Reducing cognitive load in order to boost motivation

When I first started writing about cognitive load theory and the need for explicit instruction, a lot of constructivists responded to me by suggesting that I was ignoring the role of motivation. Perhaps explicit teaching is the most efficient way for students to learn but if it turns them off your subject for life then what has been achieved? Instead, we need to give them relevant and interesting challenges. Maths education expert, Dan Meyer, suggests that we need to ask students questions that induce a state of “perplexity” in order to provoke interest and promote engagement. But I doubt that being perplexed is very motivating at all.

Instead, I have the view that it is the process of getting better at something that is motivating. In an interesting study from Quebec, students in Grades 1-4 reported their level of motivation towards maths and this was matched with maths test scores. Levels of maths achievement predicted motivation in later grades but motivation did not predict later levels of achievement. By assuming that we must provide specific activities to motivate students we place the cart before the horse. We need to focus on the quality of learning instead.

In an excellent monograph available via ResearchGate (thanks to @RonMarchetto for the tip-off), Andrew Martin of the University of New South Wales draws a number of threads together to develop an overarching theory that he calls “Load Reduction Instruction” (LRI). This carefully charts the evidence in favour of avoiding cognitive overload for students at each stage of learning. Those readers who are familiar with cognitive load theory will recognise his argument that working memory is limited and easily overwhelmed and that many teaching methods don’t take proper account of this. They will also recognise the idea of learning as a change in long-term memory (see here).

However, Martin does not stop here. Levels of guidance need to be gradually reduced as students move from novices to experts. I’d argue that instruction must not be inquiry-based (or project-based or problem-based) because this kind of teaching overloads working memory early in learning but there certainly is a role for more open-ended inquiry once students have developed sufficient automaticity and fluency. For instance, we know that solving problems becomes more effective than studying worked examples for students with sufficient levels of expertise. The key principle of LRI is therefore to reduce load during initial learning.

Martin acknowledges that more work needs to be done to tease-out the precise ways in which different components of LRI – such as direct instruction or worked examples – affect motivation. However, he does present evidence that a sense of success is important and states, “novices and academically at-risk students can have difficulty in early phases of learning and this is likely to impede their sense of efficacy throughout the learning process” [reference omitted]. The kinds of strategies he suggests will be familiar to those who have read some of the process-product research of the 1960s and 1970s; pre-training (e.g. teaching the names of the parts of a motor before teaching how a motor works), segmenting (breaking tasks into small, manageable chunks), retrieval practice and modelling.

The opposite kinds of strategies come later in a learning phase and again might enhance motivation. For instance, Martin suggests the following about ‘integrating’:

“For example, punctuation is often taught in isolation from students’ editing of their own essays and assessment tasks. In such cases, an opportunity to build a sense of relevance with regards to punctuation is lost. Integration might involve students being presented with an explicit punctuation check list (e.g. capitalise the start of a sentence, end questions with a question mark etc.) that they work through after they have written an essay. Thus, there is structured and scaffolded support for punctuation built into the student’s own essay writing activity that increases the perceived relevance and personal meaning associated with the punctuation activity.

Notably, integration is the reverse of some approaches to pre-training and segmenting described above, especially with regards to the ‘isolated elements effect’ . Whether elements should be isolated or integrated depends on available working memory resources that in turn depend on levels of knowledge – further underscoring the importance of pre-training if and when needed. Notwithstanding this, as a general principle, integration of information, materials, and/or activities allows students to better appreciate important connections in learning and thus the value of the relevant information, materials, and activities for other parts of their learning.” [reference omitted]

I think that this is a useful set of ideas that add much needed nuance to the current debate around teaching methods. It is not the case that segmenting is superior or inferior to integrating. But it is also not the case that both are equally valid strategies that different teachers can draw upon as they see fit. Instead, they are both valid at different stages in a phase of learning. In a sense, this gives justification to more traditional teaching sequences that work from the parts-towards-the-whole rather than the other way around. I discuss this in my book as ‘bottom-up versus top-down’.

Martin suggests that guided discovery learning may be effective when students are more skilled and knowledgeable – which implies a place in the learning path – and he attempts to clear-up some of the confusion around the appropriate level of guidance. Guided discovery may be considered part of LRI when it sufficiently reduces cognitive load. However, “If too much of the process remains undefined and uncertain, too much of working memory must then be directed to potentially distracting and irrelevant processes that have the capacity to lead to misinterpretation, inaccurate conclusions, and inadequate skill development.”

Martin’s monograph is fascinating. I’m not sure whether I yet agree with all of it. I need to read more about some of the ideas. However, I highly recommend it if you want to read an accessible article that will make you think about the science behind different teaching methods. One of his conclusions – that we should consider LRI to be ‘student centred’ – is an important counter to those who claim the moral high-ground for more constructivist teaching approaches.

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7 Comments on “Reducing cognitive load in order to boost motivation”

  1. Greg,

    Strange that you refer neither to this blog written by me – first in Dutch and then in English (https://3starlearningexperiences.wordpress.com/2016/05/17/close-the-stable-doors-effects-of-motivation-anengagement-on-learner-achievement/) nor the fact that the statement that the definition of learning as a permanent change is actually from my/our 2006 article.

    paul

  2. Juliet Vanyai says:

    Hi Greg,
    Add a ‘be’ between ‘to’ and ‘student’ in the final sentence of the blogpost and it will have even more impact! Good read, thanks.
    Juliet

  3. […] If you are going to argue that alternatives to explicit instruction are more effective then I will disagree. Similarly, if you want to argue that they are more motivating, I will still disagree. One major component in long-term motivation is the feeling of getting better at something – explicit instruction can deliver this feeling because it is effective. […]


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