84 short courses for development practitioners in South Asia

Master participatory approaches to community mobilization and asset-based development.

Master the specialized vocabulary and communication strategies for development work.

The logical framework, built from the results chain up: inputs to impact, indicators and SMART targets, means of verification, assumptions and risk, and how to build, test and critique the matrix.

Master the fundamentals of Monitoring, Evaluation, and Learning for development projects.

Master qualitative research techniques including interviews, focus groups, and ethnography.

Work through the ethical questions in development research and protect vulnerable populations.

Learn to design theories of change that set out the pathways to impact.

Attribution and the counterfactual: RCTs, difference-in-differences, regression discontinuity, power, and using evidence.

Combining quantitative and qualitative research: core designs, integration, and quality.

Questionnaires, sampling, modes and fieldwork quality: designing surveys that measure what you mean.

From the review question to PRISMA 2020: searching, screening, risk of bias, meta-analysis, GRADE and bibliometric mapping of a field.

From the thesis chapter to the journal article: argument, structure, clear sentences, tables and citations, the Indian PhD process, choosing a journal and surviving peer review.

Latent variables and CFA, reliability and validity, model fit read with judgement, mediation with bootstrapped effects, measurement invariance across languages, PLS-SEM, and what the arrows can and cannot claim.

The money that arrives from outside the budget: multilateral and bilateral lenders and how they decide, what a loan actually is, the shift from lending to de-risking private capital, India’s own architecture from NaBFID to asset monetisation, land and environmental law, climate finance accounting, and the complaint mechanisms affected communities can use.

NVivo, MAXQDA, ATLAS.ti and the free Taguette and QualCoder: transcripts in Indian languages, the coding workflow, queries and matrices, team agreement, mixed methods, rigour, and what to do about the AI features.

The research process from an answerable question to design, sampling, secondary data, ethics and write-up.

The logic of causal claims: counterfactuals, selection bias, randomisation, natural experiments and how to read a causal finding.

Design a programme from problem tree to implementation plan: targeting, theory of change, costing, risk and scale.

Freire to PRA, Gram Sabhas, social audits and Photovoice, with the evidence and the risks of elite capture.