Students who know what success looks like have a goal and know how to achieve it.  Goals increase motivation and belief (Locke and Latham, 2002), particularly when they are broken into “attainable subgoals” which provide “immediate incentives and guides for action (Bandura, 1982, p.134).”  A mental image of success is crucial to deliberate practice, which:

“Both produces and depends on effective mental representations.  Mental representations make it possible to monitor how one is doing, both in practice and in actual performance.  They show the right way to do something and allow one to notice when doing something wrong and to correct it (Ericsson and Pool, 2016, p.99-100).”

I concluded a recent post wanting to show students what success looks like, but unsure how best to do so.  I had always believed the key was sharing learning objectives, but eventually, reluctantly, I changed my mind.  Objectives rely on concrete descriptors – slippery words like ‘persuasive’ and ‘methodical’.  But knowing that an argument should be ‘persuasive’ does not show students how to make it persuasive: persuasiveness is the kind of idea “which cannot be specified in detail” and so “cannot be transmitted by prescription, since no prescription for it exists (Polanyi, 1962, p.53).”  I needed a better way to share goals and guide students’ actions.

An arsenal of exemplars

A sense of what success looks like “can be passed on only by example from master to apprentice (Polanyi, 1962, p.53.).”  It is “’caught’ through experience (Sadler, 1989, p.135)”: the acquisition of an “arsenal of exemplars (Kuhn, 2001, cited in Christodoulou, 2017, p.96)”, examined by the student alongside an expert.  Ron Berger describes how examples “set the standards for what I and my students aspire to achieve (2003, p.29-30).”  He offers students “a taste of excellence (p.31)”:

We sit and we admire. We critique and discuss what makes the work powerful: what makes a piece of creative writing compelling and exciting; what makes a scientific or historical research project significant and stirring; what makes a novel mathematical solution so breath-taking (2003, p.31).”

An ‘arsenal of exemplars’ lets us to show what success looks like, rather than tell.  Cognitive science suggests that providing worked examples – models broken into steps – can help students learn better and more efficiently (Zhu and Simon, 1987).  This effect seems to hold for tasks with clear solutions (like maths problems), with many solutions (like English essays (Kyun, Kalyuga and Sweller, 2013)) and even behaviours like cooperation and subjects like art (Renkl, Hilbert and Schworm, 2008).

What does this look like in the classroom?

Craig Barton (2018) demonstrates the power of example – problem pairs.  He demonstrates a worked example, then asks students to complete a similar problem independently, leaving the worked example visible.

Barton helps students master increasingly difficult problems step by step, by varying one aspect of the model at a time, for example, changing only the denominator of one fraction.  His models bring success within students’ grasp.

Carolyn Massey (2016) demonstrates how this applies to tasks without a clear solution, like elegant historical writing.  She used Orlando Figes’s A People’s Tragedy: The Russian Revolution, 1891-1924 as a model of academic prose.  Her students discussed what makes Figes’s work so powerful, formulating criteria:

I’ve argued that success criteria are meaningless on their own (What is ‘juicy evidence’?  How can we be ‘analytical’ without being ‘stale’?), but Massey’s approach does not rely on sterile descriptors: students began with excellent historical writing and then distilled its qualities into criteria.  This is the crucial step which I overlooked in sharing success criteria with students: I explained the mark scheme, rather than showing students how great work exemplified it.  Massey’s students’ criteria acted as an aide memoire, and they returned to A People’s Tragedy repeatedly, using it as a yardstick for their writing and a guide to improvement.  So, success criteria can be useful, provided they originate in, and remain connected to, the model.

Surprise 1: More than just a model

I was surprised to learn that presenting students with a good model is generally insufficient.  Successful learning from worked examples “does not always occur naturally (Wittwer and Renkl, 2010, p.394).”  If students see only good models, it can be hard to distinguish what makes them effective: comparing contrasting models allows them to identify what differentiates excellence from mediocrity (Lin Siegler et al., 2015).  We can help students further by offering completion problems: unfinished models which students complete: checking whether students can identify the next step also provides a rapid test of prior knowledge (Kalyuga and Sweller, 2004).  This seems to decrease extraneous cognitive load, to help students create mental models and to help them to transfer their learning to new problems (Sweller, van Merriënboer and Paas, 1998).

Surprise 2: The limits of teacher explanations

I was even more surprised to learn how little teachers’ explanations add to models.  There’s compelling evidence that having students evaluate the merits of contrasting models may be sufficient without additional teacher explanation (Renkl, Hilbert and Schworm, 2008; Wittwer and Renkl, 2010) – another example of the limits of words in conveying what success looks like, and the merits of models.  Craig Barton modified his use of models to take account of this: after presenting each worked example, he invites students to work out what has happened themselves – silently – before their own attempt (2018, p.209).  In showing what success looks like, our explanations may be less important than students’ thoughtful engagement in the models.

Conclusion

Use models to show what success looks like: is this really worth emphasising?  Surely everyone uses models?  I think models deserve more attention, for two reasons:

1) Teachers seem less concerned about effective modelling than other aspects of teaching.  For example, over 250 teachers signed up to read advanced chapters of Responsive Teaching.  I asked each person to describe what they were trying to improve in their teaching, and sent them a relevant chapter.  I sent thirteen people the chapter on showing what success looks like; seventy asked for guidance on feedback.  I suspect the effective use of models might solve some of the challenges we face in giving feedback.

2) I suspect all teachers offer models.  But the surprises I described above – using contrasting models, having students identify the differences themselves – can increase the power of models and are, I suspect, less well-known.

So, if you’re already using models, could you:

  • Offer two contrasting models?
  • Invite students to evaluate the models independently?
  • Offer completion problems, in which students have to do something with the models?

When we use models to show students what success looks like, we develop their mental representations of success, provide meaningful goals and guide their actions.  Models really are magic.

This is an adapted excerpt from the Responsive Teaching: Cognitive Science and Formative Assessment in Practice.

If you liked this, you may appreciate:

The previous post, on the limitations of learning objectives.

My process for helping students write better essays.

References

Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), pp.122-147.

Barton, C. (2018). How I wish I’d taught maths: lessons learned from research, conversations with experts, and 12 years of mistakes. Woodbridge: John Catt.

Berger, R. (2003) An Ethic of Excellence: Building a Culture of Craftsmanship with Students. Heinemann

Christodoulou, D. (2017) Making Good Progress: The Future of Assessment for Learning. Oxford, OUP.

Ericsson, A., Pool, R. (2016). Peak: Secrets from the new science of expertise. London: Bodley Head.

Kalyuga, S. and Sweller, J. (2004). Measuring Knowledge to Optimize Cognitive Load Factors During Instruction. Journal of Educational Psychology, 96(3), pp.558-568.

Kyun, S. Kalyuga, S. and Sweller, J. (2013) The Effect of Worked Examples When Learning to Write Essays in English Literature, The Journal of Experimental Education, 81:3, 385-408, DOI: 10.1080/00220973.2012.727884

Lin-Siegler, X., Shaenfield, D., & Elder, A. D. (2015) Contrasting case instruction can improve self-assessment of writing. Educational Technology Research and Development, 63: 1-21.

Locke, E. A. and Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation. American Psychologist, 57, pp.705–717.

Massey, C. (2016) Asking Year 12, ‘What Would Figes Do?’ Using an academic historian as the gold standard for feedback. Teaching History 164.

Polanyi, M. (1962). Personal Knowledge: Towards a Post-Critical Philosophy. Abingdon: Routledge.

Renkl, A., Hilbert, T. & Schworm, S. (2009). Example-Based Learning in Heuristic Domains: A Cognitive Load Theory Account. Educational Psychology Review, 21(67), DOI: 10.1007/s10648-008-9093-4.

Sadler, D. (1989). Formative assessment and the design of instructional systems. Instructional Science, 18(2), pp.119-144.

Sweller, J., van Merriënboer J. J., Paas F. G. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251-296.

Wittwer, J. and Renkl, A. (2010). How Effective are Instructional Explanations in Example-Based Learning? A Meta-Analytic Review. Educational Psychology Review 22(4), pp 393–409.

Zhu, X., and Simon, H. (1987). Learning mathematics from examples and by doing. Cognitive Instruction 4: 137-166.