Let’s talk about modelling

“When teachers explain, they also engage in the practice of modeling. Again in common parlance, modeling occurs when teachers show students how to do many things. Showing is a physical activity in this sense, but teachers also model cognitive processes. They think aloud as they show students how to solve a mathematics problem or interpret a literary text. They develop repertoires of representations, models, metaphors, tasks, and examples for use in building student understanding in the disciplines of knowledge and for building students’ academic skills.” (Stickler and Sykes, 2016)

Modelling a fundamental aspect of delivery in the classroom, and one of the strongest tools an educator has. Whether it’s modelling worked solutions with metacognitive analysis, essay plans, practical skills, or simply modelling fundamental behaviours to students – modelling is an ideal strategy for introducing learners to new skills and concepts, the cognitive processes that go alongside them and address key misconceptions that manifest in student work, often before they even arise. 

To the layperson, instruction and modelling are often synonymous with ‘teaching’. For the teacher, models are key places to provide ‘scaffolding’ for students for behaviour, skills and knowledge you wish for them to possess. Belland (2017) defines 4-types of scaffolding; conceptual scaffolding, strategic scaffolding, metacognitive scaffolding and motivational scaffolding. I believe these definitions can also be adapted to modelling scenarios, as a key place of scaffolding for learners;

These four areas will be explored in more detail in the future, but for now it’s safe to say that all aspects of modelling are vital across both practical and theoretical disciplines, the ability to craft and deliver strong and relevant modelled scenarios is a fundamental skill of an educational practitioner.

The Background:

It was either the first or second day back in January, and I’m in a meeting with my line manager’s line manager – we’re conducting a post-mortem on recent mock exam results – they were not good – they were about as far as good as you could get.

It was Year 13 – I had been responsible for the group in year 12 but had not been timetabled to take them forward to year 13. Due to various circumstances they had already had 2 teachers since September, the second had been a temporary member of staff who had left in the December and I was going to pick the class up. Personally I could not have been happier, I resented not being able to take that class forward, but there were others with more experience. What followed from this point is to this day one of the most fulfilling teaching years of my life, and I still miss being able to teach this class, and work with them.

But I digress, at this moment it was not good. Obviously the overall circumstance had not been ideal for the students and their progress, but I was pushed into thinking if there was anything else that could explain the results. We had done some reciprocal observations in the half-term before and I’d really enjoyed the lessons I saw, the teacher was incredibly enthusiastic and knowledgable…“but”…

There was one-thing that I had found strange…”I’m not even really sure how to explain it…or if it would even make a difference…but when they modelled examples, they did the examples as themselves, as if it was for themselves”…now I stress I am not offering this up as an explanation for poor results, it was just something that had stuck in my head in an observation. I had struggled to articulate myself, but I knew what I meant, I have discussed what I have meant when talking about modelling with colleagues over the years, but I still wasn’t happy with being unable to articulate myself clearly…until recently.

I have recently read “How Learning Happens…” (Kirschner and Hendrick, 2020) – very early on within section 1 of the book there is a chapter entitled “A Novice is Not a Little Expert” – based around a 1979 study (Chi, M.T.H., Feltovich, P.J. and Glaser, R) into approaches to Physics problems by post-graduate ‘experts’ and undergraduate ‘novices’. I actually remember this study from my PGCE, where it was used as an explainer as to why students will often incorrectly repeat identical steps in unconnected problems – especially when accounting for recency bias of examples, because on the surface two problems ‘look the same’ (similar diagram/equation/terminology) – even if the ultimate outcome and knowledge assessed in the questions are unconnected. Rereading this and the section in “How Learning Happens…” and thinking about this classification of ‘novice’ and ‘expert’ has helped me articulate the crux of my modelling conundrum.

Articulating the Thought: Who is the star of your example?

In the paradigm of teaching the expectation is to develop expert knowledge and mastery by modelling good practice. But how we pitch for and scaffold learners to this point is important. As the various studies referenced in “How Learning Happens…” state that we should not treat novices as little experts. In the lesson I had observed the practitioner had modelled process and thoughts, but had modelled the literal process and thoughts of themselves – for themselves – as an ‘expert’ – and the class just happened to be following along. The star of their modelled example was themself, the star of their modelled example was an ‘expert’.

A study by McLain, M.N et.al (2021) on STEM trainee teachers concludes with evidence of two ‘camps’ of teacher archetype within STEM, which manifest during modelling activities, a conclusion that matches earlier studies in the D&T fields. These are the ‘teacher-expert’ and the ‘teacher-facilitator’. The former uses more behaviourist approaches, with the practitioner leading the learner, the latter instead providing a scaffold to support learning. Now given what has been discussed earlier, neither of these modes is singularly ideal.

Without appropriate support, letting ‘novices’ free with a problem is going to be detrimental to progress. Countering this, whilst we need to model the behaviours of an ‘expert’, we should aim to position a ‘novice’ as the ‘main character’ or ‘star’ of your modelled solution and engage the class in this way to scaffold their development. You need to provide a frame of reference which is accessible for other ‘novices’ – the metacognitive processes, the steps, the skills – they all need to be accessible and achievable for the learner. You are modelling the cognitive and metacognitive processes that allow one to travel the journey from a ‘novice’ to ‘expert’ – not specifically the processes of the ‘expert’ themself.

This is the mindset behind ideas such as I/We/You modelling, understanding that powerful learning takes repetition, variation and depth (Webb, 2021) and structuring a method to scaffold students towards mastery. Beginning with what “I” do, modelling the metacognitive process, then moving into collaboration and partially scaffolded “We”, before allowing students to use developed principles in the “You” section of the process.

However, even in this system you craft and present a fictionalised “I” – this “I” is a vessel to emphasise certain components of a problem and make links to other knowledge areas, highlight key facts and skills, or even circumvent and discuss misconceptions in a topic. You model thoughts and processes that are second nature to the ‘expert’, as if they aren’t – that they require explicit interaction and engagement with, and are not ‘second nature’ – this allows for novice interaction and development. For example, my fictionalised “I” will often explain how they ‘struggle’ with certain geometric reasoning concepts, this allows me to introduce alternative strategies and skills, but also model competencies of perseverance, adaptability and reflection on personal weaknesses to students, which are traits ideal to develop.

Takeaways for Practice:

References and Further Reading:

• Belland, B.R. (2017). Instructional scaffolding in STEM education : strategies and efficacy evidence. Cham: Springer.
• Chi, M.T.H., Feltovich, P.J. and Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science 5 Issue 2, Pg.121-152
• McLain, MN, McLain, D, Wooff, D and Irving-Bell, D (2021) Preservice Teachers’ Perspectives on Modelling and Explaining in STEM Subjects: a Q Methodology Study. Techne Series: Research in in Sloyd Education and Crafts Science A, 28 (2). pp. 367-374. ISSN 1893-1774
• ‌Kirschner, P.A. and Hendrick, C. (2020). How learning happens : seminal works in educational psychology and what they mean in practice. London Routledge.
• Stickler, L., & Sykes, G. (2016). Modeling and explaining content: Definition, research support, and measurement of the ETS® National Observational Teaching Examination (NOTE) assessment series (Research Memorandum No. RM-16-07). Princeton, NJ: Educational Testing Service.‌
• Webb, J. (2021). Metacognition Handbook. John Catt Educational.