Explicit Instruction: Concreteness Fading

Posts in this series…
1. What is Explicit Instruction?
2. Explicit Instruction: Segmenting Complex Skills
3. Explicit Instruction: Teacher Talk and Equity
4. Explicit Instruction: Modeling

Concreteness fading is exactly what the name suggests. You start with a concrete example, and once your students have grasped it, you fade it out for a more abstract representation. The purpose behind this strategy is that abstract representations are more generalizable than concrete ones.

When teaching a concept you should use an example with strategically extraneous details. It sounds strange, but it’s true. Concrete examples help students with initial learning because they have extraneous details (Glenberg et al., 2004). These details help “ground” the concept in the familiar, allowing students to grasp the example. 

However, the extraneous details making up a concrete example hinder generalization and transfer (Petersen & McNeil, 2013). Hence the need to fade from concrete representations to abstract ones.

Useful Definitions

We do run into a bit of an academic language problem when talking about concreteness fading. Technically, abstract representations do not exist because, whenever you describe something, or write, or draw it, parts of that idea become concrete.

In their 2018 paper, Fyfe and Nathan propose a simple linguistic work around. Instead of referring to examples as concrete (specific and non transferrable) or abstract (general and transferrable) we instead identify them as less idealized (concrete) or more idealized (abstract). 

Concrete Examples (Less Idealized)

Not all concrete examples are created equal. Concrete examples that are less idealized add seductive details that make it more difficult than necessary in order to learn and generalize the example (Sundararajan & Adesope, 2020). So when we are crafting our concrete examples, we should be careful with the type of extraneous information we include, that extra information might not help initial learning.

We ought to include the extraneous information that improves initial learning (It isn’t really extraneous then, is it?). There are two types of information to be wary of: perceptual and conceptual.

Perceptual information pertains to the physical properties of the example. This could include 2D or 3D representations, visual surface features such as patterns and how real an object looks. Researchers have found that 3-Dimensional representations are generally more effective than 2-Dimensional objects, at least in math (Carbonneau, Marley, & Selig, 2013). In addition, representations that are particularly rich in visual surface features have been found to inhibit learning compared with less perceptually rich objects (Kaminski, Sloutsky, & Heckler, 2013).

The solution to this isn’t to only use 3-D or less perceptually rich representations. It is simply to be smart about it. 

What are you teaching? What is the main idea of the concept? Does the picture/diagram allow students to make incorrect inferences? How much explanation will students need to understand your concrete example? Is the “extraneous” information in this representation directly relevant to the concept?

Conceptual information is trickier, because it is learner dependent. Conceptual information depends on the background knowledge your students bring to the table. If your students are very familiar with an object, it is often difficult for them to think about that object abstractly (Petersen & McNeil, 2013).

Abstract Examples (More Idealized)

A good abstract, or idealized representation allows students to make the intended generalization with the least effort. Essentially, in a more idealized representation, your students will be more likely to successfully transfer their learning to a new context. We should also expect for students who are more novice to struggle with transferring their learning, even if they are able to think about the underlying ideas of the representation (Koedinger & Nathan, 2004).

The purpose of an idealized representation is to encourage generalization and transfer. Idealized representations achieve this by moving the focus from the what representation is to what the representation does. Idealized representations are able to do this because they lack the extraneous details of less idealized representations.

The extraneous details of a less idealized representation help to ground the example in the familiar and the relatable, thus, providing a fertile context for initial learning (Glenberg et al., 2004; Schliemann & Carraher, 2002). And it is this same grounding that reduces transfer of learning. Think about an optical illusion. If you see the young lady first, it can be hard to then see the old hag, and vice versa. When we use more abstract, more idealized representations, we make it easier for students to generalize and transfer their learning.

Three Concrete Goals

According to Fyfe and Nathan (2002) three goals of concreteness fading are to

1. Promote initial learning with a meaningful, less idealized representation of the concept. (grounded context)
2. Promote transfer of learning by ending a learning sequence with a generic, broadly applicable idealized representation.
3. Draw connections between less idealized (concrete) and more idealized (abstract) representations to create a well developed schema.

Concreteness Fading (Less to More Ideal)

Concreteness fading aims to take advantage of both concrete and abstract representations. The extraneous details of a less idealized example help the student to learn the concept, but these same details prevent students from transferring that concept, it is inert, inflexible knowledge (Schliemann & Carraher, 2002). However, if after initial learning you begin to use more idealized examples by reducing the extraneous details, your students will be more able to generalize and transfer the concept, making their knowledge applicable and flexible (Kaminski, Sloutsky, & Heckler, 2008).

As we fade from the less ideal to the more ideal, we don’t simply want to focus on the idealized examples. Concreteness fading is not a checklist procedure to follow, the initial concrete examples are still true, they are still valuable. 

The concrete examples help provide a continued grounding for the abstract ones, so we should ensure our students know not only the concrete and abstract representations of the concept, but we should also ensure they understand the connections between concrete and abstract representations by making the connections explicit. 

Fyfe and Natan encourage teachers to use a 3-step progression starting with a grounded, less idealized representation before fading into an abstract, idealized one. In order to do this successfully, teachers must reduce the perceptual and conceptual information their examples contain. 

The classic example of this 3-step model is in math. You start with a 3-D manipulative and go to an image on the paper and you finally conclude with just numbers.

This 3-step strategy can be applied in many other classes and age groups as well. In science, you could start teaching about a food chain by showing a video of a gazelle grazing in the savanna being silently stalked by a cheetah. Next, you could show the classic image of a food chain and then, finally, have your students generalize the pattern of food chains to any environment (producers to primary consumers to secondary consumers, etc).
1. Springbok Antelopes vs Cheetahs (Antelopes are a type of gazelle)
2.
3. Producer –> Primary Consumer –> Secondary Consumer

*Note: You should use the correct vocabulary throughout your examples, whether they are concrete or abstract. Ex: The bush is a producer, the gazelle is a primary consumer, the cheetah is a secondary consumer.

This will give your students more exposure to the vocabulary in context, which will also make transferring their knowledge easier.

Concreteness Fading, Research, and Teachers

Concreteness fading is not an end all be all for education, it alone is not a silver bullet. But, if we want all of our students to know our subjects deeply, it is vitally important. The methods proposed by Fyfe and Nathan will also give our students exposure to multiple models of a concept, this likely increases the flexibility of their learning (Jacobson et al., 2020).

By teaching with methods aligning to research, we make the curriculum more accessible for all students. When we deviate from research and go with mere instinct, we increase the likelihood of creating an inequitable learning environment. Research alone is not some paneca of perfection, but without it, what are you going on beyond experience?

We should understand the broad principles of research and apply them to our context with nuance.

Sources

• Carbonneau, Kira, Scott Marley, and James Selig. 2013. “A Meta-Analysis of the Efficacy of Teaching Mathematics with Concrete Manipulatives.” Journal of Educational Psychology 105 (2): 380–400. doi:10.1037/a0031084.
• Fyfe, E. R., & Nathan, M. J. (2018). Making “concreteness fading” more concrete as a theory of instruction for promoting transfer. Educational Review, 71(4), 403–422. doi: 10.1080/00131911.2018.1424116
• Glenberg, Arthur, Tiana Gutierrez, Joel Levin, Sandra Japuntich, and Michael Kaschak. 2004. “Activity and Imagined Activity Can Enhance Young Children’s Reading Comprehension.” Journal of Educational Psychology 96 (3): 424–436. doi:10.1037/0022-0663.96.3.424.
• Jacobson, M. J., Goldwater, M., Markauskaite, L., Lai, P. K., Kapur, M., Roberts, G., & Hilton, C. (2020). Schema abstraction with productive failure and analogical comparison: Learning designs for far across domain transfer. Learning and Instruction,65, 101222. doi:10.1016/j.learninstruc.2019.101222
• Kaminski, Jennifer, Vladimir Sloutsky, and Andrew Heckler. 2013. “The Cost of Concreteness: The Effect of Nonessential Information on Analogical Transfer.” Journal of Experimental Psychology: Applied 19:14–29. doi:10.1037/a0031931.
• Koedinger, Kenneth, and Mitchell Nathan. 2004. “The Real Story behind Story Problems: Effects of Representations on Quantitative Reasoning.” Journal of the Learning Sciences 13 (2): 129–164.
• Petersen, Lori, and Nicole McNeil. 2013. “Effects of Perceptually Rich Manipulatives on Preschoolers’ Counting Performance: Established Knowledge Counts.” Child Development 84: 1020–1033. doi:10.1111/cdev.12028.
• Schliemann, Analucia, and David Carraher. 2002. “The Evolution of Mathematical Reasoning: Everyday versus Idealized Understandings.” Developmental Review 22 (2): 242–266.
• Sundararajan, N., Adesope, O. Keep it Coherent: A Meta-Analysis of the Seductive Details Effect. Educ Psychol Rev (2020). https://doi.org/10.1007/s10648-020-09522-4