At Northwood College for Girls, we have many beautiful spaces for our students and staff, as well as many enabling spaces which provide our students with enriched learning experiences. One of these such spaces is our Makerspace, which since its opening has been used for STEM lessons. After a year, it felt like students and staff could gain more from this dynamic space. Because this was a space I felt particularly passionate about, I wanted to ensure that all staff and students became empowered to use it. As teachers, we often talk a lot about the importance of a learning space, when referencing study skills and habits. For example, UCAS says “Several factors can affect learning ability, including seating, light, noise, and even colour. Students who study in a positive learning environment have been shown to be more motivated, engaged, and have a higher overall learning ability.” Thus, having an inspiring learning environment, such as a makerspace, should also inspire creativity and engagement. So this year we have really considered how we can ensure that this incredible space does inspire learning.

What is a Makerspace?

According to the Government Department for Digital, Culture, Media & Sport; “A makerspace is a physical location where people gather to co-create, share resources and knowledge, work on projects, network, and build. They help intermediate and advanced users develop their skills and creativity, particularly inspiring younger generations to engage with the STEM agenda – Science, Technology, Engineering and Mathematics (or STEAM as it is now sometimes becoming referred to, by also including the Arts). Their activity promotes development of high-end technology skills needed for prosperity and social mobility.” Ultimately, a makerspace is a collaborative work space for making, learning, exploring, sharing and my new favourite word ‘tinkering’, that uses high tech to no tech tools. 

Why a Makerspace?

The fact that this features strongly in the UK Digital Strategy in 2019 (pre-pandemic) also highlights their value and potential impact. The International Society for Technology in Education (ISTE) says that making meets numerous ISTE Standards, including Empowered Learner, Innovative Designer, Computational Thinker, and Creative Communicator. Thus having a makerspace, where students can make and tinker, cultivates these skills. Furthermore, it can provide students with the following learning opportunities:

1. Provide hands-on learning opportunities. 

Students are able to learn vast amounts of concepts through books, lectures, and videos, etc. Yet, in a makerspace they have an opportunity to take an abstract concept and put it into practice. For instance, in a classroom students can learn about volume, but in a makerspace students can make a 3D printed chocolate mould with a specific volume. They can learn about electricity, but in a makerspace students can make a paper circuit and create a celebration card that lights up.

2. Teach students resilience.

Makerspaces give students an opportunity to use various tools and materials. As they ‘tinker’ they will naturally analyse what’s working and what’s not, and they have to try different strategies to solve problems. Through this process, students learn to experiment, accept failures, make improvements, and develop the resilience they need to try and try again.

3. Help students build communication, creativity, and collaboration skills.

Any classroom teacher knows the pitfalls of project based learning. There are of course many benefits, but often project based learning isn’t executed or completed to the standard that we would like. Yet, in a makerspace, projects authentically create collaboration and communication. Students naturally communicate, contribute ideas, and take on tasks, which is wonderful to see and helps students to build the necessary ‘soft skills’ of the 21st-century, such as collaboration, creativity, and communication.

4. Encourage educational equity.

Makerspaces help introduce students to engineering, computer science, robotics, and other sciences that have traditionally been the ambit of white males. In a makerspace, girls, students of colour, neurodiverse students, EAL students, and students of any socioeconomic background can access the same tools and technology that once may have been available only to students in gifted programs or in robotics clubs. Although our context is a girls’ school, allowing our students to have a safe space and exposure to these technologies, the chance to build resilience, before industry, will reduce any fears of imposter syndrome that they may otherwise fear when entering and learning in what is still a male dominated field.  

5. Can help students do better in school.

Finally, there is some small research which shows that students who are engaged learners are more likely to attend school and graduate. Thus, having a makerspace which engages a variety of learners, will improve attendance and attainment. 

What have we done?

To empower our teachers and support them in embedding the use of the Makerspace into their curriculum, Adam Giblin and I delivered a whole school CPD on Design Thinking. Design thinking is a process used to understand needs, challenge assumptions, redefine problems and create innovative solutions to prototype and test. It is most useful to tackle ill-defined or unknown problems and involves five phases: Empathise, Define, Ideate, Prototype and Test. Design Thinking is not STEM, it is a process that can be used by all subjects and Key Stages, which is why we wanted all staff to have this CPD as part of the launch of the Makerspace. Adam then continued to offer CPD on Design Thinking as part of our Teaching and Learning Pathways in the senior school. 

In this first year we received training from the companies who provided the equipment and saw use of the Makerspace by STEM and by Textiles, but we wanted to grow the space further. We also noticed that the companies who provided the equipment shared banks of ‘templates’ for printing, and although these were impressive, templates were counter intuitive to the ethos of why the makerspace would be meaningful. This year, I have been working with the Cambridge Makerspace to further develop how we train staff. From this, we have developed tutorials on how to use software which allows students to build their own designs for printing and cutting. It also established some important principles to keep this space running and safe. Firstly, the machinery and equipment has become RAG rated. Red is equipment that is only to be used by staff after training and passing a risk assessment quiz, this is the laser cutter. Amber is equipment that is only to be used by staff and students after training and passing a risk assessment quiz, this is for the 3D printers. Green is for equipment that can be used by anyone, such as card, paint, glue and crafts etc. To ensure that this information, training on the equipment and training on the correct programmes to use the equipment was accessible, a Google Site was created. This will remain as a hub for all things Makerspace related: https://sites.google.com/nwc.gdst.net/nwcmakerspace/home 

Once this was created, I invited ESLT to be ‘friendly critics’ and receive training which follows the instructions on the Google Site. This allowed for any issues or missed instruction to be spotted. It also means our ESLT are fully able to support staff in using this space too, as they know the full use and benefits. After this, some changes were made and our first group of teaching staff from Senior School and Junior School received training. 

Conclusions

Investing in a Makerspace will provide our students with a unique opportunity which will serve them as they enter into a workforce and world which is still a little unknown. They will have the skills of resilience, collaboration, creativity, reflection and teamwork, to name a few, to ensure that they thrive. This space will need to be looked after and will need to be embraced by teachers who are resilient too, something which we have in abundance. There are still learning opportunities for this space, and I know it is not completely self-sufficient, but for our students, this space can be transformative. Finally, as this will be my last blog at Northwood College for Girls, it is only fitting that I am writing about the importance of remarkable spaces. Northwood is an inspiring and remarkable place to work. The students, the staff, the whole school community is truly something special, and a place I will always hold dear in my heart. When we say, ‘first, we teach fascination’ we really do mean it and the Makerspace is simply one of the many ways in which we do this.

References

How your surroundings affect the way you study | Undergraduate | UCAS. 

Libraries and makerspaces – GOV.UK 

The Benefits of a Makerspace Learning Environment | Walden University. 

Why Your Students Need a Makerspace – The STEM Maker Lab 

Eduporium Weekly | Why Are Makerspaces Important? – Blog 

What is Design Thinking? — updated 2024 | IxDF 

For the final TeachMeet of the year, it felt important to discuss Artificial Intelligence, not only for the impact it will have on education (and is already having), but just the impact it could have on multiple disciplines and careers that will ultimately affect our students. This time, I took a slightly different approach and conducted some ‘provocations’ via Mentimeter, then took staff through some of the research, as well as sharing some practical tips for using AI. As always, I want to give full credit where it is due. Most of the research and ideas have come from Daisy Christodoulou’s book ‘Teacher vs Tech’ and from the AI in Education Conference organised by Anthony Seldon at Epsom College in May. For those of you who would like to watch the TeachMeet back, here is the recording: AI in Education – Friend or Foe (Recording).mp4 

Provocations: 

It was positive to see that no one was looking for a career change yet, and it is interesting that assessments were viewed as the area that will most likely be impacted. This probably comes from the fact that tools like ChatGPT have already started causing issues for coursework and homework. But, rethinking how we assess our students, isn’t necessarily a bad thing. 

Although the awareness of AI is there, given we know how ‘time poor’ the teaching profession is, it’s probably not surprising that most have not yet had time to use AI in the classroom yet (or not necessarily realised that they are). One of the main goals of the TeachMeet, and this blog, is to try and equip teachers in how they can best use AI in the classroom. 

Concerns

To start, we can’t ignore the elephant in the room, AI, for some, seems concerning. For us as teachers, the main concerns are probably more around ‘plagiarism and fake news’, regulation and pedagogically speaking, the potential loss of knowledge. 

Fake information is nothing new, and neither is AI. However, the past few months have seen a huge increase in awareness of AI and thus the concern around how it is growing. This is mostly down to the easy (and mostly free) access to ChatGPT. For those of you who haven’t heard of ChatGPT, this is an AI chatbot and language model that generates human-like text and responses. For this reason, plagiarism is one concern and JCQ have recently given information on expectations around the use of it. They don’t expect it to be banned (and I’ll go into why that’s a good thing later) but they do expect it to be referenced. However, with the battle of the AI plagiarism checkers (where AI generators are claiming they can’t be traced and new checkers claiming they can), this is still a difficult field to navigate. 

Another reason the ‘fake information’ stemming from ChatGPT is concerning, is how convincing this can be. It’s important to pause here and explain exactly what ChatGPT is, GPT stands for generative pre-trained transformer which is essentially a type of large language model that is making predictions using huge data sets. This can lead to a phenomenon called ‘hallucinations’. Hallucination in AI is when what is generated sounds plausible but are either factually incorrect, unreliable or misleading responses. These outputs often emerge from the AI model’s inherent biases, lack of real-world understanding, or training data limitations (for example, ChatGPT has a knowledge cutoff date of September 2021). But as a generative language model, it will give an answer to pretty much anything you ask, which means it is very good at being ‘confidently wrong’. This is particularly concerning as although AI models may be correct 90% of the time, if a student is seeing and believing the 10% that is wrong, this leads to misconceptions in their learning, which of course is incredibly dangerous. But this also exposes students to the biases of these models too.

At the moment, there is little regulation around AI. Again, we are seeing concerning headlines, including the creator of ChatGPT, Sam Altman, who admits that A.I. could cause ‘significant harm to the world’. In March, the Department for Education released a document ‘Generative Artificial Intelligence in education’, which was mostly positive about its use. One particularly important area to note within the Government document is around GDPR: Personal and sensitive data should not be entered into generative AI tools to ensure privacy. This seems sensible, however, there are certain platforms out there which do advocate for using AI to write reports which could encourage people to enter personal data, thus potentially breaching this. It is important that schools are giving guidance to staff about it’s appropriate use. 

The final concern, which I also hope to counter with ‘benefits’, is the possibility of Loss of knowledge and the risk of widening inequality. This stems from issues already raised such as ‘hallucinations’ but also digital literacy. We saw with COVID the different impact that online learning had on different areas of the UK alone, pre-2020 we never would’ve thought that ‘wifi poverty’ was a ‘thing’ whereas now we need to not only think about this but also the impact of AI Literacy. 

This shows the correlation between literacy rates and GDP (is a measure of the size and health of a country’s economy), therefore we know that literacy impacts economic success. As we move forward, the same is likely to be true for AI Literacy. But by this I don’t mean just having access to and using AI, I mean the ability to understand when AI is correct and not correct, having wider context and understanding that can then be applied to AI. This idea of context is something that Daisy Christodoulou looks at in depth in her book Teacher vs Tech, and brings me neatly onto looking at the research behind embedding technology effectively, as thus, some benefits of AI.

Benefits

So the first bit of good news, we will not be replaced by robots or ChatGPT! Panic over. And one of the reasons for this is the ‘novice to expert’ dilemma. Just like when Google was first invented and people assumed students could ‘just Google it?’, teachers weren’t made redundant. This is because AI (and Google) needs to be used by those who already have a certain level of understanding in the topic that they are using it for. Therefore, you cannot be a novice in the subject matter that you are using it for. Students who try to use it as a shortcut will not really learn anything and will inevitably get caught out, as they wont have the base knowledge to use it or to spot when it is wrong. (as AI is very good at being ‘confidently wrong’ or hallucinating). Therefore we as teachers are actually more equipped to use it and verify what it’s putting out there. 

So firstly, I’m going to explain some of the key ideas on cognitive science that Daisy examines in her book to better explain why AI will not replace educators. It’s important to remember that cognitive science underpins AI. So if we are impressed by how these tools work, it’s because they have ‘learnt’ in the exact same way that we do. They are quicker and have a lot more data stored, but let’s not forget that the only reason they learn is because there is a cognitive architecture which is common to humans, and they replicate this. Thus, humans still need to learn in traditional ways and the reasons why are rooted in Cognitive Science. AI cannot be a shortcut to our human learning, but something supplementary. 

In the book, Daisy explains how our working memory limits our ability to learn. Learning is like building blocks, to learn effectively, we need to have certain information already in place (or stored)  in our long term memory before we can build on it and learn more. If we try to learn too much at once, we are overloaded and nothing really stays in our long term memory. Cognitive load theory argues that the magic number for how much we can remember is 7 (plus or minus 2), but this slightly changes when we already have information rooted in our long term memory. 

Take these 18 letters (you have 5 seconds to memorise them all): 

SBB CNH SGM TRA FIT VFA

How many?

Now, you have 5 seconds to memorise the following 18: 

S BBC NHS GMT RAF ITV FA

How did you do? 

They are the exact same letters, however, these letters are structurally similar to acronyms familiar to most British people, thus we will remember more because we are now using our long term memory to simplify the task.

Another example to explain why having information already stored in our long term memory is important, is context. We need context to understand, so again, there is certain knowledge that we just need in our long term memory. For example, the word ‘bank’ and its context:

Bob stood in the lush meadows and listened to the sound of the boat oars. He could see John was standing by the bank.

OR

Bob stood outside the train station and watched the pinstriped financers rushing by. He could see John was standing by the bank.

The last sentence in these descriptions is exactly the same, ‘He could see John was standing by the bank.’ but due to the context of the prior sentence, we would have two different images in our mind. 

A final example of why we need certain knowledge in our long term memory is this very common scenario; who has ever asked a student to improve their writing by using more complex vocab? Take the sentence “I am a good footballer”. Have you ever had results like this “I am a congenial footballer”? Congenial means pleasing, pleasant etc, so you can see the similarity to ‘good’. But the sentence makes no sense.  

Background knowledge in our long term memory or prior knowledge helps explain the difference between novices and experts. If AI is used as a shortcut in knowledge acquisition, students will not learn anything.

The good news is that any novice can become an expert, but this is by developing these knowledge structures in the right way. And how we do this, is building knowledge through direct instruction. (This is why teachers won’t be replaced). Hattie’s 2008 meta-analysis ‘Visible Learning’ shows direct instruction is one of the most effective approaches. This creates the building blocks of learning. 

Now some may argue ‘What about constructivism?’ Which is the idea of constructing meaning for ourselves. Yes, this is important but it doesn’t mean guidance is harmful. Structured approaches help us to construct meaning whereas unstructured approaches can leave us confused or our working memory overloaded. This is one of the main issues that Daisy highlights with project based learning which isn’t well structured or expects ‘real world application’ too soon in the learning process. 

This in turn can lead to the ‘Knowing-doing gap’. The knowing-doing gap is more likely if students are taught in an unstructured way, – for example, when students know they should use capital letters for proper nouns and at the start of sentences, but don’t do so. This is because they have been taught how to write with capital letters by ‘doing writing’ e.g. by practising writing stories, letters and lengthy articles with a ‘real world purpose’. This overloads working memory because they are not just thinking about different technical aspects of writing but also the details of the topic. Therefore they need direct instruction on the smaller skills of writing a sentence that starts with a capital letter until this becomes a habit. Only then can they move on to these ‘real world’ application tasks. This is why we need certain knowledge in our long term memory. 

So this is why we can’t just ‘google it’?

Apply to internet searching (and ChatGPT): looking something up on the Internet or in any reference source, takes up valuable and precious space in working memory. Also, in order to look something up successfully, you need to have some idea both of what it is you are looking for, and what you expect to see. 

We need facts to think: we need facts in our long term memory. Everything we see, hear and think about is critically dependent on and influenced by our long-term memory. (Krischner PA eg al., 2006). This is also true as we start considering the use of AI and ChatGPT. As we saw earlier, ChatGPT isn’t always correct and it can be very convincingly wrong. Therefore our students still need to learn facts and have these as part of their long term memory in order to fully understand what they are looking at via AI.

Engagement: The multimedia principles

So now we have established that teachers are here to stay. How can we, as teachers, embrace this new world of AI? Firstly, we can ‘create memorable content’ that supports cognitive science. Such as through applying Richard Mayer’s principles of multimedia learning.

The multimedia principle is the concept of presenting text and images together, which enhances learning. Our limited working memories have two channels, one verbal and one visual so presenting both uses the full capacity of our working memory and allows us to build more sophisticated mental representations of the concept we are trying to learn. There are actually 30 multimedia learning principles. They do not depend on certain technologies, but they should be applied to how we create resources, including those using technology or AI.

But many of these get violated; e.g. images chosen for decorative purposes can end up confusing or distracting learners. Therefore presentations and video content needs to be carefully constructed. Some of the best ways to do this is by embedding questions in videos that let students check understanding and frequently using mini quizzes or end of unit quizzes (EdPuzzle and Google Forms). 

One very simple example of AI is using a platform called https://www.d-id.com/ (although it is not free), which is a website that can animate faces and use text-to-speech to being images to life (quite literally). You can even use ChatGPT to generate the speech or to tailor text that you already have into a more simplistic way. To make it really effective, on the slide of your AI creation, you could have key terms followed by some quiz questions. But even as a ‘hook’ or even a revision task to set students (once you are confident they are not novices), AI can bring some ‘life’ into our lessons.

Engagement: How can we use technology to personalise learning?

According to PISA, personalised learning is the biggest indicator of academic success (only below wealth). However, this is an issue when we have ‘one teacher, many students’. Who here has marked a set of assessments and there are x amount of students who have one knowledge error, x amount with another, one student missing due to illness etc and x amount ready to move on… what do you do? Technology, and AI, could be the solution to this problem.

But, there is also the bigger question of ‘what do we actually mean by personalised learning?’

3 examples that Daisy looks at:

1. Individual learning styles

2. Student choice

3. Adaptive learning

Individual learning styles is a theory that doesn’t just claim that we have a preferred style or a best style, it claims that if we are taught in our preferred style, we will learn better. And that is not the case. When we are learning, what matters most is not our preferred learning style, but the best learning style for the content. For example, if you want students to learn the locations of countries on a map of Africa, then a visual presentation of the material will be best. And this will be best for ALL students, regardless of their preference. Similarly, it can be useful for material to be presented in more than one way: this can be beneficial for more than one student. Eg why it’s important to combine words and images. Another issue with ‘learning styles’ is that they can enforce stereotypes. Eg if a child prefers watching to reading, they will only choose this learning style and then never get any better at reading. Therefore,  rather than providing students with instruction exclusively in the style that appeals to them, we should be looking at the specifics of the content and the research-backed principles about how we manage information. So AI platforms that adapt to the learning preferences of students, can limit the students ability to actually learn, we as teachers with pedagogical knowledge need to select the appropriate tasks and technology.

Student choice or a ‘self paced environment’ can be viewed as a way to stop students getting bored or lost by the pace. However, the research literature shows that learners are not well equipped to make good decisions about their learning, precisely because they are still learning. Similar to the expert/novice example; to be able to make good decisions about our own competence in a particular area, we need to already possess a degree of competence in that area. (the Dunning-Kruger effect). Equally, we may feel that repeating an easy task over and over is boring, and not helping, but sometimes ‘overlearning’ can be valuable as it builds fluency (and reduces cognitive load). We can also struggle when learning something for the first time and think this is a sign to slow down or stop, but that’s also not necessarily right as is shown by Bjorks ‘Desirable difficulties’. Therefore, students, especially ’novice’ should be guided in their learning choices until they can make good choices.Once again, AI platforms that encourage student choice are only appropriate once students are already ‘experts’.

Adaptive learning or adaptive systems will change questions based on how students answer questions etc. They also provide students with hints and tips in the same way a teacher might. As prior knowledge is key for students and students are not always able to fully access their learning goals, personalised data is needed to help teachers and students make better decisions about what each student needs. These adaptive systems will change based on this data in real time as students are using them. These systems are capable of providing different pathways through content for every student. The evidence in favour of such programmes is fairly positive, although not completely consistent, the impact is always positive (but the size of impact varies). Therefore this is the ‘best’ form of personalised learning, and one that AI can support. So with this, the question is more around, how should this be used? Should it replace classroom instruction completely, be integrated with classroom instruction, or only used as a separate homework programme. I think COVID has taught us that we cannot simply remove the interactive or social element of physically being in the classroom, however, this is where AI could really enhance, and level up, education.

Workload 

The million pound question; ‘how can we reduce teacher workload? There are many ways that AI and ChatGPT have the potential to reduce teacher workload.

One such way is through automating administrative tasks. For example, letters and emails. As report writing is still a heavily debated one, I’m not going to suggest that (this is for individual schools to decide under the Government GDPR guidance). But by automating other time-consuming tasks, teachers can focus more on the right instructional activities and building student engagement.

ChatGPT can allow teachers to effectively create personalised learning experiences for their students, using their expert knowledge. For example, you can ask ChatGPT to create revision summaries or create scaffolds that would support the needs of specific students. It can even create quizzes with multiple choice answers. Again, teachers have the knowledge of their students’ individual needs and the most appropriate tasks, so this simply speeds up the way in which teachers tailor resources to them. 

Finally, lesson planning and resource recommendations. There are some new (and some free) AI platforms that can assist teachers in creating lesson plans by providing resources, suggesting relevant activities, and offering a wide range of teaching strategies. With our ‘expert’ knowledge of cognitive science, we can select the most appropriate ones, especially when suffering a bout of ‘teachers block’ when sitting down to a lesson plan.

Opportunities 

Out of this AI ‘enlightenment’ revolution, there are many exciting new opportunities and tools. What is important is to not forget the cognitive science when looking at them. Equally, remembering that there are a lot of new platforms that want to make money (which given how little money is in education, is a concern), so check out it’s free versions or demos beforehand to ensure that it is worth it too. 

1. ChatGPT prompts: One way we can reduce workload and start getting more familiar with applications like ChatGPT, is by asking it the right types of questions. On Twitter, there are lots of recommendations around ‘prompts’, one account which is particularly helpful is Zain Kahn (@heykahn). He also has a newsletter that you can sign up to called ‘Superhuman’. This gives frequent tips on prompts for ChatGPT and other AI platforms. It’s free to sign up too. 
2. Another useful and free tool for ‘prompts’ comes from Daniel Fitzpatrick: 40 Proven AI Prompts for Educators [THIRD EDITION] by Dan Fitzpatrick – Issuu  
3. Daniel Fitzpatrick is also the creator of of the website, ‘The AI educator’ and on here you can see lists of different platforms. You can also filter them and one filter includes ‘free’ or ‘freemium’. It’s important to note here that ChatGPT is listed as ‘freemium’ however, there is not really any need for Teachers to sign up to the paid version, we can do so much in the free one. Equally, D-ID who i referenced earlier is also ‘freemium’ but this is only a 14 day free trial, so not a very good ‘freemium’ unless you’ve got 14 days to just sit down and create. AI Educator Tools 
4. Teach Mate AI: This has been created by Mr P ICT, who you might recognise from social media. He often posts memes about education as well as giving lots of practical Teaching and Learning advice. This new platform has a suite of AI-powered tools capable of generating bespoke teaching resources and simplifying various elements of a teacher’s job. It does have tools that are free so you can get an idea of what TeachMateAi is capable of, but for full access, you need to sign up for a Pro account.TeachMateAi 
5. Study Hall AI: This is a platform I saw at the Epsom College Conference, it’s not free so I do not have extensive knowledge of it, but this really appealed to me as it is using AI to support reading and maths, and the feature ‘Deep reading’ enables students to build knowledge and most importantly, engage with the text they are reading. The tasks it is promoting are clearly rooted in cognitive science. Studyhall AI 

As well as these ‘newer’ platforms, Daisy Christodoulou also highlights several edtech platforms which were already embedding cognitive science to enhance student learning.

• Cerego: this is an adaptive platform which doesn’t come loaded with content, but instead allows teachers or groups of teachers to add or create their own content.
• Eedi (Diagnostic questions): this looks at thousands of student responses to questions to help teachers learn more about their students thinking
• Anki or Quizlet: these are flashcard apps to create your own flashcards
• Up Learn: this is an independent study programme designed for A-level students in certain subjects which has videos and quizzes linked to specific exam boards.
• Memrise and Duolingo: are both online language learning platforms

• Hegarty Maths: has videos and thousands of practice questions which replace and mark maths homework
• Smartick: is an adaptive maths programme designed to be used for 15mins a day (4-14 year olds)

Final provocations: 

Before rounding off the TeachMeet, I wanted to poll teachers on the first provocation as well as a new one.

Positively, no one thought it would replace teaching. With regards to the benefits, it was more split, but atleast only two felt that teaching would become more like ‘crowd control’. I think that as professionals it is fair to say that we are not fully there yet. There is a lot out there and so the time to find the right tools is still limited. However, it is good to see that some are excited about how much more creative we can now be in the classroom. 

Conclusions

Schools aren’t going anywhere, and neither are teachers. This is because:

1. Education is concerned with more fundamental skills and knowledge that are less likely to be overturned by technology. Self-driving cars may remove the need for driving instructors, but it’s hard to imagine a world that doesn’t need people who can read, write and do basic mathematics.

2. Skills which are economically valuable are dependent on knowledge skills. You won’t be getting a job based on your ability to recite the times tables, but this basic mathematical knowledge allows you to understand more complex ideas. The same is true of creativity and innovation. Think of recombination innovation we looked at in the last TeachMeet on Rebel Ideas, you need to have knowledge of two different concepts or ideas to create a new one.

3. And finally, schools should not be solely concerned with the economic value of students . We teach literature, not because it has direct economic benefit, but because it helps students understand the world. 

So schools just might look a little different in the next few years, and this could be amazing. We still need teachers to guide students in how they use technology and AI to ensure that they are still building memory, being inspired and encouraged to think creatively, and we need AI to help liberate teachers’ time, not to replace it.

References

Christodoulou, D. (2020). Teachers vs Tech?: The case for an ed tech revolution. Oxford University Press

Fenichell, S. (2022), StudyHallAI: https://studyhall.ai/ 

Fitzpatrick, D. (2023). 40 Proven AI Prompts for Educators [THIRD EDITION]:  ]https://issuu.com/theaieducator/docs/13_ways_chatgpt_can_reduce_teacher_workload_1_ 

Fitzpatrick, D. (2023) AI EDUCATOR TOOLS, Thirdbox LTD https://aieducator.tools/ 

Parkinson, L.(2023) a.k.a @ICT_Mr P TeachMateAI: https://teachmateai.com/ 
Seldon, A. AI in Education Conference (May, 2023), Epsom College: https://www.epsomcollege.org.uk/whats-on/ai-in-education/

This term, our Teach Meet was inspired by Matthew Syed’s most recent book ‘Rebel Ideas’, specifically the importance of being a Polymath and also why cognitive diversity is so important. Matthew Syed is a British journalist, author, broadcaster and former table tennis player (so quite the polymath himself). He has published several books including; Bounce, Black Box Thinking and Rebel Ideas: The Power of Diverse Thinking in 2019 (with some additions post-COVID). In brief, the book Rebel Ideas argues that diversity in thought and experience is essential for innovation and progress. He draws on examples from various fields, exploring the power of cognitive diversity and the ways in which it can be cultivated in organisations and society. He argues that by embracing difference and creating a culture of respect and safety, individuals and groups can overcome homophily (or echo chambers) and achieve greater success. 

The book opens by looking at 9/11 and what retrospectively looked like the failings of the CIA to spot the ‘glaringly obvious’ cues of what was to come. However, the issue wasn’t down to their failings to see what was in front of them, it was down to their failings to diversify the CIA, as since its inception, the CIA had been staffed by ‘white male Protestant elite’. – Collective blindness. The book then looks at what ‘cognitive diversity’ actually means. Cognitive diversity is different from ‘ethnic’ diversity. If you have a group of people from various ethnic backgrounds, who still all went to an Ivy League university, are not diverse in how they think. However, you could argue that their journeys to an Ivy League were very different, so perhaps this is over simplified. Syed’s point is that for cognitive diversity, we need to have a wide range of different thinkers, which is what the CIA was lacking. Its excuse was it only wanted ‘the best’, but this meant they only selected from the same pool. Thus, in the education sector, we need to ensure that there is more diversity in teacher recruitment, in 2021, 85.1% of all teachers in state-funded schools in England were white British, 3.8% of teachers were from the ‘white other’ ethnic group, the second highest percentage, 92.5% of headteachers were white British, 75.7% of teachers were women, and there were more female than male teachers in every ethnic group. The teaching profession is incredibly lacking in diversity, yet how diverse are our school communities? How are we going to reach every student?

Syed also points out that cognitive diversity has a time and a place. When it comes to simple tasks, diversity is a distraction. For example, if you are running a relay (simple task) you just want the best runners. But for complex tasks, such as policy, cognitive diversity is essential. For example, Sweden’s snow clearing policy in the 1970s focused primarily on clearing roads and car lanes, while pavements and bicycle lanes were left covered in snow and ice. Women, who tended to walk more than men and were more likely to be responsible for taking children to school and running errands, were disproportionately affected by this policy. These examples highlight the importance of considering diverse perspectives when deciding on complex policies. Thinking about this in education, it is why we are seeing even more emphasis (and rightly so) on the importance of staff/student/parent voice in individual schools. In the education sector, we are very much working on ‘complex’ tasks and so cognitive diversity is important. Yet, if we look at the past ten years of Secretaries of State for Education, where we have had ten different people, is there really much diversity in their experience or thought…?

This is very much a ‘whistle stop’ tour of the book, but it leads me onto the two main themes and chapters I wanted to focus on from Rebel Ideas: Innovation and Beyond Averages.

Innovation 

Syed looks at the two types of innovation, incremental and recombinant. 

1. Incremental innovation – James Dyson (vacuum) and the understanding of the cyclone systems with each new version.
2. Recombinant innovation – take two ideas (previously unrelated) and join them together e.g wheels and suitcases… Matt Ridley calls it ‘ideas having sex’.

Recombination needs diversity as it is bringing together different fields – rebel combinations. A study in 2017 revealed that 43% of companies in the Fortune 500 were founded or co-founded by immigrants or the children of immigrants. Another study found that around a quarter of all tech and engineering companies started in the US from 2006-2012 had at least one immigrant co-founder. So why is this? When immigrants see a tech company in a new country, they do not see it as something set in stone, but rather something that could be changed, reformed or adapted (this is called the ‘outsider mindset’). Immigrants also have experience of two different cultures (recombination innovation). Therefore they can be a lot more creative and able to think outside the box. Could we make parallels to the teaching profession and COVID-19 pandemic? Were teachers who tend to be more traditional in their teaching less able to adapt whereas those who were newer to the field, thus technically having an ‘outsider mindset’ more able to adapt? 

To have an ‘outsider mindset’ you do not just have to travel across borders, it is about interdisciplinary skills or being a polymath. Darwin alternated research between zoology, psychology, botany and geology which enhanced his creative potential as it gave him the opportunity to see his subject from the outside and fuse ideas from diverse branches of science. One study found that the most consistently original scientists switched topics, on average, a remarkable forty-three times. Think of the original philosophers, they were artists, mathematicians and scientists. When comparing the Nobel Prize winning scientist with other scientists from the same era, the nobel laureates were twice as likely to play a musical instrument, seven times more likely to draw, paint or sculpt, twelve times more likely to write poetry, plays or popular books and twenty two times more likely to perform at amateur acting, dancing or magic. Similar results were found for entrepreneurs and inventors. Therefore what we need is not necessarily to be ‘experts’ but to have ‘conceptual distance’, being deep and too focused in our areas of study limits us. We do still need inside expertise: we need conceptual natives and recombination immigrants working together. Ultimately, most institutions need specialists who in turn, need space to do their job. But we often get the balance wrong, leaning towards insularity and ‘expertise’, not because we don’t value the insights of people who think differently, but because we underestimate their significance, like the CIA did. Again, how many meetings have we been in when staff only want to work in their departments or don’t see how something applies to their subject?

Provocation one: Are teachers (and the education system) too focused on being ‘experts’? How can we inspire innovation in the classroom?

Firstly, one of the reasons why teachers perhaps focus ‘too much’ on being experts is down to the fact that the system we are in doesn’t favour the polymath. Exam specifications are bigger and more content heavy than ever since the 2016 reforms. As Syed points out, being an expert is important. For teachers, it allows them to have a deep understanding of their subject area, which in turn enables them to design and deliver effective lessons. At the same time, polymathic thinking is also valuable for teachers. Being a polymath can allow teachers to make connections between different fields of study and to bring a diverse range of perspectives to their teaching practice. Ultimately, being a successful teacher requires a combination of expertise and polymathic thinking. Teachers need to have a deep understanding of their subject area, but they also need to be able to think creatively and make connections across different fields of study. By incorporating both expertise and polymathic thinking into their teaching practice, teachers can create engaging and effective learning experiences for their students. Surely this is more meaningful for our students and their future skill set than teaching to the exam?

That being said, many subjects do naturally have interdisciplinary elements, such as Science and Modern Foreign Languages. Science is a multidisciplinary field that encompasses a wide range of subjects, including Mathematics, Physics, Chemistry, and Biology. It requires the ability to think critically, logically, and creatively, and to analyse and interpret data. Therefore studying science can help students develop problem-solving and analytical skills, which are essential for developing a polymathic mindset. MFL requires students to learn a new language and to gain an understanding of different cultures. This requires developing an open-minded and empathetic approach to communication and a willingness to learn and adapt to new ways of thinking and communicating. Studying MFL can help students develop a broader perspective on the world and an appreciation for different ways of life. Thus, science and MFL share many similarities in their approach to inquiry and investigation. Both subjects require an evidence-based approach and the ability to question assumptions and evaluate evidence. They both require creativity and adaptability to different contexts, and they both involve developing a deep understanding of complex systems. By studying science and MFL, students can develop a range of skills and knowledge that can help them become more well-rounded and adaptable individuals, capable of approaching problems from multiple perspectives and finding innovative solutions. This can help them become polymaths, with the ability to integrate different fields of knowledge and use their diverse skills and perspectives to make valuable contributions to society.

Finally, as teachers we can support and model being a polymath in our approach to teaching and learning. Lesson study is one such way. Lesson study is a collaborative process in which teachers work together to plan, observe, analyse, and refine a single lesson or unit of instruction. The goal of lesson study is to improve teaching and learning by focusing on the process of lesson design and delivery, rather than on individual teacher performance. This allows teachers to observe lessons from across departments and thus modelling being a polymath. Within our actual lessons, one idea to encourage this interdisciplinary thinking is by using starters of ‘what connects’ or dual coding to get students thinking in a recombinant way.

Beyond average 

So the next chapter I wanted to focus on was ‘Beyond Average’ which specifically looks at why ‘standardising’ anything (including education and policy) doesn’t work. One example it gives is the American airforce during the late 1940’s and their incredibly high crash rates. He discusses the issue with the design of aeroplane cockpits which is based on a ‘mythical average’. This is similar to some of the issues raised in the book; Invisible Women by Criado Perez, which talks more about the ‘tyranny of average’. For Example, piano keys were designed based on the average hand size of men as well as other things such as military equipment. Averages discriminate. Syed then looks at how we use ‘averages’ or ‘standardised’ concepts in other workplaces and how this impacts people’s creativity and success. 

Syed looked at the success of call centre employees, he found that those who used Chrome or Firefox were more productive, more successful, more likely to stay longer, less absences etc than those who use internet explorer or safari. But, why? Explorer or safari come as standard on a PC or Mac. To use Chrome or Firefox, you have to be curious enough to see if there are better options out there, you have to download and install them. Therefore these are the type of employees that don’t stick to scripts that call centres often provide for its employees, they think outside the box and problem solve. They don’t keep to the ‘standard’ script. This idea also applies to standardised work spaces. Syed compared standardised or ‘lean’ office spaces (this the same cubicle for all) to those who give people autonomy to create their own space. In these autonomous spaces productivity rose by 30% from the ‘lean’/standardised spaces. Furthermore, there is a correlation between job satisfaction and creativity: those who saw their roles as what they wanted them to be, rather than just a standardised job description that they must fulfil, were more successful and creative. This is why we cannot standardise the workforce. In fact the most important working requirement of Generation Y is flexibility and work life balance. So, if we know the work force we are setting our students up for shouldn’t be standardised, why do we continue to standardise education? Especially when this is potentially so detrimental and not preparing students for the workforce?

Continuing to look at this from an educational perspective, the 2015 PISA tables showed that ‘adaptive instruction’ was the second most powerful predictor of high levels of educational outcome, rating above discipline, class size and much more.  The only thing more powerful was wealth. Adaptive instruction is teachers who adapt to the needs of individual students rather than getting everyone to do the same thing, at the same pace, at the same time. What we should be working towards is an education system that flexes to the needs of individual learners, yet we are told to crowbar individuals into a standardised system. We give students very little autonomy over their learning experiences. We ask them to take standardised tests when they arrive at school and continue to use these as measures of their progress. They will then all sit the same test at the end of Year 11 and Year 13, which is standardised by an external exam board. Do these exams allow students to be creative and to be polymaths? Think about the EBacc which gives superiority to certain, and not traditionally creative, subjects. 

Provocation two: Do standardised tests still have a place in education? What do they actually tell us?

Some staff who have recently been on exam board training reported that change is coming, however, what this is and what it will look like is unknown. However, with our first summer of ‘normal’ exams since COVID just around the corner and the more recent ‘tech revolution’ in the form of Chat GPT, let’s hope the appetite for change in how we assess students continues. 

Another interesting point is that there appears to be an increase in applications to American Universities. The American higher education system has a long-standing tradition of liberal arts education, which emphasises a broad-based education in the humanities, social sciences, and natural sciences. This approach is different from the more specialised degree programs that are common in the UK and many other countries. For context, there were over a million international students studying in the United States in the 2019/20 academic year. This is compared to 690,923 ten years earlier. 

This then led us to consider whether we think our students would rather be polymaths or experts? As, although we may know the benefits of being a polymath, what if that does not resonate with our students? Unfortunately, the feeling is that a lot of our students are still pressurised by the ‘perception’ of certain routes in education. Again, the precedence of EBACC in the state sector and the reputation of Oxbridge and Russell group universities continues to push a very narrow narrative of what education and ultimately, what intelligence looks like. Coming back to ‘cognitive diversity’ and the importance of breadth of knowledge, not just depth of knowledge, we can see that standardising anything encourages a specific ‘blinkered’ knowledge that is not broad and this in turn does not support creativity or innovation. Which certainly seems to be an issue in our current education system.

Conclusions

To finish on a more positive note, Syed ultimately asks ‘why are humans so successful?’ We may be inclined to think ‘big brains lead to big ideas’ but the reality is that it’s more like ‘big ideas lead to big brains’. Diversity (and being social) is the hidden gem of humanity and perhaps natural selection will start to favour good learners. The reason only humans evolved is we are social. In groups such as Chimpanzees, they have one dominant male and a few females, this dominance ‘stops creativity’. In orangutans, they are isolated creatures. Therefore, innovation dies with them. It is not that they are ‘less intelligent’, they are just collectively less intelligent. Humans are not different from animals because of our hardwear (genetics) but because of our collective brains.

So what practical advice can we take from Syed on how we can harness diversity?

1. Unconscious bias: We need to do what we can to address and be aware of our unconscious bias. 

This isn’t ‘easy’ as it is unconscious, however if left unchecked, this becomes structural bias and is dangerous. Syed looks at how orchestras introduced recruiting with a screen, so they could hear the music and not see the candidate. When this was introduced, female players increased from 5% to 40%

A university study looked at CVS. When a black candidate was clearly better than a white one, they would choose the black candidate. And vice-versa. However, when the applications were close, that is when unconscious bias crept in and students showed a preference for white candidates.

Unconscious bias becomes structural bias: those who are less likely to be selected have to work even harder, and the incentive to work harder is not there. As educators, we need to empower our students to feel that they can break through any barriers that structural bias brings as well as being empowered to recognise and challenge bias. 

Interestingly, in the GDST ‘The Girls’ Futures Report 2022,  it looks at how girls’ confidence dips in teenage years, some of this is down to biological changes but some of this is also down to the structural bias of society and how it specifically ‘nurtures’ girls. Yet, in the GDST context, our girls do not feel held back compared to those in co-ed and their confidence is similar to boys in co-ed schools. So although this is a less diverse environment in terms of sex, the positive impact of these environments is that the educators who work in this context are working even harder to ensure that their students do not feel that conscious or structural bias is going to negatively impact their futures.  

2. Shadow boards: young people who advise executives on key decisions and strategies. These typically consist of a group of the most able young people, drawn from across an organisation (therefore with a variety of experience/expertise), who have regular input into high level decision making. 

Again, we could use this as a way of practising student/staff and parent voice – ensuring that we are getting insight from a range of our stakeholders with a variety of lived experiences.

3. A giving attitude: in a study of 600 medical students, they looked at the success of the givers vs the takers. In the first year, where their practice was very individual, the takers outperformed the givers. However, in the second year, where their placements were more collaborative, the givers caught up to the takers. By the third and fourth year, the givers were outperforming the takers significantly. 

As educators, I think we are by nature, really giving. This is something that we should continue to role model to our students and society. 

So in a very simple conclusion; embrace diversity and challenge bias, embrace the polymaths and challenge the ‘experts’, embrace being social and challenge the echo chambers. We can learn a lot, we can achieve a lot.

References

Matthew Syed, Rebel Ideas: The power of diverse thinking, 2019

The Girls’ Futures Report 2022 

School teacher workforce – GOV.UK Ethnicity facts and figures 

International students in the U.S. 2022 | Statista

If a career change from Teacher to Instagram Influencer is why you’ve landed here, I’m afraid this blog isn’t for you. However, if you want to know what more you can do to get the best for all of your students, then read on… For our first Teach Meet of the academic year we looked at the Pygmalion Effect. The Pygmalion Effect, or Rosenthal effect, is a psychological occurrence in which high expectations lead to improved performance in a given area. The effect is named after the Greek myth of Pygmalion, the sculptor who fell so much in love with the perfectly beautiful statue he created that the statue came to life.

Pygmalion Research in the Classroom

The original research of Rosenthal and Jacobsen focused on an experiment at an elementary school where students took intelligence pre-tests. Rosenthal and Jacobsen then informed the teachers of the names of twenty percent of the students in the school who were showing “unusual potential for intellectual growth” and would bloom academically within the year. Unknown to the teachers, these students were selected randomly with no relation to the initial test. At the end of the study, students were given the same IQ test. While all students performed better the second time, Rosenthal and Jacobsen found that those students who had been labelled ‘intellectual bloomers’ had improved to a greater degree than the other students. From this, they concluded that teachers expecting enhanced performance from students can actually lead to enhanced performance. Therefore, if we as teachers have belief that our students will do well, this almost becomes a self-fulfilling prophecy. 

In our Teach Meet last term, guest speaker James Nottingham showed us some of the research from Hattie’s ‘Visible Learning’ which showed that Pygmalion interventions can lead to an impact of 1.46 (which is almost an additional grade and a half of progress), hence why this seemed like something worth investigating. Interestingly, when researching this, I also came across the opposite to the Pygmalion Effect, which is called ‘The Golem effect’. In this model, where lower expectations are placed upon individuals either by teachers or the individual themselves, this will lead to poorer performance by the individual. As James Rhem puts it; “If you think your students can’t achieve very much, are not too bright, you may be inclined to teach simple stuff, do lots of drills, read from your notes, give simple assignments calling for simplistic answers”. 

Labelling Theory and self-fulfilling prophecy

Researching this further, inevitably led me to come across similar research on labelling theory and ‘self-fulfilling prophecy’. Labelling is simply the process of defining a person or group in a ‘streamlined’ way. For example, labelling involves that first judgement you make about someone, often based on first-impressions. When applied to teaching, this is where teachers actively judge their pupils over a period of time, making judgments based on their behaviour in class, attitude to learning, previous school reports and interactions with them and their parents, and they eventually classifying their students according to whether they are ‘high’ or ‘low’ ability, ‘hard working’ or ‘lazy’, ‘naughty’ or ‘well-behaved’, ‘in need of support’ or ‘capable of just getting on with it’, to name just a few categories. It’s worth noting here that a number of small-scale research studies of teacher labelling.  The labels teachers give to students are sometimes based not on their behaviour but on a number of other preconceived ‘stereotypes’ and ideas teachers have (e.g. ethnicity, gender or social class background) therefore labelling can be said to be grounded in stereotypes; something to be aware of.

A concept similar to labelling theory is that of the self-fulfilling prophecy; where an individual accepts their label and the label becomes true. For example, a student labelled as ‘naughty’ actually becomes ‘naughty’ as a response to having such a label. Again, if we flip this on its head, as we saw in the Pygmalion study, if we use positive or aspirational labels, then our students will achieve this. This is illustrated by the flow chart above. Thus if a student is labelled a success, they will succeed, if they are labelled a failure, they will fail.  

The reasons for this are as follows:

• Teachers will push students they think are brighter harder, and not expect as much from students they have labelled as less-able.
• A positive label is more likely to result in a good student being put into a higher band, and vice versa for a student pre-judged to be less able.
• Positively labelled students are more likely to develop a positive attitude towards studying, those negatively labelled will develop a negative attitude towards studying.
• The above may be reinforced by the peer-groups they socialise with as well.

However, one significant caveat to this is the fact that schools themselves often encourage teachers to label students. For example, entry tests, over which teachers have no control, pre-label students into ability groups anyway, and the school will require the teacher to demonstrate that they are providing ‘extra support’ for the ‘low ability’ students and that they are providing challenges for those who score highly in these tests. There are measurements such as ‘flight paths’ since the removal of levels and of course, we have students with very specific SEND profiles, which are not labels but can still create a label.

Are all labels bad?

Our first ‘provocation’ was ‘Are all labels bad’. As the reality is, whether intentional or not, they do happen. From this, a few specific themes appeared. Firstly we looked at the concept of setting. This is always a topical debate and one that comes up quite frequently, in fact this was something we discussed in our first ever Teach Meet on Crehan’s  ‘Cleverlands’ which examines best practice from top performing educational systems around the world. In 1963 Finland moved away from a two tiered system that divided students from 10 years old. Instead, students choose an academic or vocational route at 15-16 years meaning that all students had the same education for 9 years rather than 4. This is supported through evidence which suggests that countries who select later reduce inequality in secondary school and those from disadvantaged backgrounds do better. In fact, the evidence from Hanushek and Woessmann shows that there was no negative effect of late selection on any group, even the brightest 5%, which resonates with the Pygmalion Effect. Furthermore, there is much evidence to suggest that in mixed ability groups, those who are ‘weaker’ are pulled up by those who are ‘brighter’ and those who are ‘brighter’ deepen their understanding by supporting the ‘weaker’ student. 

Not surprisingly, the discussion on labelling also led to discussions on differentiation. Again, this echoes other elements of ‘Cleverlands’, when looking at practice in China. In China they have very much adopted a Growth Mindset and the Confucian way of thinking: “Learning does not privilege anyone, and neither does it discriminate against anyone. Everyone is capable of seeking and achieving knowledge regardless of one’s inborn capability and social circumstances.” In the book, Crenhan was talking to a Chinese teacher who had visited the UK and thought it odd how students are given different levels of maths problems, explaining that those with ‘easy’ maths will never keep up. If we want them to believe that everyone can achieve mastery knowledge, shouldn’t we start from the top and support all in getting there? Again, this would be adopting a Pygmailon approach. Following on from this, we then discussed aspirational and predicted grades. At Northwood, we make ‘aspirational’ predictions, this is what they should be striving to achieve. The rationale is that alongside wanting students to know how they are currently doing (a Current Performance Grade), we want them to know that we know their current attainment is just one piece of a much bigger picture, and that most importantly, we believe that they can achieve higher than this. What is also important about this, is that it is not a predicted grade. This links well with the Pygmalion Effect and also still means that students have an idea of where they are and where they should be aiming. 

After this, we spent some time discussing students with SEND profiles. It was felt unanimously that a student having a SEND profile in no way labels them, however, the bigger caveat to this is how well trained staff are on the needs and breadths of needs of students with SEND profiles. For example, a student with ADHD may get labelled as ‘unable to focus’ but the reality is that ADHD can actually allow students to be hyper-focused on specific areas of interest. Our fantastic SENDCo highlighted that there is a general movement in the SEN community towards a broader view of diagnoses and more awareness of the comorbidity of many current labels, for example where a pupil may present with Dyslexia and Autism. This then led to the final area of discussion; staff narrative. Staff narrative can be a powerful force, both positively and negatively. I was reading the book ‘Personal and Authentic’ before the summer, which talks about the author’s journey as a teacher. In one of the first chapters, he recalls trying everything he could with a student and feeling like it was getting him nowhere. His mentor overhears him having a gripe about this student in the staffroom and afterwards pulls him up on this. The extract is as follows:

“Tom, what did I tell you before that first day?” Mark asked. Without waiting for me to respond, he continued, “This work is all about relationships. This work is about loving and caring about kids. Without it, you have nothing. And right now, with this student, it looks like you have nothing… Instead of yelling at him, what if you encouraged him the moment you saw something positive? Instead of calling home for being in trouble, what if you called home for something great? When do you think he last heard a compliment? When’s the last time you think mom received a positive call home? If you want to get through to him, Tom, maybe it’s you who needs to change.” 

What a powerful message! This further highlights the importance of having a Pygmalion approach and avoiding a Golem narrative, and the fact that this is a responsibility that we as teachers must take. 

Should we use praise? 

After these discussions, I think it’s fair to say that we can see the merit in having high expectations and high aspirations for all of our students. So the next concept I wanted to consider was how do we let our students know we have high expectations of them and have a Pygmalion approach? When I think about how I try to validate students and want them to know I believe in them, I will often use praise as well as motivational talk. But the type of praise is crucial. 

Dweck spoke about how teachers try to counter stereotypes and build confidence in girls, we often heap intelligence praise on them. But this is counter productive as they then become less confident and scared of failure, as the value is now on their intelligence. “My great concern is that in our attempt to counter these stereotypes and build girls’ confidence in their intellectual abilities, we now heap intelligence praise on them”. (Dweck, 2000) This is the danger of intelligence praise on any student. Dweck has always emphasised the importance of ‘Praise process not qualities’ As this tells them what they need to do whereas praise on intelligence or innate qualities is detrimental as it makes them scared about getting things wrong. It also gives them a label that they are scared of losing. E.g. no more ‘clever … or talented’ but rather ‘I really like the way you…’ or ‘I can see you’re working hard to solve that…’

Most interestingly, and what builds to our next provocation is that Dweck also says no praise is better than praising innate qualities and that teachers should actually ‘ramp down’ praise so that children aren’t constantly looking over their shoulder wanting praise, so they end up enjoying the actual learning experience etc. The other reality is that students do like the ‘bad praise’, they like when people call them intelligent, but this isn’t good for them. It’s a quick hit, it impacts confidence and means they develop bad habits. The other impact of this is that when you need to give constructive feedback, students cannot deal with it as it impacts their self-esteem, which in turn, will limit their progress. For example, in a sports context, if we label a student as talented at football and then need to give feedback, any challenge to this innate talent is too much. When we should be able to say ‘in the second half you could have done X’, but rather (most often parents) will say ‘you were robbed’ and put blame onto something else (such as the referee), to avoid hurting their feelings. 

So my question here is, should we use praise? Especially if we end up praising labels. How can we combine praise and the Pygmalion Effect? Once again, this had me reflecting back on Cleverlands as China’s focus on praise and effort was very humbling. Yet in China, failure is not an issue, what matters is that you tried and that you learn from it. China’s graduation encouragement cards read ‘congratulations on your hard work’ and focus on self-improvement, rather than selecting students who simply ‘excel’ at a subject. If we adopt the Confucian way, we know that effort and persistent effort will lead to success. So as teachers we should praise the effort and process, not the outcome. By having this dialogue with our students we can motivate them in the process and ensure that they know their value does not simply come from their outcome. What is important here is also the equity of praise. If we are praising the process of our students, we need to make sure we do this for all students. Once again, pygmalion shines through, we must have high expectations of all of our students, and we must be transparent in showing this to all of our students. 

Practical tips

Finally, I wanted to end our Teach Meet on some practical steps. I genuinely believe that we all have a positive view of our students and want them all to achieve, therefore having a few ‘bitesize’ reminders of what this can look like, is a positive way to finish. 

• It is important that we treat our class with the notion that each student is capable of learning and improving.
• Always communicate high but realistic expectations of our students.
• Never forecast failure in the classroom. If you know a test is particularly difficult, tell your students that the test is difficult but that you are sure that they will do well if they work hard to prepare.
• Establish high expectations. Students achieve more when teachers have higher expectations. When you give students a difficult assessment, tell them, “I know you can do this.” If you genuinely believe that your students cannot perform the assessment, postpone the assessment and re-teach the material.
• Do not participate in gripe sessions about students. Teachers who gripe about students are establishing a culture of failure for their students, their department and their own teaching.

The impact of a pygmalion approach is significant and we can see the evidence through this not only in Hattie’s ‘Visible Learning’ but also in various educational systems around the world. 

Sources:

Crehan, Lucy. Cleverlands: The Secrets Behind the Success of the World’s Education Superpowers. 2016

Dweck, Carol.  Self Theories: Their role in motivation, personality and development. 2000

Loftus, Yolande. ‘Dyslexia and Autism: Is there a Connection? Feb 17 2022, Autism Parenting Magazine

McLeod, Susan. “Pygmalion or Golem? Teacher Affect and Efficacy.” College Composition and Communication 46 (3): 369-386.

Murray, Thomas C. Personal & Authentic: Designing Learning Experiences That Impact a Lifetime. 2019 

Rhem, James. “Pygmalion in the classroom” NTLF 8 (2): 1-4.

Rosenthal, R, and L. Jacobsen. Pygmalion in the classroom: teacher expectation and pupils’ intellectual development. New York: Holt, Rinehart and Winston, 1968.

Rosenthal, R., and E. Y. Babad. 1985. Pygmalion in the gymnasium. Educational Leadership 43 (1): 36–39.

For the final Teach Meet of the academic year, we ended on a high, by welcoming James Nottingham as our guest speaker. I first came to know James’ work back in 2011 when I started my teacher training. The Learning Pit was used by one of the first schools I worked in, but this is only one of the many impactful initiatives that James Nottingham has been involved in. We are probably all familiar with P4C and in 1999, Nottingham appeared in a TV documentary about Philosophy for Children (P4C), which led him to being invited to set up a social regeneration project in North East England. This multi-million-pound initiative won many prestigious awards for strengthening young people’s lives, including “helping young people to become clearer, more accurate, less self-contradictory and more aware of other arguments and values before reaching a conclusion.” Skills which are still incredibly important today. In 2006, Nottingham co-founded Challenging Learning, an independent consultancy to share the best practices with a wider audience. This company is now supporting education on every continent (except Antarctica!). In a business sense, Nottingham continues as the CEO of the company; in education terms, he is the principal keynote speaker, author and innovator. And I was actually fortunate enough to see James when he was touring as a keynote speaker with Carol Dweck in 2019. That CPD sticks with me to this day and not simply because I got a selfie with Dweck, but actually because it was James’ session that has had the biggest impact on my teaching. I’ve also used this to not only blog about, but showcased key messages to our staff soon after and still use the practical advice given by Nottingham in our new staff training sessions at Northwood. 

What is a Growth Mindset?

Essentially, this comes down to how we make sense of success and failure. A fixed mindset is the belief that our intelligence is fixed ‘no matter how hard I try, I will only ever be able to do X’ and a growth mindset is the belief that our intelligence can be developed, ‘if I work hard, practice and keep trying, I will be able to achieve Y’. 

One of the ‘growth mindset’ myths that came out of Carol Dweck’s research was the idea that we are one or the other. In reality, we are constantly fluctuating in our mindset which is why it is better to recognise when we are ‘in’ a fixed mindset or ‘in’ a growth mindset. But, if you look at the characteristics of a growth mindset above, you’ve got to think that growth mindset is worth it. Imagine how much further we could go in education if we could consistently be in a growth mindset.

Growth Mindset and girls

Interestingly, the research suggests that girls are in fact more prone to getting into a ‘fixed mindset’ than boys are. Nottingham does acknowledge that this isn’t the biggest piece of research, and that there are multiple factors such as circumstances, upbringing and actually the biggest impact on students is parents’ perception and how they respond to failure. But from this research, it does suggest that girls are more likely to get into a fixed mindset. This research was conducted by S.J. Ceci and W. Williams (2006), this study gave students challenging tasks to solve: “We found that bright girls didn’t cope at all well with confusion. In fact, the higher the girl’s IQ, the worse she did. This didn’t happen to boys. For them, the higher their IQ, the better they learned. The confusion only energized them… What we’re looking at here isn’t a difference in ability, but a difference in how students cope with experiences that may call their ability into question. If they exhibit a fixed mindset, then they are more likely to be demoralised by challenges.” Nottingham suggests that this is because if a girl has a high IQ, they have been told that they are ‘brilliant and intelligent’, therefore, finding something challenging puts this reputation on the line and the fear of no longer being considered intelligent. 

Growth mindset and attainment?

Once again, the evidence would suggest that helping students get into a growth mindset is incredibly positive for their learning and also their attainment. However, at the moment, there are only two meta-analyses of growth mindset. Jeni Burnette et al, 2013 included 85 studies, so is fairly well researched, but only found an ‘effect size of 0.19 and Yeager et al (2019) found the effect size to be even smaller at 0.11 which, when compared to the typical effect size of any intervention at school of 0.40 it means that growth mindset interventions are pretty low level compared to others. 

This analysis comes from Visible Learning Plus, where John Hattie has pulled together all the meta-analyses of the studies he has examined. Here you can see that growth mindset interventions have a relatively low effect on student outcomes. 

The list on the right of the diagram shows all of the studies that Nottingham offers training on through his consultancy. As you can see, everything that they offer training on has an above average impact on student success. Most impressive here is the Pygmalion effect which can improve student attainment by 1.46, there is also formative feedback at 0.92. So why then is Nottingham such an advocate for growth mindset when its effect size is only 0.11?

Dylan Wiliam, most notably known for his book ‘Assessment for Learning’, argues the case that small, well-established effects, such as growth mindset are meaningful given that this type of intervention typically takes less than an hour, therefore even just 0.08 effect size would be an increase in the rate of learning of at least 20%. So as far as a simple one hour intervention goes, this is worth doing. He then goes on to say that ‘Growth mindset is a means to an end, not an end in itself, as it makes learners more receptive to feedback, and feedback (formative), as shown above, can have an effect size of 0.92. 

Is a Growth Mindset worth it?

This is where it comes down to us as professionals and whether we think the characteristics of being in a growth mindset is worth it. Do we want our students to seek challenges, examine mistakes and see them as opportunities? Do we want our students to see feedback as advice, and believe that their abilities can be developed over time?

Is it worth it? Like meta-cognition, you’ve got to actually apply it. If it becomes just a buzzword: ‘today we are doing Growth Mindset’. Therefore it is worth doing, but it’s about embedding it in a way that we as teachers create tasks that promote opportunities for developing a growth mindset.

For me, these are attributes that I want to encourage, as well as assuring my students that they will succeed. This is why, one of the key takeaways I took from Carol Dweck and James Nottingham back in 2019 was the idea that ‘We should never test… once!’ In fact we should test twice as much. Controversial, I know, but again the rationale makes so much sense when it comes to embedding a growth mindset. If we as teachers tell our students, “you have an end of unit test and this test is going to be recorded, sent home to parents and even determine your predicted grades, you have one week to revise”… students who value our subject will panic and spend that week fretting and revising none stop, those who do not, will do nothing and say that is why they won’t do well. However, for both types of students, we are telling them to have a fixed mindset of themselves. Rather, we should ‘surprise’ them, let them know it is low stakes and that this test is to help them identify their strengths and weaknesses, so that they can revise for the real thing more effectively. Then, when they take the ‘real’ test, they will have made progress and most importantly, they will see that progress. Thus, their mindset will be more set for growth. 3 years on and I can really see this in my students, they know that it’s just another test and that they always have another opportunity. From a performance standpoint, my data sheets in which I use conditional formatting, is a very visual way for me to see that ‘yes, they are making progress’. 

Nottingham also highlights how parents’ attitudes have the biggest impact on mindset, so we need to show parents that we also take a positive attitude towards failure too. But what about those who may never be able to do something, how do we manage that expectation? Especially for parents? This is where Nottingham talks about the importance of us as teachers setting appropriate targets. For example, flying. I am never going to be able to fly, without some sort of contraption to help. So don’t set a target of ‘learn to fly’ with the messaging of ‘you just can’t fly yet.’ The ‘yet’ only works well when it is in conjunction with expectations that are possible, but that there is also a clear roadmap of how we are going to get there. Strategy is important, so we as teachers can sit down with students and parents to explain how they can get to where is possible. 

Will your context be helped by Growth Mindset interventions?

Controversially, Nottinghams’ conclusion here is that no, growth mindset interventions will not help us in the context in which we work. This is down to the fact that we are all having to fulfil curriculum demands and exam specifications in a very short period of time. So to really unpick why this is, Nottingham gives two very different school focuses. These are two polarised examples, and he acknowledges that most schools will have elements from both sides, but that one side will definitely resonate with your school more than the other.

Performance Focus	Learning Focus
Grades are referred to frequently Will it be on the test? Is my child doing well? Prospectus emphasises grade success Avoid mistakes & failure Efficiency Get the points Beat others Prove Note taking Hide mistakes Summative feedback Finish it!	Grades are secondary to engagement What connections can I make to this? Is my child thriving? Prospectus emphasises experience Examine mistakes & failure Depth Get the point Personal bests Improve Questioning Examine mistakes Formative feedback Explore it!

If the elements of performance focus are more true to you and your context, then ‘growth mindset’ is not for you. But if more elements of learning focus are true to you and your context, then ‘growth mindset’ is for you. Equally, if you recognise that you are too much on the performance focus and want to move to a learning focus, then you should embrace growth mindset interventions as a way to get there, however there will be resistance along the way. I think it is fair to say that there are elements of both sides which are necessary in our context, but that for us, the learning focus is certainly the most important. 

A really interesting example Nottingham gave was on funding for reforestation and how this initiative has got it wrong. This currently works by funding being given for each tree that is planted, however this should be shifted to funding that is given to every tree that is flourishing 7 years later. This is because it is relatively easy to plant a tree, however to keep it thriving and to keep it alive, is a much bigger commitment and investment. This should be the approach of schooling too. It is relatively ‘easy’ to teach students the exam and how to ‘play the system’ of exams, but the question should be, how well are they thriving 3 or 4 years after they have left school? This is why a learning focus approach is more meaningful when considering the long term development of our students as opposed to the instant exam results, which we are inevitably measured against. 

Conclusions

From this session, it felt clear that ‘growth mindset’ is worth it. Yes, on paper, it doesn’t appear to give the same ‘gains’ that other interventions might. However, it is not just an intervention, it is a pedagogy and a way of framing how we approach education. If we can use ‘growth mindset’ as a bedrock that underpins other aspects of teaching, then perhaps that will have the most impact. For Nottingham, this is why his latest book is called ‘Challenging Mindset’, growth mindset is not perhaps what we have thought it was in the past and lots of educationalists have got it wrong. Surface level interpretations of growth mindset do not go far enough. Having a ‘Growth Mindset’ display in the back of a classroom whilst simultaneously having a performance focused classroom is not going to add value to your students, your lesson or your school. Furthermore, misinterpretations of what growth mindset is doesn’t help either, for example, ‘try harder’ is not encouraging a growth mindset, what is important is supporting students in knowing what actual strategies they should try or need to adapt before they are able to try harder. Finally, in a performance focused environment, mindset doesn’t matter. But in a learning focused environment, mindset does matter. Mindset matters most in times of challenge, if things are easy then mindset doesn’t matter that much. These interventions will help us when we are struggling, that’s when mindset matters. And let’s face it, in the world of work, our students will be facing challenges and they will need the strategies to overcome them. For most, there will be no high stakes exams past A Levels or University, so only having ‘success’ at these levels as the goal, will not allow them success beyond. Perhaps this is why businesses and tech companies are heavily investing in ‘growth mindset’ professional development for their employees. This is why the quote “the one who plants trees, knowing that he or she will never sit in their shade, has at least started to understand the meaning of life” by Rabindranath Tagore resonates so much. As educators, we may never see the full impact of ‘growth mindset’ interventions on our students whilst we teach them, but we know that by embracing them, we will have equipped them for the future. 

References

James Nottingham, (2018) Challenging Mindset: Why a Growth Mindset Makes a Difference in Learning – and What to Do When It Doesn’t

S.J. Ceci & W. Williams (2006), Why aren’t more women in science?

Jeni Burnette et al, (2013) Mind-sets matter: a meta-analytic review of implicit theories and self-regulation

Yeager et al (2019), A national experiment reveals where a growth mindset improves achievement