Learning Walls & Why They May Not Be a Good Idea

By | First Published: | Last Updated: 12 April, 2021

Where I live, there is currently a great deal of frenzy over creating learning walls in classrooms. This frenzy intensifies when bigwigs visit schools and classrooms. But what are learning walls and are they a good idea? The answer may surprise you! So, read on.

If you are in a rush, you can skip down to the answer if you wish.

Or, you can read through the reasoning behind the answer first. This reasoning explains:

What learning walls are

Where the idea for learning walls came from

A critical explanation of the research that supposedly supports learning walls

Finally, I answer the question are learning walls a good idea?


What are Learning Walls?

Learning walls are a visual classroom displays that are meant to make intended learning visible to students. More specifically, learning walls:

Show students the big picture of what they are learning

Include learning intentions and success criteria

Students are often involved in creating the learning wall. This co-construction is meant to help them to clarify in their minds what they:

Will be learning (learning intentions, learning targets)

Need to do in order to prove they have succeeded in learning it (success criteria)

Students are also encouraged to use the learning wall in conjunction with activities such as:

Self-assessment

Collaborative assessment

Learning walls are related to, but distinct from other types of wall displays such as:

Data walls

Bump it up walls

Yet, in practice, there appears to be some cross-over between these different types of visual displays.


Where Did the Idea for Learning Walls Come From?

Two ideas met, and that meeting led to many teachers using learning walls in their classrooms. The two ideas were:

Data walls (visual displays of student, achievement and growth)

Visible learning (learning intentions and success criteria)

where learning walls come from

Data Walls

Data walls were one of the key ideas that led to the notion of learning walls. They started as a way to build collective teacher responsibility and efficacy for improving student results. The use of data walls was usually part of a broader school improvement process.

sample data wall image

You don’t need to have a full understanding of data walls to grasp how they influenced the idea of learning walls. However, a few points are worth noting.

Influential advocates of data walls, such as Michael Fullan and Lyn Sharratt, championed visual displays of student data as a way to help teachers and school leaders make data-driven decisions. Lyn Sharratt later advocated the use of learning walls.

These displays of data (i.e. data walls) were for teachers and school leaders. They were not for students. So, school leaders put them up in places where students could not see them (e.g. staffrooms).

Using co-constructed Data Walls, teachers and leaders assess trends that concern them, question each learner’s progress, and begin work to prevent losing track of the progress (or lack thereof) of any learner.

Lyn Sharratt

Data walls influenced the later idea of learning walls by planting the notion that co-constructed visual displays were a potentially powerful way to stimulate focused action.

Visible Learning

The second central idea behind learning walls was John Hattie’s notion of visible learning.

The idea is quite simple. John believes that students achieve better results when teachers and students are clear about what students:

Need to learn

Must do to demonstrate their learning

John uses the term learning intentions to describe what students need to learn. Put another way, learning intentions are what teachers want students to learn after a lesson, a series of lessons, a unit or even after a full year of learning.

John uses the term success criteria to describe what students must explicitly do to show they have successfully achieved the learning intention.

Note, John does not specify how teachers should help students gain clarity over what:

They are learning

Success looks like

This makes sense, as the best way to achieve such clarity is determined by the:

Age of students, what they already know and what they can already do

Nature of the learning and how you will assess it (e.g. success in writing a persuasive essay needs more criteria than finding the area of a rectangle)

For an example of age relevance, a teacher in the early years may want the students to be able to write a sentence (learning intention) and may judge their success using criteria, such as:

Sound-letter relationships

Spaces between words

Sentence boundary punctuation (capitals and full stops)

Yet, if most of the children are still learning the fundamentals of reading, it makes no sense to display written criteria. A better solution, in that case, would be to:

Read the following sentence to the student

Highlight and talk about what you are looking for in the sentence

Clear learning intentions, transparent success criteria, and making learning visible to the student are the key elements of engaging students.

John Hattie

How Data Walls + Visible Learning Led to Learning Walls

Data walls showed the potential power of large, co-constructed visual displays.

Visible learning highlighted the potential power of teachers and students being clear about:

Intended learning

What success looks like

Then, these ideas merged into the notion that co-creating large visual displays showing learning intentions and success criteria may be a good idea.


The Underlying Research

To understand the research discussed below, you must have a basic understanding of different types of research.

Types of Research

Many teachers are unfamiliar with research methods in education and what they are suitable for. If that is you, here is a quick primer that will help you understand the actual research that follows.

Experimental Research

Experimental research shows that X causes Y. For example, this type of research has shown that spacing out practice over time leads to better achievement than practising intensively for a short block of time. Behavioural scientists usually conduct experimental research in a university lab or room. This environment allows researchers to control other factors that may cast doubt on the research findings (e.g. teacher quality, time of day etc.)

Quasi-Experimental Research

Researchers often conduct quasi-experimental research in real settings, such as classrooms. Therefore, this type of research can show that an idea that works in a lab also works in practice. On the downside, it cannot fully control other potential factors that may have affected achievement. However, researchers address this to some degree by using randomisation and large numbers. For example:

Randomly choosing 50 classes to use learning walls

Doing the same for 50 classes to not use learning walls

Then comparing the results of the 2 groups

Correlational Research

Correlational research reveals if there is a relationship between two factors. Yet, it cannot show that one factor caused a change in the other. For example, there is a correlation (relationship) between student achievement and students’ belief in their ability to do well at school. However, correlational research cannot show whether:

Students’ belief in their abilities led to (caused) higher levels of achievement, or whether

Students’ high levels of achievement caused them to have a stronger belief in the ability to do well at school, or whether

There is a reciprocal relationship between the two

Case Studies

Case studies are merely descriptions of something that happened. They cannot prove that X caused Y or even that X and Y are related. For example, a case study of a man who smoked until he died at the age of 102 doesn’t prove that smoking causes longevity.

Why then are case studies considered research? There are 2 key reasons. Case studies can:

Highlight factors that may be worth researching in more rigorous ways (experimental, quasi-experimental, correlational)

Be a useful follow-up to more rigorous research, offering practical examples of how teachers have implemented an idea (such as spaced practice) in different contexts

Experiments, quasi-experiments and correlational research produce hard evidence, while case studies produce soft evidence.

Research on Learning Walls

My search for and review of research on learning walls revealed 3 key things. There:

Is no hard evidence that shows learning walls lead to better learning outcomes

There are case studies that describe schools who have used learning walls (along with other initiatives such as changing how they teach reading) that show improved results

Is some hard evidence to support some of the ideas underpinning learning walls, as well as some hard evidence against such visual distractions, but the research is complex and does not relate directly to learning walls.

As the research doesn’t exist, I cannot elaborate on point one, other than to highlight its importance.

There is no hard evidence that using learning walls leads to increases in student achievement.

For an example of a case study mentioned in point two, click here.

Following is a highlight of research underpinning learning walls (point 3), but which does not evaluate learning walls per se.

The research underpinning learning walls is complex and uses a wide range of terminology not previously covered in this article. To make matters worse, researchers have often used different terminology to each other.

The importance of teachers and students being clear about what students need to learn

The value of having some tangible idea about what successful learning looks like

The usefulness of students using the above to enhance their learning

Research on Clarity About Intended Learning

There is evidence that a concept called teacher clarity has a moderate to a strong relationship with student achievement. This research has been collated and evaluated in two meta-analytic reviews by:

Frank Fendick

Scott Titsworth and his colleagues

A meta-analytic review involves collating many individual research studies and statistically combining the results to show the strength of the relationship or the size of the impact.

4 points about the research on teacher clarity are worth noting:

The research was correlational, so it showed that teacher clarity was related to student achievement, but not that teacher clarity caused improvements in achievement

As the name implies, teacher clarity refers to teachers being clear about intended learning – not students.

The concept of teacher clarity includes several components, only one of which was being clear about intended learning.

The research did not say anything about putting learning intentions up on walls.

Research on Success Criteria

No research uses John Hattie’s phrase success criteria. However, there are two collections of research that exist and support the idea using different terminology.

One collection uses the term criterion-referenced feedback

The other uses the term self-evaluation

In the first collection, Robert Marzano and his colleagues explored a wide range of research on classroom instructional strategies. After reviewing this research, he concluded that one (of many) effective strategies was criterion-referenced feedback. Put another way, learning is enhanced when teachers use explicit criteria to judge students work and offer concrete suggestions on how they can improve.

In the second, Lyn Lavery, as part of her research into self-regulated learning, collated and analysed findings on the effectiveness of self-evaluation. She defined self-evaluation as the student:

Setting their own standards

Judging their efforts against those standards

Both Marzano’s and Lavery’s reviews involved using criteria/standards, but:

Marzano focused on teachers using criteria to help students improve their work

Lavery focused on students making and using standards to improve their own work

It is also important to realise that:

Neither Robert Marzano or Lyn Lavery explored the effectiveness of putting success criteria up on a classroom wall

Lyn Lavery’s review of research included many studies on self-evaluation being used at a university level

Research Against Learning Walls

There is no research that directly shows that learning walls are a bad idea. Yet, there is research showing that visual distractions impede learning. For a good, plain language explanation of this research see Brad Nguyen’s article on Minimising Classroom Displays.

So, Are Learning Walls a Good Idea?

With any new initiative, amongst other things, you must consider:

What the research says about the positive effects of the idea

Potential adverse effects of the idea (e.g. time, effort, money, use of space, distraction for students)

Whether the effects in point 1 are worth the effort involved in implementing the idea

With these three things in mind, I advise against using learning walls in your classroom/s. At best, the existing studies support nothing more than research trials. They are not enough to justify:

Widespread adoption

Dogmatic imposition

The widespread adoption of practices not grounded in evidence is nothing more than a fad.

shaun killian drawing

SHAUN KILLIAN
(MEd., MLead.)

Shaun Killian (me) is an experienced and passionate teacher, as well as a past school principal. After a heart transplant and having both my legs amputated, I am not yet capable of returning to work. Yet, my passion for helping students succeed has led me to use my time to research teaching and associated practices. I then share what I find in practical ways through this website. The greatest compliment I have ever received from a past student was I never left any student behind. That is mission of most teachers and I hope you find the information on this site useful.

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