Understanding factors that influence Teaching at the Right Level’s effectiveness and generalisability: a Bayesian evidence synthesis
Programme of work
Enhancing evidence transferability
Principal investigator(s)
Noam Angrist
Host institution
Young 1ove Organization
Other institutions
London School of Economics
Dates
February 2020 to July 2021
Project type
Evidence synthesis
Country/ies
All the countries where the Teaching at the Right Level (TaRL) intervention has been rolled out.
Research question
This study is a systematic assessment of which programme compo-nents and contextual factors are most decisive for the success of TaRL, a remedial education intervention to improve learning.
Research design
This project will employ a Bayesian hierarchical approach to synthesise the evidence. This approach will assess generalisability across settings and unpack the relative importance of the differing features of the TaRL programmes and study contexts. The analysis will estimate the average treatment effect across all studies and the variance across contexts.
Data source
The study will draw on raw data from existing trials of TaRL interven-tions
Policy relevance
This study will:
- Advance knowledge on what works to improve learning outcomes;
- Develop methodology to synthesise and understand complex interventions through middle-range theory; and
- Test an innovative combination of methods to inform generalizability that can be applied to future interventions.
Study findings can inform efforts to scale up TaRL in several countries.
Project Outputs
- CEDIL syntheses working paper: The role of implementation in generalisability: A synthesis of evidence on targeted educational instruction and a new randomised trial
- CEDIL evidence brief: Translating effective education approaches, such as targeted instruction, across contexts
- CEDIL conference 2022: Maintaining Learning During the Pandemic