Characterising effective teaching

This study exploits an existing dataset collected by the research team to improve our understanding of what effective teaching looks like in practice. The findings are expected to be of interest to those involved with teacher training and professional development, as well as those responsible for hiring teachers and scholars working in the field of educational effectiveness.

The dataset contains ratings from c.3,000 GCSE classroom observations carried out over two years by teachers from the same schools. They rated their colleagues using a modified version of the Danielson framework, a teaching evaluation tool that identifies those aspects of a teacher’s responsibilities shown through empirical studies to improve students’ learning, for example ‘managing student behaviour’ and ‘engaging students in learning’. They also recorded how lesson time was divided between 12 different activities, including ‘lecturing and dictation’ and ‘children working in groups’.

The dataset includes information on children’s demographic characteristics, prior test scores and GCSE grades, and the researchers also hope to link it to the National Pupil Database in order to include the A-level results and post-school destinations of the first of their two cohorts.

Machine learning techniques will be used to identify those ‘packages of practice’ most strongly correlated with pupil progress, as well as those associated with higher Danielson ratings from the teacher-observers. The ‘value added’ by individual teachers will be identified using the established approach described in Chetty et al. (2014).

The results of the analysis will be benchmarked against three additional sources: the UK Qualified Teacher Status standards for England; an alternative teacher evaluation methodology (MET) used for videoed lessons in New York; and a new online survey of the leading providers of university-based teacher training in England. Survey respondents will be asked to rank a range of in-class teacher tasks in order of their importance for boosting GCSE scores in English and Maths, and for supporting other outcomes, including success at university or in employment, and non-cognitive outcomes such as resilience.

Project details



Professor Simon Burgess, University of Bristol

Dr Shenila Rawal, Oxford Partnership for Education Research & Analysis (OPERA)

Dr Eric Taylor, Harvard University

Grant amount and duration:


October 2018 – September 2019