This report draws insights on how the behavioral sciences could provide a lens to help us (1) better understand the problem of low foundational learning levels in low- and middle-income countries (LMICs) by shedding light on what influences teachers’ decision-making in the classroom, and (2) help shape solutions to improve foundational learning by supporting teachers to implement effective instructional practices.
Significantly improving foundational literacy and numeracy (FLN) outcomes at scale across LMICs remains a major challenge in education. Much is known about the sorts of instructional practices that can promote FLN. But given all we ask of teachers (research estimates that teachers typically make around 1,500 decisions in a single day), making it easy for them to take-up and implement effective instructional practices and do so consistently and at scale is critical.
In this report, we propose that the Integrative Model of Behavior Prediction can be a useful conceptual model to understand teacher behavior and take-up of instructional practices. Although the Model hasn’t been explicitly used in the design of FLN interventions to date, findings from many effective FLN interventions support its logic.
This synthesis report is designed to be used to stimulate discussion in the sector. A longer, companion report is available upon request for those that wish to explore any of the key messages in more depth. The longer report is split into 8 modules, each of which can be read alongside different sections of this shorter report. A breakdown of how this synthesis report relates to each of the full modules is provided below. A separate document with full references for both reports, as well as a list of acronyms and glossary of key terms is also available separately.
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This report is based on research funded by the Bill & Melinda Gates Foundation. The findings and conclusions contained within are those of Better Purpose and do not necessarily reflect positions or policies of the Bill & Melinda Gates Foundation.