Explicit Instruction

(Done Right)

Explicit instruction (EI) has become synonymous with traditional teaching and in some circles this conjures up the caricature of the boring droning teacher who lectures without interest in their students and then assigns mindless busy work in the form of worksheets. This is not EI! While it is possible to see classrooms like these, they are not examples of the defining features of EI.

I claim that EI done right is:

Well planned
Interactive and dynamic
"Engaging" and motivating
Compatible with Assessment for Learning
Aligned with the recommendations from the Cognitive Sciences

Proper EI consists of the following 4 parts:

Managing students' cognitive load
Using effective narrative structures
High levels or participation and thinking hard
Motivating students with formative assessment that generates quality feedback

Managing Cognitive Load

Cognitive load theory (CLT), as well as ways of managing intrinsic and extraneous load, is well summarized here.

However, there is an additional piece of the puzzle: the challenge equation. This equation is a model that helps teachers approximate the amount of challenge any given task may pose to our students.

Here are some things ideas to reflect on: as domain knowledge in a subject grows and/or as support is given to a student, the challenge decreases (i.e. challenge is inversely proportional to domain knowledge and support). Moreover, the greater the number of interacting parts in a task or the level of abstraction, the greater the difficulty (i.e. challenge is directly proportional to the number of interacting parts and abstraction). Keeping these four variables in mind, we can monitor and adjust (differentiate) the challenge levels.

Directions of Travel (DOT) and Narrative Structures

People have evolved to tell and make sense of stories. Therefore, stories are an excellent vehicle for important information that needs to be remembered. DOTs are examples of narrative structures we can use to improve explanations.

The DOTs:

Simple to complex
Forest-trees-forest

Example-principle-example
Explanation then definition

Conflict then resolution

Simple to Complex

David Ausubel tells us that prior knowledge is important to new learning - that is it is easier to build new knowledge on top of existing schemas. That said, moving from simple to complex allows us to build more complicated ideas from simpler often pre-existing knowledge.

For example, when teaching about chemical bonds, at first students are told they are "connections" between atoms and as time progresses, these ideas are built on such that the "connections" become different types of bond (e.g. ionic, covalent) increasing in complexity.

In physics, we learn about speed before we discuss the more complicated concept of velocity (the former is a quantity the latter is a vector).

It is generally true that in our explanations, we ought to move from concrete to abstract or familiar to unfamiliar (this is why we use analogies, for example).

Forest-Trees-Forest (Big Picture-Small Picture-Big Picture)

One thing we ought to avoid is not seeing the forest for the trees. The details and nuances of a concept are important but students need to understand the big picture too. This is why a good approach is to reveal the big picture then zoom into the details before then zooming out again to gain a new appreciation for the whole.

For example, teaching a grade 7/8 class about the heating and cooling curves (graph of temp vs time of water as it changes states).

Example:

It's normal to think that if you heat water the corresponding heat-time graph would look like graph 1 - it gets hotter and hotter and hotter...

But actually, it looks like the second graph.

[Teacher explains what happens at the particle level]

Now let's take a step back and see why graph 2 is the correct graph and not graph 1.

Graph 1

Graph 2

Example-Principle-Example

Examples help students form mental models of the concepts we teach. But, we must be careful that our examples are well sequenced so that students extrapolate from them the correct features that we are trying to convey.

To the right, I demonstrate a well sequenced example. Below, I show how it could go wrong.

Click here to read about how it could go wrong.

Well sequenced example:

Teacher is giving a lesson on adaptations.

Polar bear camouflage (example)
White baby seals (example)
Adaptations: how animals suite their environments (principle)
Dead-leaf mantis (an example that's not just about colour but also shape)
Seal fat (example that expands principle and is not about camouflage but heat retention)
Elaborate bird dances (example that expands principle to behavioural adaptations)
Wolves hunting in packs (example of behaviour adaptation)
[Expand principle explicitly to include behaviour]
Opposable thumbs in humans (example)
Verbal communication in humans (example)
[Expand principle to allows students to appreciate that we are animals and adaptations apply to us too]
Etc.

Explanation Before Definition

Don't Do

Avoid starting with abstract definitions. For example, in a biology class one might see the lesson start like this:

‘Homeostasis is the maintenance of a constant internal environment’...

By starting with a generalized definition in this way, we present vacuous strings of words devoid of meaning. This increases cognitive load and risks demotivating students at the start.

Instead, one should start the lesson something like this:

“Imagine you are exercising. Your body temperature goes up. How does your body respond? You sweat, cooling your body down. On the other hand, on a cold winter day, as soon as your body temperature goes down, your muscles start shivering which warms you back up. So, when your body temperature goes up, your body does something to bring it back down. When it goes down, your body does something to bring it back up.”

In this case, students can relate to the information. David Ausubel would say we identified what the students already knew and we taught them accordingly. Building new knowledge on top of old.

Conflict Then Resolution

Which introduction is better?

Intro 1:

Good morning grade 6.

Today we will look at how organs in the digestive system work together to break down food into small molecules that our body can use for growth and energy.

Intro 2:

Good morning grade 6.

All animals eat food - they need this food to grow and get energy. But, think about how strange it is... how does our body take a burger, or salad and use it to grow? We don't look in the mirror and see a big burger, so what exactly is our body doing to the food?

Intro 2 sets up a conflict - a tension - that the mind wants resolved. Posing essential questions at the start of class does this. In this way we create a need (motivate students to seek out an answer) and we sell the the solution (deliver the lesson we planned).

High levels of participation and thinking hard (Ratio)

Ratio: Thinking and Participation

Ratio is a Doug Lemov term that refers to the number of students actively engaging with the content of the lesson.

Two very good indicators of learning include time on task and level of cognitive effort. Therefore, it would make sense to increase your class' participation and thinking ratio (i.e. the relative number of students thinking hard and participating). See the adjacent PDF for examples.

Participation is achieved by using whole-class activity strategies such as mini whiteboards or finger voting (I like using coloured cards or markers to indicate my choices) or cold-calling.

Hard thinking happens when students cannot go into "autopilot" mode. Interleaved rather than blocked practice is recommended here. In question sets, ask questions from previously covered units to break the pattern (an added benefit is that this is retrieval practice of previously learned material).

Examples of Ratio:

Participation and thinking ratio activity (2).pdf

*MWB = mini whiteboards

Feedback and Motivation

Increasing amounts of evidence demonstrate that success comes before motivation - that is, experiencing success is highly motivating and motivated students engage in more of that kind of behaviour (see key principle 1 here). While motivation does lead to more success, successes leads to more motivation. If your struggling to motivate students, start by having them successfully complete a challenging task - this should generate some motivation.

There are a couple caveats here:

if the challenge is too low or too high, students will either lose interest or be demotivated. Therefore keep the challenge equation in mind
not everyone comes to your class intrinsically motivated by your subject and that's okay. Some amount of extrinsic motivation will need to be applied to shepherd your flock.

The feedback we give our students plays a role in their motivation. Novice students require directive feedback while experts benefit more from non-directive feedback.

Directive vs Non-Directive Examples:

Scenario 1:

Sam has just finished teaching his class about gravity. He does a quick check for understanding (CFU) and asks his class why things don't fall off the bottom of the planet with a cold-call. A student says 'because gravity sticks things to the planet.' Sam says ' interesting, but that's not what I was looking for' pauses for a little while and then moves on to another student.

The above is an example of non-directive feedback. The teacher is hoping not to embarrass his student by saying "interesting" and doesn't want to give too much help but waits to see if the student could fix their thinking. The problem here is that novices do not know what they do not know. Sam's student is lacking too much domain knowledge to evaluate their own answer and may have been confused by the teacher's comment of "interesting". Here Sam should have said "Thanks for sharing - that's a common misconception and I'm glad you said it. No, gravity does not 'stick' things like glue. Who can make this right?" After hearing the correct answer from another student, Sam should come back to the first student and have them now answer the question correctly.

Scenario 2:

Sam's class is answering a set of questions about photosynthesis and, as he circulates the room, he notices that a student has written that carbon dioxide is absorbed in the roots of a plant. Sam interrupts the student and says 'what comes in from the roots?' [water] 'good, yes. Not carbon dioxide. Carbon dioxide is absorbed in the leaves during photosynthesis. Make sure you review this for homework because I'll ask you about this again soon.'

Here Sam noticed a student with low domain knowledge struggling and rather than playing the game "guess what's in the teacher's head" or "20 questions", Sam immediately corrected the student and instructed them to practice this more (with retrieval practice homework) because there will be a check up (likely in the form of a prior knowledge check in the next class). Directive feedback of this kind reduces the chances that a student becomes demotivated as they fumble to make sense of the teacher's cryptic questions.

Scenario 3:

Sam has been working with his class for weeks on tectonic plates and his class has demonstrated a lot of mastery in this topic when he checks for understanding. In a sketch and explain activity, Sam notices a student accidentally mislabeled the Earth's crust. He interrupts the student and says 'I'm noticing a mistake somewhere in your labelling - please look it over' then walks away.

Here the teacher knows their student has the domain knowledge and can find and correct the error independently. Non-directive feedback is well applied here.

Work-Focused VS Student-Focused Feedback:

Be careful giving student-focused feedback. Carol Dweck in Growth Mindset points out that feedback that is about immutable characteristics of one's self tend to demotivate students - students may begin to believe they are 'not meant for the sciences'. Ego-centered feedback causes these kinds of problems. Telling a student "great job. You're so smart" could inadvertently reduce their future participation - they will want to avoid making mistakes and losing their status as smart kid.

A generally good bet is to give work-focused feedback. This tends to be immediately actionable and clear and separates the student's ego from the error, yielding better results from the feedback. So, rather than saying "This is very messy work, you need to fix it." one ought to say "It's hard for me to follow your thinking. Can you write each step in the math on a new line like this?" [shows an example] "When you're done this come back and I'll look at it again. Thank you". [student follows instructions then returns] "See this is very clear for me now. I'm noticing a problem on line 2. It looks like you forgot to convert your units. Fix this please." (etc.)

Collecting Data to Give Good Feedback:

This is an entire subject on its own. I've written about formative assessment here here and here.

Conclusion

I hope that this is convincing evidence that Explicit Instruction is not the dull, sit-back-and-absorb caricature we sometimes hear. Not only is there a lot of evidence from the cognitive sciences supporting EI done well, it seems to be a prerequisite for success in other more inquiry or discovery based activities, as well as for what has been dubbed '21st century skills'.

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