Research School Network: Understanding the Content Deb Friis explores the research evidence that sits behind dimension 1 of Evidence Based Education’s ​‘Great Teaching Toolkit’

This is the first of a series of four articles which will look in more detail at the Great Teaching Toolkit Evidence Review, which has been recently released by Evidence Based Education. As Wiliam (2018) pointed out, the single most effective thing that we can do to promote overall equity and attainment is to improve the quality of teaching currently in schools. This report is the first stage in an attempt to create a feedback system to help teachers to identify their strengths and also priorities for further development. The next stage will be the release of a set of diagnostic tools to accompany this report.

The report begins by acknowledging that teaching is complex, and that the evidence in favour of particular strategies is not always clear cut. There are regular evidence reviews throughout the report which make it clear to the reader which factors have a good background of empirical research and which are more problematic and why. The EBT have decided that on balance there are a clear set of factors which it is better to have than to not have, and that this makes the publication worthwhile. They also present clear evidence that having a structured framework for teacher improvement, which aims to develop teachers’ understanding and expertise in these skills and practises, is likely to be the best way to enhance impact, and therefore improve teaching (Creemers and Kyrakides’ Dynamic Model, 2006; 2011).

The report breaks presents a model for great teaching broken down into four dimensions as follows:

1. Understanding the content
2. Creating a supportive environment
3. Maximising opportunity to learn
4. Activating hard thinking.

This article will concentrate on the first dimension and others will be covered in subsequent weeks.

Dimension 1 is broken into four subsections:

1.1 Having deep and fluent knowledge and flexible understanding of the content you are teaching
1.2 Knowledge of the requirements of curriculum sequencing and dependencies in relation to the content and ideas you are teaching [or pedagogical content knowledge]
1.3 Knowledge of relevant curriculum tasks, assessments and activities, their diagnostic and didactic potential; being able to generate varied explanations and multiple representations / analogies / examples for the ideas that you are teaching
1.4Knowledge of common student strategies, misconceptions and sticking points in relation to the content you are teaching

This aspect of content knowledge has not usually been included in generic models (such as Praetorius et al., 2018) which tend to focus on behaviours that can be observed in the classroom. However in this report the authors have deemed that there is enough evidence that having particular kinds of knowledge is an important factor in effective teaching, and they place this section first as it is likely to be a prerequisite of professional learning. As the report acknowledges, however, one of the problems with the evidence for this dimension is that much of it comes from the domains of mathematics and science which means that it is hard to generalise across other subjects, although Kaiser and König (2019) do give other subject examples.

Section 1.1 is ​“essentially content knowledge, of a deep and connected kind”, and also theoretical knowledge of the domain of learning. ​“Pure” content knowledge has been studied by looking for relationships between teachers’ subject knowledge or qualification level and learning gains, and these have been inconsistent (Wayne & Youngs, 2003). Although content knowledge is important at the bottom end of the scale (Hill et al., 2005), once it is at least adequate there is no further benefit for the majority. It may be that the existing evidence is limited to particular age-groups or topics and, as mentioned earlier, many available studies are on mathematics subject knowledge enhancement alone.

Pedagogical content knowledge (PCK), section 1.2, has more broad support (Baumert et al., 2010 and Kaiser and König, 2019 have both completed reviews). There have been differing interpretations but in this case, PCK involves understanding connections between different topics and the sequencing of the curriculum in order to be able to successfully teach students a new concept. It is specifically identified in a framework from the Teacher Education and Development Study in Mathematics (TEDS‑M project. Blömeke et al., 2016). This project also gives good evidence for the importance of teachers’ knowledge of good models, analogies, explanations, examples and representations which is highlighted in section 1.3. Expert teachers have a wide repertoire of tasks and activities, their relative cognitive demands, and their effectiveness in various different situations (Baumert & Kunter, 2013). The report points out that it is this aspect of teaching that teachers are often expected to learn ​“on the job”, which means it can happen in rather an ad hoc nature, but that this knowledge can also be explicitly taught.

Section 1.4 concerns misconceptions, common errors, and types of strategies that students exhibit. The importance of a good understanding of this aspect is supported by many studies (Baumert et al., 2010; Blömeke et al., 2016; Hill et al., 2005; Hill and Chin, 2018) and is a feature of a number of effective teaching models (for example the Early Career Framework for England, 2019; and Hill et al., 2005). There are also various evidence-based approaches to addressing misconceptions (for example Braasch et al, 2013).

The report finishes Dimension 1 by noting that all of this knowledge is necessary but not sufficient for effective classroom practice: lesson structure and delivery are paramount. This may be why studies into these areas have shown limited impact as theoretical knowledge alone is not enough. There is much cross-over here with Dimension 4 which concerns classroom practices to activate hard thinking and this will be explored in a later article.

Deb Friis

Maths Research Associate and Sussex Maths Hub Secondary Co-Lead