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Understanding scaffolding or…

…scaffolding understanding?

Hello and welcome to the 73rd edition of our fortnightly newsletter, Things in Education.


One of the most important parts of planning lessons is to plan the scaffolding that a teacher needs to give the student to ensure deep learning. Deep learning means that students not only understand surface details but are also able to recognise patterns and apply their knowledge in different contexts (you can read more about surface structures and deep structures in the 8th edition of our newsletter). So, what is scaffolding?


In a general context, we know that scaffolding is what is made before a building’s construction begins. Scaffolding helps in building the structure, holding up the structure while the concrete dries and becomes strong. Once the building is ready, the concrete has set and the building is strong, the scaffolding is removed from the structure. In the exact same way, as teachers facilitate the building of students’ learning, they need to provide support and structure to students along the way. This process of providing support is called scaffolding. And much like the scaffolding in construction, this teacher support also has to be reduced and finally removed as students start mastering the material. 


The process of scaffolding can be divided into two components: chunking and teacher involvement. 


Chunking is the process of cutting up the material to be taught into small bite-sizes that the students can tackle. Why should you break down information into chunks? At the surface level, it may seem like breaking down things and teaching it is too ‘Direct Instruction-ish.’ However, breaking down information is quite important in problem-based or project-based learning too. But, the main takeaway is that it reduces the load on students and doesn't make them feel overwhelmed.


Barak Rosenshine gives a great example of chunking in the article Principles of Instruction. “...when students were taught a strategy for summarizing a paragraph, an effective teacher taught the strategy using small steps. First, the teacher modeled and thought aloud as she identified the topic of a paragraph. Then, she led practice on identifying the topics of new paragraphs. Then, she taught students to identify the main idea of a paragraph. The teacher modeled this step and then supervised the students as they practiced both finding the topic and locating the main idea. Following this, the teacher taught the students to identify the supporting details in a paragraph. The teacher modeled and thought aloud, and then the students practiced. Finally, the students practiced carrying out all three steps of this strategy. Thus, the strategy of summarizing a paragraph was divided into smaller steps, and there was modeling and practice at each step.”


Teacher involvement is how much the teacher needs to help the students with their learning. Reciprocally, it is a measure of how independently a student is able to learn the material. What kind of teacher involvement is needed? While you should always plan for the kind of support you can provide, you should know what is equally important is the things you have not accounted for—your students’ questions. Questions are always a good thing because they are a way of knowing that your students are grasping what you are saying.

So, we can think of chunking and teacher involvement as two axes along which scaffolding can be broken down. How big the chunk size should be and how much teacher involvement should be present will be based on multiple factors. However, we can all agree that at the beginning of a topic, teachers will have to start in area A of the graph above—the teacher has to be intensely involved and the chunk size has to be small, so that the students are able to engage meaningfully with the material. We can also agree that evidence of deep learning is when students can deal with big chunks of information, make generalisations, integrate and apply knowledge from different “chunks”. And doing this with the least amount of teacher involvement is the final evidence of learning. So in other words, the students should end up in area D of the graph above. So in the process of learning, students need to move from area A to area D. And teachers need to plan how they are going to reduce their own involvement in making students more independent with the task or skill or knowledge and how students can deal with more and more material at the same time.


As an example of chunking, a teacher can get students to only do the first couple of steps of the procedure of long division and then start getting the students to perfect the skill. With time, the teacher can increase the chunk size by increasing the number of steps that the student needs to do at one go. Similarly, as an example of teacher support, the teacher can model the steps of the procedure of long division and with time, reduce the number of steps that they are modelling. This means that if the teacher has not done the example post step 2, the student will have to do the next steps independently.


One way to go from area A to D is to take Path 1. Here the teacher keeps increasing the amount of material for the students in every chunk, that is, increases chunk size while keeping the teacher involvement almost constant—area B. Once the students are able to deal with big enough chunks of information, the teacher involvement should be reduced. 


If students get stuck in area B, it means that students have not had enough independent practice of the skill that they are trying to build. Doing things independently for students in area B is the key.

Another approach to go from area A to D is Path 2. In this case, for a given chunk size, the teacher gradually reduces their involvement. As the students grow more confident in dealing with a chunk size, teachers can increase the size of the chunk. This can be repeated till students are independent, even for reasonably large chunks of material.


Here there are a few open questions: Where to start off from in area A. How much involvement is needed? What is the ideal chunk size? When does Path 1 work better? When does Path 2 work better? What does area C denote? These are some questions that we will tackle in future editions. In the meantime, we welcome your thoughts on these questions.

 

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Edition: 3.21

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