I’ve been thinking about feedback and reminiscing about my younger days as a sports coach. When introducing a new skill to an individual, it was imperative I could model, or show an example of what ‘good’ looks like, otherwise learners would simply not know what they were aiming to achieve.
Learning something new is challenging and it becomes more so if we don’t know what good ‘looks like’. I’m not an engineer, but let’s take the example of learning a fillet lap weld. Without seeing what a good fillet lap weld looks like, it would be nigh on impossible for a learner to do one successfully. Take the correct use of apostrophes - without seeing the various uses of an apostrophe, one simply wouldn’t know how to use it.
However, just knowing what good ‘looks like’ isn’t enough to learn something effectively. Along the way to mastering a fillet lap weld, or correct apostrophe use, there’ll no doubt be mistakes made. This is where feedback is essential. According to Ramaprasad (1983, p.4) “Feedback is information about the gap between the actual level and the reference level of a system parameter which is used to alter the gap in some way.” In other words, feedback should identify the strengths and weaknesses of performance in relation to what good ‘looks like’. But is it that simple?
Feedback on performance
In 1996 Kluger and DiNisi explored the effects of feedback on performance. Their meta-analysis revealed that on average, feedback improved performance, but bizarrely, in over a third of cases, feedback actually impeded performance. Upon further exploration, their work revealed that the more effective feedback focused on thequality of the work (task-oriented), rather than the person (ego-oriented). In other words, focus was on the strengths and areas for development of the work, rather than assigning numbers or grades to the work, which allow for comparisons between learners.
In addition to this, they found that more effective feedback focused on what and how the individual could improve their performance (the future), rather than focusing too much on the performance itself (the past). I liken this to the analogy of driving a car. If we focus too much on what we can see in our rear view mirror, we’ll probably crash (image 1). Whereas, if we acknowledge our mirror, but focus our attention on the road in front, we’re more likely to be moving forward positively (image 2).
Clear goals for improvement
Similar findings were noted in the work of Hattie and Timperley (2007) who determined that feedback was best served with clear goals for improvement. If we think back to my point about knowing what good ‘looks like’, if feedback is provided in relation to a good example of a fillet lap weld and looks at how current work could be developed to achieve a good standard, then it is more likely that the learner will make improvements.
The thing with feedback is it becomes extremely challenging for a teacher to provide 20 to 30 learners with regular individual feedback in a session. Here’s the thing, you don’t need to. Once learners are clear with what good ‘looks like’, there are 20-30 other resources at a teacher's disposal, so why not ask them to provide feedback to one another?
Some common methods to do this are identified in Petty’s (2009) fantastic Evidence Based Teaching book. One of his diamonds is the ‘medal and mission’ approach - simple, yet effective. Firstly task-centered information is provided to the learner in relation to the goals (what good ‘looks like’) - the medal. Following this, learners are given a clear target for improvement in relation to the goal - the mission. For example:
"Jamal, you have clearly fit-up the plates accurately and your weld indicates that the distance to the joint was good, as the arc is the correct depth (medal). If you look at the model example, the bead size is slightly larger. To increase the size of the bead, you need to decrease the speed that you move along the joint. In your next attempt, continue in the same manner as before, but with a slightly slower speed."
Similar approaches that may be used include:
- Two stars and a wish: Useful for peer assessment, the learners give one another two stars (in other words, two things they think their peer has done well in relation to what good ‘looks like’) and a wish (something they wish could be improved upon in relation to what good ‘looks like’).
- WWW/EBI: As before, this acknowledges the past - What Went Well (in relation to what good ‘looks like’), before looking to the future with clear guidance for improvement, Even Better If… (in relation to what good ‘looks like’).
Whilst peer feedback is useful, it is worth noting the limitations of the above approaches. Indeed, Nuttall (2007) acknowledges that around 80 per cent of feedback in a typical classroom is between peers, yet around 80 per cent of that feedback is inaccurate. If we can provide suitable structures, such as the above, and ensure that clear success criteria is provided, then we can improve the effectiveness of peer-to-peer feedback.
To summarise, if we really want to maximise feedback in classrooms, we need to ensure the following:
- Everyone is clear with what good ‘looks like’.
- Feedback looks forward and not back.
- Feedback focuses on the task and not the person.
- Feedback involves everyone.
Dan Williams is a Lecturer in Post 14 Teacher Training at the University of Derby. He is also a Board Member and Trustee of the ETF and Chair of the SET Management Board. His interests include educational research, specifically classroom based experiments and cognitive psychology.
- Hattie, J. and Timperley, H. (2007). The power of feedback. Review of Educational Research. 77 (1), p. 81-112.
- Kluger, A.N. and DiNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis and a preliminary feedback intervention theory. Psychological Bulletin, 119 (2), p. 254-284.
- Nuthall, G. (2007). The Hidden Lives of Learners. NZCER Press
- Petty, G. (2009). Evidence Based Teaching. Cheltenham: Nelson Thornes.
- Ramaprasad, A. (1983). On the definition of feedback. Behavioral Science, 28, 4–13.