Taking account of context

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In many subject areas, a learning objective can be distinguished from the context in which it is learnt. For instance, if I want to teach students how to start a sentence with a prepositional phrase, I have an almost infinite set of contexts to select from. Students could be engaged in writing a letter to their local political representative, analysing a text, constructing a narrative etc.

Maths and English teachers will be familiar with calls to teach their subject through real-world or authentic contexts. There is a popular view that many of the contexts we conventionally use are somehow fake or artificial and if we focused on students’ everyday experience then they would be more motivated to learn. There are a number of difficulties with such an idea. Firstly, real-world contexts tend to be highly complex and therefore not ideal for learning the first principles of a subject. Secondly, the concepts of real-world and authentic start to dissolve under examination. The late Grant Wiggins devoted some effort to attempting to differentiate authentic from real-world and defining the former.

When it comes to the idea of real-world contexts being motivating, I usually point to an example from David Perkin’s book, Future Wise, where he suggest students could plan, ‘for their town’s future water needs or model its traffic flow.’ This doesn’t sound motivating at all. It sounds really dull.

But real-world versus fake (or authentic versus inauthentic) are not the only axes along which contexts may differ. So, I still think it is worth thinking carefully about the contexts we select. For instance, when we first teach a complex academic idea, we should probably keep the context as familiar to students as possible. That’s not the same as claiming it should be real-world or authentic because it is quite possible to be familiar with a fairy story or with set theory. Familiarity is not a property of the context alone, it is defined by an interaction between the context and the student.

The reason for seeking a familiar context is to minimise cognitive load. This is only going to be useful when the complexity of the new academic idea threatens to overwhelm working memory. It’s not going to be as essential for learning lists of names or labels. By using a familiar context, we minimise the load generated by the context, freeing-up load for the new idea. This also suggests a way forward. If students have mastered prepositional phrases in the context of writing responses to The Wind in the Willows then we are not done with prepositional phrases. Off we go to a new context.

This last point hints at the essentially arbitrary nature of what constitutes a context. For example, if students have mastered prepositional sentence starters, then a teacher could potentially ask students to write sentences of this kind as part of a sequence where they are intended to learn the causes of the first world war. In this case, the prepositional phrases effectively act in the same way as a familiar context and the causes of the first world war are the new idea to be learnt. This may sound like an odd teaching approach but similar methods are deployed in writing programmes such as The Writing Revolution. By mastering the sentence expansion routine, ‘because, but, so,’ students can then use it as an aid to learning new content.

Varying the contexts is an important step in learning a new concept because we know that learning can become locked to a specific context. Students are not clear where the idea ends and the context starts. The context represents the ‘surface structure’ and the idea represents the ‘deep structure’. So, moving from context to context helps students tell the difference because it places the edges of the concept in relief. Craig Barton has developed a maths site that tackles this problem the other way around; cycling students through problems involving the same surface structure but different deep structure.

A recent paper by Florence Lespiau and Andre Tricot explores another way in which contexts may differ. They draw upon the distinction made by David Geary between biologically primary and biologically secondary knowledge. Briefly, the former is the kind of knowledge we have evolved to acquire, such as how to speak, and the latter is the kind that has arrived relatively recently in human history; things like learning how to read and write or solve abstract maths problems. We can broadly identify biologically secondary knowledge with the academic content of school curricula – in a sense, schools were invented to impart this knowledge.

Lespiau and Tricot asked volunteers (126 university students in one study and 101 high school students in the second study) to solve logic problems. These follow familiar patterns of deduction such as:

All hipsters have beards.

Jay has a beard.

Is Jay a hipster?

Lespiau and Tricot did not teach participants how to solve the problems so this was not a study of learning, it was a study of performance only. Lespiau and Tricot suggest that logic problems are biologically secondary because humans don’t naturally reason using logic (or ‘system 2’ thinking), instead we tend to make use of various heuristics (‘system 1’ thinking).

They then manipulated the context so that it either involved a biologically primary context or a biologically secondary context. Yet in both cases, the actual content was new to the students. So, for instance, one biologically primary context was dealing with food. Participants were presented with the following logic problem:

‘In a community in Jamaica, if an ugli is picked up red, then it is peeled entirely to be eaten.

In a community in Jamaica, an ugli is picked up red. Is this ugli peeled entirely to be eaten?’

Note that the participants did not have previous knowledge about uglis.

Participants also had to answer similar logic problems about grammar rules that they did not know; a biologically secondary context. For instance, a grammar rule might be, ‘In Quenya, if a strong verb is conjugated to the perfect, then this strong verb ends with -ie’. The authors also manipulated cognitive load by writing some of the problems backwards or asking participants to memorise arrangements of dots.

Despite knowing equally little about the specifics of either context, the participants tended to perform better in the food based contexts. They also found them more motivating. This suggests that biologically primary domains are privileged. Perhaps we have mental modules that are primed for learning biologically primary material. if so, biologically primary content would not load working memory in the same way as biologically secondary content, making for a more pleasant experience and allowing participants to focus on the underlying logic. As part of the study, Lespiau and Tricot asked participants to self-report their cognitive load and, as might be predicted, found it to be lower in the food-based problems.

This may be worth thinking about when designing contexts for learning challenging academic concepts and it adds further weight to the biologically primary versus biologically secondary distinction.


4 thoughts on “Taking account of context

  1. Hi Greg,
    Very interesting problem site.

    Does the categorization into primary verses secondary become defined by those things which we learn easily are primary? I see a danger in circular reasoning otherwise. But with that definition in becomes an interesting area of study – which contexts provide low cognitive load and an easier learning path?

  2. You always write about interesting things. Thanks!
    I had a question about your use of terminology re: cognitive load. You wrote “minimise the load generated by the context, freeing-up load for the new idea”. Would it be correct, or even preferable, to speak of “freeing-up space” or “freeing-up capacity”. I think people are getting confused with cognitive load theory by interpreting it as just being the same as the idea that there is a limit to total capacity of working memory (i.e. not recognizing the importance of whether something is already known or not).

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