Data Must Speak: Unpacking Factors Influencing School Performance in Nepal

Data Must Speak: Unpacking Factors Influencing School Performance in Nepal

Published: 2022 Innocenti Research Report

Joint efforts by the Government of Nepal, development partners and key stakeholders to achieve SDG 4 by 2030 have improved education access, participation and retention. However, learning outcomes in Nepal remain stagnant.

What resources and contextual factors are associated with good school performance in Nepal? By merging and analyzing existing administrative datasets in Nepal, this report helps to identify positive deviant schools – those that outperform other schools despite sharing similar contexts and resources.

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 being 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.

Theory of Change: Methodological Briefs - Impact Evaluation No. 2

Theory of Change: Methodological Briefs - Impact Evaluation No. 2

AUTHOR(S)
Patricia Rogers

Published: 2014 Methodological Briefs
A theory of change explains how activities are understood to produce a series of results that contribute to achieving the final intended impacts. It can be developed for any level of intervention – an event, a project, a programme, a policy, a strategy or an organization. In an impact evaluation, a theory of change is useful for identifying the data that need to be collected and how they should be analysed. It can also provide a framework for reporting.
Overview: Data Collection and Analysis Methods in Impact Evaluation: Methodological Briefs - Impact Evaluation No. 10

Overview: Data Collection and Analysis Methods in Impact Evaluation: Methodological Briefs - Impact Evaluation No. 10

AUTHOR(S)
Greet Peersman

Published: 2014 Methodological Briefs
Impact evaluations need to go beyond assessing the size of the effects (i.e., the average impact) to identify for whom and in what ways a programme or policy has been successful. What constitutes ‘success’ and how the data will be analysed and synthesized to answer the specific key evaluation questions (KEQs) must be considered up front as data collection should be geared towards the mix of evidence needed to make appropriate judgements about the programme or policy. This brief provides an overview of the issues involved in choosing and using data collection and analysis methods for impact evaluations.
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