The best form of feedback is more teaching

‘Feedback’ is used to describe the high-pitched whine that emanates from a speaker when the audio waves are picked up by a microphone, or other audio-input device, and amplified back through the speaker in a continuous, building, loop. It is piercing, irritating and unwelcome.

This form of feedback is a useful metaphor for another meaning of the term; the act of providing students with guidance on how to improve. Regurgitated and amplified through misguided school policies and CPD sessions, feedback has become a cacophonous racket which threatens to drown out the everyday melody of teaching and learning.

The term feedback was coined by Norbert Wiener during the Second World War to mean where the outputs of a system are routed back as inputs, creating a virtuous circuit or loop that leads to improvements in the system. Despite the aim being to achieve a ‘desired state’ where the system works effectively, the corrective feedback itself was described by Wiener as ‘negative’ as the output indicated error or insufficiency.

“Negative feedback loops minimize differences between the current situation and the desired situation by feeding the outcome of an action back into the system. Any discrepancy between the outcome and the desired situation leads to a corrective action whose intent is to reduce the gap.” Wiener

In teaching, the act of correcting students obviously predated Wiener’s work. However, the field of Cybernetics, developed by Wiener and his contemporaries, subsequently influenced how we thought about dynamic, complex systems in industry, society and education.

The concept of negative feedback (identifying the error in an output and routing this back in to the system to reach the desired state) has taken hold in education and in many schools has become the most elevated aspect of the teaching process. We have placed increasing importance on examining the output of a sequence of lessons (i.e. the students’ work) to assess where it is deficient against out ‘desired state’. Corrective information is fed back in an attempt to create a virtuous cycle of improvement.

As the feedback frenzy took hold, the hours spent by teachers looping through this endless cycle amplified until we reached the current workload crisis.

[As an aside, you can see a similar slavish commitment to the feedback loop, over a longer time-period, with the regular data-collection and intervention cycles which have also driven up workload for teachers – “that student is two grades below target; there is an error in the system!”]

But I believe there is a fatal flaw in our application of Wiener’s ideas. It derives from what is often identified as the ‘desired state’ and how the negative feedback is routed back in to the system.

When we examine a piece of student’s work we seek to identify how it falls short of the piece of work we would really like to see. The model we hold in our minds (the ‘desired state’) enables us to identify the errors and feed these back. This feedback goes to the student, after all it is their work we are marking and if they know how the work is deficient they will be able to move it towards the desired state.

What we are forgetting is that the piece of work is the output of a sequence of learning, not the output of the process the student went through to create the piece of work. If the output falls short of the desired state, the fault might be at any point along the learning process. Why would the power to correct this shortfall lie solely in the hands of the student? If this were true, we would not have designed, delivered and guided students through the sequence of learning in the first place. We would have left them to get on with it.

This error arises when we see the student’s work as a product of their ‘skill’ and not as the outcome of the knowledge which they have, or have not, acquired through the learning process. We provide feedback to the student such as ‘add more detail to your explanation’ or ‘analyse the causes of this’, as if the problem lies with the fact that they’ve just forgotten that that is what they should do. The problem is that they haven’t acquired sufficient knowledge to produce the work. The ‘desired state’ is not the model piece of work we hold in mind, it is the schema of knowledge we want the student to acquire which enables them to produce the piece of work.

Remember that Wiener advocated feeding information about deficiencies back in to the system to close the gap between the actual and the desired state. In this case, the system is teaching and learning (not the production of the final piece of work by the student). The deficiencies in students’ work should therefore inform the teaching process; the system which produced the outcomes.

This interpretation of Wiener’s concept of feedback, as applied to an educational setting, profoundly changes what we, as teachers, do with the information we glean from examining students’ work. Rather than turn this information into feedback to the students themselves, we should use this data to inform our teaching.

In other words, we interpret insufficiency in students’ work as an imperfection in the learning process we designed and delivered, rather than a deficiency in the student.

This re-thinking of the feedback loop brings benefits over current practice:

  1. We stop the hours spent providing personalised, negative feedback to each student.
  2. The error-information informs the most powerful part of the process; the teaching.
  3. Teachers begin to see error as a result of the teaching and learning process rather than as a symptom of inadequacies in the student.

If we are to reduce the gap between what students know and what we would have them know, our energies should be directed at refining the teaching process following our assessments of students, rather than waste time telling the student what they did wrong.


Defective teaching

One of my university lecturers, a long time ago (in Brighton, so also in a galaxy far, far away), told a story which was probably apocryphal. None-the-less, it made the point. It went like this…

In the 1980s, a British company decided to start buying in components from Japan. They were very specific in the contract that they required 95% without defects. They were not going to accept any nonsense from these foreign suppliers.

When the goods arrived, exactly 5% of the components wouldn’t work properly. The company contacted the suppliers to point out that this was at the margin of what they would accept. The Japanese firm were confused. “But we gave you exactly what you asked for”, they protested. “If you wanted 100% without defects, why didn’t you say that?”

The lecture was on quality assurance. The story highlighted the strange practice in Western business culture of tolerating products coming off the production line with faults. These products would either be sent back for correction or, if they were beyond repair, thrown away. The Japanese, however, had stopped expecting defects and started building quality in to every stage of production. Why allow a system which produces waste?

In Western teaching traditions we have the mentality of pre-1980s British manufacturing, only our tolerance for defects is much higher. Why else do we spend our evenings as teachers searching for defects, correcting them or simply discarding the end result of a student’s efforts as beyond rescue?

If you were to estimate the defect rate each time you collect and mark a class’s work, how high would it be?

What if we moved to a ‘zero defect’ policy in our classrooms? How would this look?

What if we could stop the practice of sifting through the end products, looking for error?

What if we spent our time designing the learning process well, delivering exemplary teaching and building in opportunities to pre-empt error? What if we aimed to get it ‘right first time’?

Let’s make a contract with our students for 100% quality.

Zen and the Art of the Computing Curriculum

“The whole is other than the sum of its parts.” Kurt Koffka

There seems to have been a resurgence in debate about curriculum, at least amongst the blogging classes. This interest has perhaps been driven by the freedoms created through a slimmed down National Curriculum and removal of NC levels, and perhaps also by arguments in favour of a ‘knowledge-rich’ curriculum being made convincingly by some. Whatever the reason, I welcome this shift in focus and see it is an opportunity for teachers to wrestle back some professional autonomy.

In the subject of Computing, however, there is somewhat of an existential crisis which needs to be resolved, as suggested by the fluidity of what the subject is called. We have moved from ICT, to IT, to Computing & IT, Computing or Computer Science. The subject is struggling to settle on an identity and its practitioners to agree on why the subject exists. Without a clear purpose, making sound decisions about what to teach is impossible.

The Govian rationale

Michael Gove was the catalyst for this existential crisis. Almost overnight, the bread and butter of ICT teaching, learning how to use application software, was devalued and debunked. Instead, computer programming was hailed as ‘what the economy needs’. Gove’s vision for an economy leading the way internationally in software development, a nation of programmers rather than secretaries, created a hierarchy of knowledge in the subject whereby using an application was ‘low value’ but knowing how to engineer it was deemed a more worthwhile pursuit.

Many educationalists are repelled by the notion that schools might exist to ensure a future workforce have the skills to generate economic prosperity. I don’t have a problem with this being part of the mission (although in my mind not the primary goal). However, wealth generation is not a mission that gets me out of bed in the morning, and I find Gove’s rationale for the existence of the subject in the school curriculum rather… uninspiring. Besides which, Gove’s economic logic is flawed even on its own capitalist merits. We simply don’t need a nation of programmers; we need an elite group who are highly skilled. What we do need is a nation of people who can use the internet, databases, spreadsheets and graphic applications. These skills might not generate as much economic value but they have high personal value as individuals navigate the modern world and seek employment.

To use or to create?

When viewed from the perspective of what the economy/individuals ‘need’, deciding what to teach in the Computing curriculum is quite simple. On the one hand, the subject needs to equip all students with the ability to use computers for everyday and common work-related purposes. On the other hand, we need to inspire and equip a generation of programmers. The latter purpose requires some introductory computer science content pre-GCSEs before allowing some students to specialise in this side of the subject.

Whilst the above approach is pragmatic, it leaves Computing as a divided subject. Indeed, in our school we call it ‘Computing and IT’, a recognition that what we now have is a forced marriage of two disciplines, with separate purposes, differing origins and distinct pedagogies.

The economic view of why the subject exists has no way of reconciling the divisions within the subject. Whilst we impose a functionalist perspective on the subject’s purpose/s, it will remain a marriage of unequals, the low-status IT forever subservient to the high-value Computing.

To reconcile the divisions described, we need to find a more meaningful reason for the subject of Computing to exist. A starting point may be to consider our relationship with technology. Let’s turn to the 1970’s for help.

Understanding how the motorcycle works

“The way to solve the conflict between human values and technological needs is not to run away from technology. That’s impossible. The way to resolve the conflict is to break down the barrier of dualistic thought that prevent a real understanding of what technology is – not an exploitation of nature, but a fusion of nature and the human spirit into a new kind of creation that transcends both. When this transcendence occurs in such events as the first airplane flight across the ocean or the first footsteps on the moon, a kind of public recognition of the transcendent nature of technology occurs. But this transcendence should also occur at the individual level, on a personal basis, in one’s own life, in a less dramatic way.”
― Robert M. PirsigZen and the Art of Motorcycle Maintenance: An Inquiry Into Values

Computers are things of wonder. What is now possible as a result of digital technology would not only have been unimaginable to past generations but is almost magical to the vast majority of people today. We can comprehend what it is that computers have made possible but few can comprehend how this is actually possible.

We can see the lady sawn in half, we know it is not magic, but goodness knows how it is done!

The almost magical nature of modern technology is due to what is called ’emergent behaviour’ in systems theory. This is the phenomenon whereby the whole (system) has properties its parts do not have. These properties come about because of interactions among the parts. In other words, the whole is greater than the sum of its parts, as the saying goes.

However, technology seems to have progressed beyond simple emergent behaviour. The functionality of computer systems seems so far removed from what should be possible by combining a computer’s component parts that there is a disconnect in our understanding of what we know we can do with computers and how on earth this is possible. [This is evident when you teach binary to children and explain to them that the strings of 0s and 1s are the entire basis for all computer processing – they simply cannot conceive that this is possible given what they have seen computers do.]

Perhaps a better description of the behaviour of modern computer systems is, in the words of Kurt Koffka, that “the whole is other than the sum of its parts”. This quote (mis-translated in common usage, as above) comes from the Berlin School of experimental psychology. The saying has been misappropriated by systems theorists and in fact does not relate to the emergent behaviour of systems, rather the tendency of the human mind to perceive the whole of something as independent of the parts of which it comprises. However, the quote seems apt to our experience of technology today. We can no longer conceive how our experience of the technological world which we are emerged in can possibly relate to the circuits and electrical currents which drive our virtual world.

The disconnect between our experience of technology and our understanding of how it works was identified by Robert M. Pirsig in his novel ‘Zen and the Art of Motorcycle Maintenance’, published way back in 1974. Pirsig highlights the frustration and dissatisfaction with modern life which arises, he argues, from technology becoming so complex that the user ceases to understand it, or to be able to engage with the concepts that underpin its design and functionality.

The motorcycle analogy in the title exemplifies this conflict. The act of riding the motorcycle is, to the romantic, a joyous experience, almost magical. However, there arises a deep frustration with the technology when the motorcycle requires maintenance which, without an understanding of the mechanics of the vehicle, must be carried out by someone else. The narrator promotes an understanding of the engineering of the motorcycle achieved through carrying out one’s own maintenance and, in doing so, coming to understand the ideas behind what the machine is; creating a synergy between the user and the machine, between the materials and the human ingenuity that created the whole.

“You go flying across the countryside under a power that would be called magic if it were not so completely rational in every way. It’s the understanding of this rational intellectual idea that’s fundamental. John looks at his motorcycle and he sees steel in various shapes and has negative feelings about these steel shapes and turns off the whole thing. I look at the shapes of the steel now and I see ideas. He thinks I’m working on parts. I’m working on concepts.”

The ‘dehumanizing’ effect of technology is a theme throughout the book and Pirsig’s nameless narrator seeks a way to reconnect with our creation through experiencing the romantic joy of the technology’s use and understanding how this experience is delivered through an intimacy with the human ideas which lie behind the machinations.

Pirsig’s insight is that technology is “not an exploitation of nature, but a fusion of nature and the human spirit into a new kind of creation that transcends both”. This ‘transcendence’ is the Wow! factor which makes the subject of Computing appealing and fascinating to the teenage mind. Pirsig points to the shared cultural transcendent moments, such as the moon landing, but argues that “this transcendence should also occur at the individual level, on a personal basis, in one’s own life, in a less dramatic way”.

This ‘personal transcendence’ achieved by an individual fusing their ideas with the available technology to create something new and ‘greater (or even ‘other’) than the sum of its parts’ is a good start to establishing a mission statement for Computing as a subject. But this romantic notion of technology is in itself not sufficient. There must also be a rational understanding of how this technology has come to be and of the concepts and ideas which humans have conceived before this technology could be created. Without understanding how technology comes to be there will remain a disconnect between human and machine, which will breed suspicion and frustration.

Towards a meaningful existence

Pirsig’s novel, and the philosophical ideas upon which he draws, offer us an alternative to the purely economic rationale for the existence of Computing as a subject, and also a potential way to reconcile the two parts of the subject.

As stated previously, we do not have to reject the functional view that Computing prepares students with the knowledge and skills needed to succeed, either as elite programmers, office workers or in managing their personal finances. However, we can aim higher than this in forming a driving mission for the subject.

Perhaps we can begin by seeking to educate students in the ways in which technological machines are greater than the sum of their parts; that the emergent behaviour of the systems we have created is powerful and transformational.

We might then explore how the technological world, the web of machines and the artificial intelligence which begins to arise, is other than the sum of its parts; truly changing the way humans live their lives and even how they conceive of their existence.

At a personal level, we might aim to give each student a transcendent experience, showing them what becomes individually possible when they fuse their human capacity to generate ideas with the technological capacity to deliver them.

And we might teach students to overcome the dehumanizing effect of technology by educating them in the mechanics; not just the technicalities of the machine’s operation, but the big ideas behind its design. The motorcycle maintenance.

I don’t expect that what we decide to teach would be very different as a result of this re-conception of the subject. I suspect we would still spend some time creating spreadsheets, teaching binary, understanding networks and learning how to search the internet. But perhaps how we engage students in the subject would change if we had a compelling vision for its place in the curriculum. Perhaps, as teachers of the subject, we might be more united and proud of our subject, elevating it above the shameful Govian ‘skills for work’ brand to a subject which is essential in understanding the world, like Geography or History.

If the subject is ever to be more than the sum of its disparate parts, we need a driving purpose and vision for its place in the school curriculum. And we need to decide what we are going to call it!

Confessions of an occasional IT teacher

Anyone can teach IT, can’t they? That attitude may be changing now the subject has morphed into Computing (all that pesky programming and the like), but when I started teaching IT it was definitely the view.

IT teachers themselves were conscripts from other subjects, usually D&T or Maths. As long as you were geeky and liked tinkering with cables at the back of a computer you would do.

As a Business Studies teacher I qualified to be able to teach IT. After all, we used computers in my subject too and I looked like I knew what I was doing. To be fair, we did some IT in my teacher training (and dabbled with some Economics). But I was self taught in using computers, and still am. I’ve never attended a training course and yet I can do some cool stuff with a spreadsheet!

For that matter, I’ve never been trained properly to teach any of the other subjects I’ve ended up teaching; Economics, Sociology, Maths and RE. I’ve taught four subjects to A Level, three of which I learnt by teaching myself the content one lesson ahead of the students.

I’m a headteacher now and I try to help out in filling the gaps in the timetable where I can. This year I’ve been given two Year 7 IT classes (except now its called Computing and IT; more of that later). I haven’t taught IT for a over 10 years. I have taught the subject to AS Level, but it has changed a lot. Anyway, I was happy to teach it again and, you know what, I’m enjoying it.

The thing is, two things have changed since I last taught this subject:

  1. My teaching
  2. The subject

10 or 15 years ago, there seemed to be a common approach to IT teaching which might be described as ‘Come in. Get on with it’. IT was all about learning how to use application software. There was obviously some explicit teaching which usually took the form of a quick explanation of how to do something on the computer (all about the skills, certainly at KS3), then students worked on an open-ended task, sometimes for weeks.

The features of this approach were:

  • Short, skills-based teaching inputs (usually begrudged by students who just wanted to ‘get on with it’)
  • Limited amounts of theory or conceptual understanding
  • Low levels of challenge
  • Extended projects
  • Students working at their own pace
  • Individual, verbal feedback from the teacher when students got stuck or the teacher noticed them doing something wrong.

I was observed by a senior colleague once and given a ‘satisfactory’ for my lesson. The reason it wasn’t ‘good’? The observer told me “there was no starter or plenary. They just came in and got on with it”.

I was livid at the time. I had spent months training them how to ‘get on with it’. As a result, they were productive, focused, on task and making great progress. Every student in that class got A*-C and the value added was through the roof. Interrupting this Zen-like flow would have been crazy, I thought.

Although we can scoff at the (Oftsed inspired) three-part-lesson looking back, I am starting to think the observer had a point. What were students learning in that lesson? They were doing lots, but were they applying the skills they already knew?  I could tell they were making progress in completing the task (I had a spreadsheet to prove it), but could I tell they were making progress in their learning?

I think now that the subject, the subject pedagogy and the assessment was all wrong. I’m glad the subject has changed and I’m glad my teaching has changed.

What follows is a summary of how my current practice as an occasional (Computing &) IT teacher is now, with some visuals thrown in for good measure.

Change 1: What I am teaching

IT is not the subject it used to be. The dramatic swing to Computer Science (driven by Michael Gove) has changed the subject beyond recognition in some schools. The pace and scale of these changes has left many schools floundering to find teachers, train teachers and retain teachers (who just don’t want to teach high-level programming skills).

In our school, common sense prevails. Our great head of department and I agree that, whilst a minority of students will need skills like programming and it is useful to give all students an introduction to Computer Science, most still need application software skills too. Being able to write a letter on Word, create a spreadsheet, use a database, search the internet, send an email or prepare a presentation, are skills that most young people will need in their personal and working lives in the future.

Our Computing and IT curriculum is therefore a healthy mix of the old IT and the new Computer Science.

Compared to my previous experience, however, teaching the subject feels quite different. There is now much more ‘knowledge’ to be taught and a greater need to ‘teach’ over ‘facilitate’. The content is also much more challenging. The topics I taught to Year 12 students over 10 years ago are now in the Year 7 curriculum. Think about that for a moment. We aren’t expecting Year 7 students to understand as much as a Year 12 student would, but we are touching upon the same topics, concepts and skills.

Change 2: How we think about ‘progress’

When your teaching is built around students completing a task to ‘show’ they have a set of skills, then moving on to the next unit, it is unsurprising that progress is measured by whether they complete the task and evidence a set of competencies. The dominant mode of assessment – coursework/projects – reinforces this view of what progress is.

We have been looking carefully at our models of progress (i.e. where students start from, where we want to get them to and the route from A to B). I have been influenced greatly by the the definition of learning as a ‘change in long term memory’ (Kirschner, Sweller and Clark). I want students to remember the skills I have taught them, not just be able to apply them immediately afterwards. I am also faced with considerably more conceptual knowledge to teach in the subject than I was previously used to. To make progress over time, students will need to retain this knowledge and be able to access it later.

I have also increased my awareness of the importance of breaking down knowledge in to its component parts and sequencing very carefully how this knowledge is introduced to students. Writers such as Daisy Christodoulou (Making Good Progress) have introduced me to deliberate practice models which require explicit instructional approaches. When faced with teaching topics like ‘Binary’, I am finding that careful thinking about knowledge and sequencing is very important. But even in teaching the ‘old IT’ content, such as spreadsheets, these ideas are valuable. I find myself building conceptual understanding and skills more methodically and carefully than I used to, preempting misconceptions and checking that everyone is ready to move on.

Change 3: How we summatively assess

We have made the decision to introduce end-of-year exams at KS3 in our school. This has been driven by the idea that a well-designed, summative assessment is probably the most reliable way to infer if students have actually learnt anything.

As an occasional Computing & IT teacher, I welcome this change. It will support my change in focus from short-term performance to long-term retention of knowledge. The knowledge that my students will be tested on what they have learnt over the year is beginning to change my teaching.

Change 4: Being clear about essential knowledge

I have started to experiment with Knowledge Organisers (early days). Part of me thinks this might be a fad, and I share some of the concerns I hear and read about this being a reductionist approach. However, I am drawn to KOs for the following reasons:

  1. They force me to articulate exactly what it is I want students to know, at least as a minimum
  2. They provide clarity for assessment
  3. They are useful for non-specialist and novice teachers of the subject in their planning
  4. They (may) help students develop better study habits and (could) be useful for promoting retrieval practice

So far, I have written some (which has been useful in focusing my teaching) but I am yet to share with students. I intend to do this in the run-up to the summer exams, to help them structure their revision. However, I might try some retrieval practice homework to support revision for some low-stakes tests in the meantime.

Here are my first attempts (apologies for the picture quality).


Change 5: Diagnostic questions and deliberate practice

I am interested in the common mistakes, bad habits and misconceptions in Computing & IT. Whereas my old self would have spent a great deal of time walking from student to student, individually and repeatedly correcting their errors, I now want to preempt these errors and explicitly address them in my teaching.

For example, students often right-justify text in Word using the space or tab bar. It drives IT teachers crazy. In days gone by  I would tell students not to do this, but instead to use the ‘right alignment’ icon. They would then ignore my instruction and resume their bad habit. They would print their work, I would take it home to mark and write “Right align!!!” or something similar on their work. They would ignore this and continue with their ingrained habits. And why wouldn’t they? Repeated behaviours cannot be broken by a swipe of my red pen.

I have come to realise that habits will only change if new habits are introduced and reinforced. I have done this in two ways, with some success. Firstly, make students repeatedly practice the behaviour you want them to adopt. In the example of alignment, give students text aligned in various ways with an instruction to change the alignment in a specific way (e.g. left to right). Whereas students can ignore your verbal advice, this simple approach gets them to practice the behaviour you want them to adopt. If they persist in their old ways, get them to do the exercise again. They soon change their ways.

For errors that are based more on conceptual misunderstanding than passive resistance, I have made use of diagnostic questions which provide a snapshot of the class’s knowledge and help explicitly address misconceptions.

The example below (which I used as a starter – that old observer would have been pleased!) was designed to reinforce good habits around formula construction. Three of the answers would work (A, C and D), but D is the required solution. This question emphasises the need to put the = at the start, not the end of the formula (as you do in Maths) and leads to a reminder of the benefits of using cell references over numbers.

Diagnostic question picture

Following this starter (which some students gave the wrong answer to) none of the students made the common errors which I would normally expect from a Year 7 class. What is more, hardly any students made these mistakes in any of the spreadsheet work they did thereafter. There was no time wasted in correcting students individually and no need to write on their work with red pen – they got it right first time.

These skills were supported by an excellent deliberate practice exercise (produced by my head of department) whereby students repeatedly entered sum formula in to a spreadsheet model, which gave them instant feedback on their efforts.

Change 6: Retrieval practice and spaced practice

This area is definitely work-in-progress, but requires a more fundamental shift in our schemes of work, assessment and homework. However, I have mentally shifted from my past practice as an IT teacher of teaching it and moving on. With an end-of-year assessment looming, we cannot afford to touch upon key concepts only once. Students’ memory of the content will fade over time and find recall in exam conditions tough, or impossible. Revision needs to become something that happens throughout the year, not just before the exams.

I am increasingly using low-stakes testing to promote retrieval and this appears to be effective. Technology such as Plickers appeals to the students and enables me to capture their responses, but I am also using more traditional approaches (like quizzes and starter questions). My next step is to interleave questions from past topics. I like the ‘starter for 5’ approach I see used in Maths which has some questions focused on the learning from last lesson, some on concepts further back and one to bridge to that lesson’s content. This approach is simple and can become a habit which is easy for a teacher to sustain.

The knowledge organisers will help with planning retrieval practice. By setting out the essential knowledge in each topic, it is easy to come up with recall questions and track which knowledge you haven’t yet revisited. I hope that students will also find these useful as they become more accustomed to retrieval practice homework.

Change 7: The pattern of my lessons

As a result of all of the above, the pattern of my teaching in this subject has changed. Instead of prolonged periods of independent working, my lessons are punctuated by bouts of explicit teaching, deliberate practice, diagnostic assessment, low-stakes tests and the occasional open-ended tasks. My teaching is more varied, more targeted and more explicit. You will never hear “Come in. Get on with it.”, that’s for sure.

Its’ a better subject now, and I think I’m a better teacher. I wonder how much it will change by the next time I’m asked to teach it?


Many moons ago my Dad bumped in to my old headteacher. He asked after my brother (a ‘good’ student). My Dad told him how he was getting on, then mentioned that his other son (me) was starting his teacher training.

The head of my former school laughed. “He’ll never be a teacher”, he guffawed.

He was wrong. I am a teacher. What’s more, a headteacher with a national teaching award under my belt. That’s not a boast, but it is a two-finger salute.

I’m tempted to attach the label ‘pompous idiot’ to the man who flounced in to his first assembly at the school in his graduation gown and mortarboard, as many of us sung the Batman theme tune. But I’ll be more generous and call him ‘misguided’ in his estimation of his former student’s potential.

What was the source of his error?

Perhaps he made a generalisation error. I wasn’t the most hard working student and my laid-back attitude to study might have been interpreted as a character trait, rather than a behaviour attached to a certain type of endeavour. Had he observed the efforts I made in pursuit of something I was passionate about (the hours I spent rehearsing for drama productions, for instance), he might have realised his mistake in attributing behaviour to an inherent trait, rather than the situation.

Perhaps my lack of commitment to my studies and apparent weakness as an academic was interpreted as evidence of unsuitability for the profession. Teachers have to work hard and have good subject knowledge after all. If I didn’t demonstrate this in a school environment, why would I in a work-context?

Or perhaps he made an extrapolation error, assuming that my past actions were a reliable prediction of my future self.

Whatever the reason, the assessment of my potential was wrong.

As you can tell, this experience has, in a small way, driven me. It has also shaped me as a teacher. I am wary about talk of ‘potential’. I am irritated by others who write students off. I do not assume that the child I see in front of me is all that they are. I try to remember that their behaviour is situational, not an inherent feature of their personality. I am cautious about predicting a student’s career path or life chances.

Ironically, being told I would not make a good teacher has made me a better teacher.

’Potential’ be damned.


The Quest for Teacher Quality

There has been an increasing tendency in schools in England to hold teachers to account for the outcomes achieved by their classes. This has become the predominant means by which schools attempt to improve examination results. The thinking seems to be “We want to improve results. Results are dependent on the quality of teaching. We need to hold teachers to account for improving their teaching (i.e. results)”.

There are many flaws in this logic, including making ‘results’ the goal rather than ‘quality education’, and confusing ‘better teaching’ with ‘better exam results’.

There is also an incorrect assumption, which is that exam results are largely a consequence of the quality of teaching provided by an individual teacher. This assumption ignores the situational factors which can affect performance.

In a paper by Mary M. Kennedy titled ‘Attribution Error and the Quest for Teacher Quality’, the tendency to underestimate situational factors is given a name:

“Social psychologists are persuaded that we are all guilty of overestimating the influence of personal characteristics on behaviour and underestimating the influence of the situation itself. In fact, this tendency is so widespread that it has been called the fundamental attribution error (Glibert & Malone, 1995; Humphrey, 1985; Ross, 1977)”

In education, Kennedy argues that:

“we have veered too far toward the attribution of teaching quality to the characteristics of teachers themselves, and are overlooking situational factors that may have a strong bearing on the quality of the teaching practice we see.”

If we accept this contention, we would need to change our assumptions about the factors which lead students to succeed or fail from this:


Teacher characteristics (leads to) Teaching practices (leads to) Student learning

to this:

Teacher characteristics

                                                  (both lead to) Teaching practices (leads to) Student learning

Situation characteristics


Another way of conceptualising the influence on outcomes is this:

situational factors


Drawing on Kennedy’s paper and adding my own thoughts, the situational factors which may affect outcomes include:

Layer Factors
External Assessment reliability

Qualifications available

The defined curriculum

Student home backgrounds

Reform clutter

School Availability/maintenance of equipment

Work distractions

Behavioural norms

Quality of supporting systems

Requirements made of teachers (e.g. assessment, marking, homework)

Attendance levels

Allocated curriculum time

Requiring teachers to teach out-of-subject

Department Availability and quality of text books


Peer support


Class Room

Group mix

Quality of teaching received previously

General attainment levels of students in the class


It is common for schools to benchmark a class’s outcomes against:

  • National ‘expectations’ (e.g. FFT or P8)
  • The school’s outcomes (e.g. P8 score)
  • Other departments
  • Classes within the same subject
  • What those students achieved in their other subjects

Through benchmarking, it is possible to assert that a class’s results were good/bad/okay. It is also possible, through confidence testing and monitoring results over time, to get a sense of whether these outcomes were ‘normal’ or whether they fall outside of what might reasonably be expected.

What is much more difficult is to be able to conclude whether the results, good or bad, were as a result of teaching quality or situational factors. Even if we can see that the same students did better in other subjects, or that another class doing the same qualification achieved better, it is hard to say with certainty that this is because of variances in the quality of teaching.

There is some statistical evidence to suggest that the exam results a teacher achieves with their classes are more dependent on the department and school they work in than their effectiveness as a teacher. Good outcomes tend to be clustered in certain departments and poor outcomes in others. It is unlikely that the one department happens to contain lots of ‘better teachers’ than the other, and more likely that there are situational factors which affect the impact of the teacher’s teaching.

Equally, teachers in good schools tend to get better outcomes for their students than those in weaker schools. We may assume that the weaker school is full of less effective teachers, but what if the teachers are less effective because of the situation they are in?

In summary, I would sound two cautionary notes:

  1. When we look at exam results we need to be careful we don’t make the fundamental attribution error and ascribe all of the success/failure to the quality of the teacher/teaching. We should actively consider the effect of situational factors and come to a qualitative judgement on what caused the outcomes, and to what extent these causes were within or outside of the teacher’s control.

A considered approach will ensure we don’t make simplistic links between exam results and teacher competence.

  1. When we set about improving outcomes we should not fixate on teacher quality. Although the quality of teaching is a very important factor in improving outcomes, there are many other factors which will create an environment in which teachers have more impact. For example:
    1. Reducing tasks that distract teachers from teaching
    2. Improving standards of pupil behaviour
    3. Workforce planning to maximise the number of lessons taught by subject specialists
    4. Improving attendance levels
    5. Grouping/setting students
    6. Investing in resources and text books
    7. Maintaining equipment
    8. Improving the quality of leadership

We need to make sure that it is as easy as possible for teachers to teach.


Before we ‘step up’ our efforts to hold teachers to account where outcomes are not acceptable, we must consider carefully what the evidence actually is for whether teaching quality is the issue.


Tips for using MC questions to highlight a misconception

I’ve been fortunate to observe a number of colleagues using multiple choice questions in their teaching recently. Sometimes these were being used to promote recall of previously taught material. Others were using MC questions to highlight misconceptions.

The design and use of MC questions for highlighting misconceptions seems to be a tougher thing to get right. The problematic aspects appear to be around deciding when to employ this assessment approach, how to design the question/s and how to maximise the learning opportunity.

Here are some tips:

1. Be selective about when you use MC questions to highlight misconceptions. They work best when you can identify errors which often occur in relation to the topic or concept. It really helps less experienced teachers if these common misconceptions are highlighted in the scheme of work.

2. Make sure there is at least one credible ‘distractor’ answer, probably more than one.

3. Don’t lay traps. For example, don’t make an answer ‘wrong’ just because it doesn’t contain the right terminology or isn’t explained clearly enough.

4. Be clear with students what the ‘rules’ of the question are. For example, let them know if there is only one correct answer, or more than one. Warn them that there are answers which are ‘almost right’ or designed to highlight common misconceptions. Explain why you are asking them the question.

5. Make sure they do not confer.

6. Reassure students that you are absolutely fine with them getting the answer wrong; indeed it will be really helpful if some do. Make it safe for them.

7. Employ some method of every student having to decide on an answer and you being able to scan the answers given. Mini- whiteboards are sufficient. I’ve been using Plickers as a low-cost technological alternative, which has the advantage of capturing the data.

8. Don’t give away what the correct answer is until you’ve squeezed the learning out of the exercise. Saying things like ‘most of you have got it right’ will belittle those who didn’t and undermine the potential for learning from mistakes.

9. Encourage students to articulate their thinking. Don’t agree or disagree. Bounce to other students to allow them to add to, or differ, from the rationale given. Make them listen to each other and extend each other’s thinking.

10. Praise those willing to state their thinking, not just those whose thinking is correct.

11. Consider revealing the distractor answer before you reveal the correct answer. Explain clearly why it is not correct, but why students often choose it. Make the mistake feel normal and the opportunity to discuss it valuable.

12. Once the right answer is revealed, focus sufficiently on the reason for it being correct to ensure students are clear. Perhaps pause for them to write down in their own words why this is the correct answer.