conceptual knowledge (not procedural knowledge) (Chen and Kalyuga 2019; Sinha and Kapur 2021). Variation theory also predicts it (Marton 2014).
Interestingly, the area that researches this—often called productive failure—is part of cognitive science (applied to learning), but doesn't appear to have been selected as part of the EduCogSci rule set, despite the evidence in its favour.
Chen and Kalyuga are, in fact, close collaborators of Sweller and his work on cognitive load theory. They admitted in the paper their surprise at the findings, considering their understanding of cognitive load. They called it a contradiction. In other words, according to their rule set of viable moves—hypotheses made from their readings of cognitive load theory—the results weren't supposed to happen.
The key point is that as science changes, it doesn't necessarily mean that the rule sets people think with are going to change. They are two distinct things. In rule sets, subjectivity and uncertainty are the key players. Additionally, when people play by different rule sets, misunderstandings may arise. Especially when people don't realise they're discussing different games, not an objective reality.
It's the language that highlights it. When people use certain phrases it tells you more about them, than about learning itself. And you can include this post in that idea, of course. Being aware of this, I hope, could help social media discussions about education.
Scholarly reading and an understanding of educational research are absolutely what we should seek as a teaching profession. But with it comes a responsibility to have a perspective on perspectives. For example, reflecting on what it means to say a classroom activity is evidence-based.
If you want to see what teaching and learning could look like, in practice, from an enactive cogsci perspective rather than a computational perspective, then see my book, Difference Maker:
References
Chen, O., and Kalyuga, S. 2019. “Exploring factors influencing the effectiveness of explicit instruction first and problem-solving first approaches.” European Journal of Psychology Education 35: 607–624.
Foerster, H.von. 2003. Understanding Understanding: Essays on Cybernetics and Cognition. USA: Springer-Verlag.
Foerster, H.von. 2014. The Beginning of Heaven and Earth Has No Name: Seven Days with Second-Order Cybernetics. Edited by A Müller and K.H. Müller, Translated by: E Rooks and M Kasenbacher. Kindle Edition: Fordham University Press.
Marton, F. 2014. Necessary Conditions of Learning. London: Routledge.
Sinha, T., and Kapur, M. 2021. “When Problem Solving Followed by Instruction Works: Evidence for Productive Failure.” Review of Educational Research 91 (5): 761–798.