Data Must Speak: What can we learn about the practices and behaviours of highly effective schools in the Lao People’s Democratic Republic?

Data Must Speak: What can we learn about the practices and behaviours of highly effective schools in the Lao People’s Democratic Republic?

AUTHOR(S)
UNICEF Innocenti; UNICEF Lao PDR; Ministry of Education and Sports Lao People’s Democratic Republic

Published: 2023 Innocenti Research Report

While the Lao People’s Democratic Republic has made steady progress in expanding access to quality education, many children still leave primary school with difficulties in reading and writing for their age. Despite this, there are ‘positive deviant’ schools that outperform other schools located in similar contexts and with an equivalent level of resources.

This report presents important insights from both quantitative and qualitative data on behaviours and practices of a variety of education actors in positive deviant schools in Lao PDR. It also explores existing local solutions and broader evidence emerging from all schools on various education-related challenges.

Data Must Speak – a global initiative implemented since 2014 – aims to address the evidence gaps to mitigate the learning crisis using existing data. The DMS Positive Deviance research is co-created and co-implemented with Ministries of Education and key partners. DMS research relies on mixed methods and innovative approaches (i.e., positive deviance approach, behavioural sciences, implementation research and scaling science) to generate knowledge and practical lessons about ‘what works’, ‘why’ and ‘how’ to scale grassroots solutions for national policymakers and the broader international community of education stakeholders.

DMS research is currently implemented in 14 countries: Brazil, Burkina Faso, Chad, Cote d'Ivoire, Ethiopia, Ghana, the Lao People’s Democratic Republic, Madagascar, Mali, Nepal, Niger, the United Republic of Tanzania, Togo and Zambia.

Cite this publication | No. of pages: 70 | Thematic area: Education | Tags: child education, data analysis, schooling
Data Must Speak: Exploring school climate in Lao schools

Data Must Speak: Exploring school climate in Lao schools

AUTHOR(S)
UNICEF Innocenti; UNICEF Lao PDR; Ministry of Education and Sports Lao People’s Democratic Republic

Published: 2023 Innocenti Research Briefs

While the Lao People’s Democratic Republic has made steady progress in expanding access to quality education, many children still leave primary school with difficulties in reading and writing for their age. Despite this, there are ‘positive deviant’ schools that outperform other schools located in similar contexts and with an equivalent level of resources.

This policy brief – about school climate in Lao schools – is part of a series that presents important insights from both quantitative and qualitative data on behaviours and practices of a variety of education actors in positive deviant schools in Lao PDR. It also explores existing local solutions and broader evidence emerging from all schools on various education-related challenges.

Data Must Speak – a global initiative implemented since 2014 – aims to address the evidence gaps to mitigate the learning crisis using existing data. The DMS Positive Deviance research is co-created and co-implemented with Ministries of Education and key partners. DMS research relies on mixed methods and innovative approaches (i.e., positive deviance approach, behavioural sciences, implementation research and scaling science) to generate knowledge and practical lessons about ‘what works’, ‘why’ and ‘how’ to scale grassroots solutions for national policymakers and the broader international community of education stakeholders.

DMS research is currently implemented in 14 countries: Brazil, Burkina Faso, Chad, Cote d'Ivoire, Ethiopia, Ghana, the Lao People’s Democratic Republic, Madagascar, Mali, Nepal, Niger, the United Republic of Tanzania, Togo and Zambia.

Cite this publication | No. of pages: 5 | Thematic area: Education | Tags: child education, data analysis, schooling
Data Must Speak: Moving towards a culture of assessment for learning in Lao schools

Data Must Speak: Moving towards a culture of assessment for learning in Lao schools

AUTHOR(S)
UNICEF Innocenti; UNICEF Lao PDR; Ministry of Education and Sports Lao People’s Democratic Republic

Published: 2023 Innocenti Research Briefs

While the Lao People’s Democratic Republic has made steady progress in expanding access to quality education, many children still leave primary school with difficulties in reading and writing for their age. Despite this, there are ‘positive deviant’ schools that outperform other schools located in similar contexts and with an equivalent level of resources.

This policy brief – about practices aligned with formative assessment in Lao schools – is part of a series that presents important insights from both quantitative and qualitative data on behaviors and practices of a variety of education actors in positive deviant schools in Lao PDR. It also explores existing local solutions and broader evidence emerging from all schools on various education-related challenges.

Data Must Speak – a global initiative implemented since 2014 – aims to address the evidence gaps to mitigate the learning crisis using existing data. The DMS Positive Deviance research is co-created and co-implemented with Ministries of Education and key partners. DMS research relies on mixed methods and innovative approaches (i.e., positive deviance approach, behavioural sciences, implementation research and scaling science) to generate knowledge and practical lessons about ‘what works’, ‘why’ and ‘how’ to scale grassroots solutions for national policymakers and the broader international community of education stakeholders.

DMS research is currently implemented in 14 countries: Brazil, Burkina Faso, Chad, Cote d'Ivoire, Ethiopia, Ghana, the Lao People’s Democratic Republic, Madagascar, Mali, Nepal, Niger, the United Republic of Tanzania, Togo and Zambia.

Cite this publication | No. of pages: 5 | Thematic area: Education | Tags: child education, data analysis, schooling
1 - 3 of 3
first previus 1 next last