Social Research Methods Training Course

Duration 10 days 16 modules · 65 contact hours
Level Intermediate Certificate on completion
Who attends Monitoring and Evaluation Officers, Programme Managers and others
Fee from USD 2,200 KSh 190,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 9 Nov 2026 Course code SD-ME-085

Before you join: Participants should have experience working with development, humanitarian, public-service or social programmes and a basic understanding of programme objectives, indicators or reporting requirements.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Development and humanitarian decisions often depend on evidence collected under time pressure, with diverse populations and difficult access conditions. Poorly framed research questions, weak samples, leading interview questions or inconsistent analysis can produce findings that misdirect programme design, resource allocation and accountability reporting. Staff need to judge what evidence is credible, select methods that fit the decision, and explain the limits of findings clearly to donors, partners and affected communities.

This course develops practical social research skills for monitoring, evaluation, needs assessment, accountability and learning work. Participants move from a decision need to research questions, a theory of change, sampling strategy, data-collection instruments, fieldwork protocols, analysis and reporting. The course covers quantitative, qualitative and mixed-methods designs; probability and non-probability sampling; surveys, interviews, focus groups and observation; research ethics; data quality assurance; coding; descriptive statistics; and interpretation. Participants also apply OECD DAC evaluation criteria and establish appropriate approaches for inclusion, safeguarding, informed consent and data protection.

Teaching combines short instructor briefings with worked cases, instrument review, group analysis and structured application to participants' own programmes or realistic development and humanitarian scenarios. Participants develop a complete social research protocol during the course, including an evaluation matrix, sampling plan, data-collection tools, analysis plan and dissemination approach. Peer review sessions help participants identify methodological weaknesses before fieldwork begins and strengthen the practical usefulness of their proposed study.

The course suits professionals who commission, manage, conduct or use social research in programmes serving communities, public institutions, displaced populations and other groups affected by development or crisis response.

What you will be able to do

  • Formulate decision-focused research questions, objectives and measurable indicators
  • Construct theories of change and evaluation matrices for social research assignments
  • Select quantitative, qualitative and mixed-methods designs suited to research questions
  • Design probability and non-probability sampling strategies with defensible sample sizes
  • Develop survey questionnaires, interview guides, focus-group guides and observation checklists
  • Apply informed consent, safeguarding, confidentiality and data-protection procedures
  • Analyse qualitative codes and quantitative descriptive statistics to produce credible findings
  • Present a complete social research protocol with findings-use and dissemination plans

Benefits of attending

For you

  • Greater confidence commissioning and reviewing social research
  • A defensible approach to sampling and participant selection
  • Practical templates for ethical fieldwork and consent
  • Stronger interpretation of qualitative and quantitative findings
  • A complete protocol ready for adaptation to work assignments

For your organisation

  • Better evidence for programme adaptation, targeting and resource decisions
  • More credible evaluations, assessments and donor reports
  • Reduced risk from unethical consent, safeguarding and data practices
  • Consistent research standards across teams and implementing partners
  • Clearer pathways from findings to management action

Course modules

16 modules over 10 days

Participants can convert a programme decision need into focused, answerable research questions.

  • Decision-focused research purpose statements linked to programme management actions
  • Distinguishing research questions, evaluation questions, indicators and assumptions
  • FINER criteria used to test feasible research questions
  • Problem trees separating causes, effects and evidence gaps
  • Stakeholder mapping for users, participants, gatekeepers and decision-makers
  • Research objectives written with scope, population and intended use

Participants can build an evaluable theory of change and evaluation matrix.

  • Theory of Change links among activities, outputs, outcomes and impact
  • Assumptions and external factors tested through research evidence
  • OECD DAC criteria translated into context-specific evaluation questions
  • Evaluation matrices linking questions, indicators, sources and methods
  • Contribution analysis for plausible programme influence claims
  • Indicator reference sheets defining measures, disaggregation and calculation rules

Participants can select and justify a research design matched to the evidence required.

  • Cross-sectional, longitudinal and comparative designs matched to decision needs
  • Experimental and quasi-experimental designs for attribution questions
  • Case study design using multiple evidence sources
  • Mixed-methods sequencing, integration and triangulation decisions
  • Rapid assessment designs balancing timeliness, depth and methodological limits
  • Design rationales documenting feasibility, validity and resource constraints

Participants can operationalise social concepts into measurable variables and indicators.

  • Construct definitions separating abstract concepts from observable measures
  • Variables classified as nominal, ordinal, interval and ratio
  • Operational definitions specifying population, unit, timeframe and threshold
  • Validity types: face, content, construct and criterion validity
  • Reliability assessed through consistency, stability and inter-rater agreement
  • Disaggregation choices for sex, age, disability, location and status

Participants can define a sampling frame and choose an appropriate sampling approach.

  • Target population, accessible population and sampling frame distinctions
  • Unit of analysis selected at individual, household, group or facility levels
  • Probability sampling principles: known selection chance and random selection
  • Non-probability sampling uses, limitations and transparent justification
  • Sampling error, non-sampling error and implications for findings
  • Inclusion strategies for underrepresented and hard-to-reach populations

Participants can produce a probability sample plan with stated assumptions and limitations.

  • Simple random sampling using complete and verified sampling frames
  • Systematic sampling intervals calculated from population size and sample target
  • Stratified sampling for meaningful subgroup estimates and comparison
  • Cluster sampling for dispersed populations and constrained field access
  • Sample-size assumptions: confidence level, margin of error and prevalence
  • Design effect, non-response inflation and finite population correction

Participants can plan purposeful qualitative sampling that supports credible interpretation.

  • Purposive sampling criteria aligned with research questions and variation
  • Maximum variation sampling across relevant participant characteristics
  • Criterion sampling for participants with defined experience or exposure
  • Snowball sampling safeguards for hidden or sensitive populations
  • Theoretical sampling decisions during iterative qualitative inquiry
  • Saturation assessed through recurring themes and diminishing new information

Participants can draft a clear, measurable and field-ready survey questionnaire.

  • Questionnaire flow moving from screening to sensitive demographic questions
  • Closed questions designed with mutually exclusive response categories
  • Likert scales balanced for direction, labels and response options
  • Recall periods matched to events, services and respondent memory
  • Leading, double-barrelled and loaded questions identified and rewritten
  • Cognitive interviewing used to test respondent understanding before deployment

Participants can design qualitative data-collection guides for individual and group methods.

  • Semi-structured interview guides built from questions, probes and transitions
  • Funnel questioning moves from broad experience to specific evidence
  • Focus-group composition planned for safety, participation and shared experience
  • Moderation techniques manage dominant speakers, silence and disagreement
  • Observation checklists distinguish behaviours, conditions and researcher interpretations
  • Field notes capture context, verbatim statements and analytic reflections

Participants can apply ethical safeguards throughout a social research assignment.

  • Informed consent procedures covering purpose, risks, benefits and withdrawal
  • Assent and guardian consent requirements for research involving children
  • Do-no-harm assessment addressing distress, stigma, retaliation and exclusion
  • Safeguarding referral protocols for disclosures of abuse or exploitation
  • Confidentiality measures separating identifiers from research responses
  • Data minimisation, access controls and retention schedules under GDPR principles

Participants can prepare fieldwork systems that prevent, detect and correct data-quality problems.

  • Fieldwork plans assigning teams, routes, targets, supervision and escalation
  • Enumerator training covering protocols, neutrality, consent and safeguarding
  • Pilot testing instruments for timing, comprehension and response patterns
  • Back-checks and spot-checks used to verify completed interviews
  • Data-quality dimensions: accuracy, completeness, timeliness, consistency and validity
  • Daily debriefs identify emerging risks, errors and instrument revisions

Participants can prepare quantitative data and generate defensible descriptive findings.

  • Codebooks documenting variable names, labels, values and missing-data rules
  • Data cleaning checks for duplicates, ranges, skips and logical consistency
  • Frequency tables used to inspect distributions and response completeness
  • Central tendency measures: mean, median and mode selection
  • Cross-tabulations comparing groups with percentages, bases and caveats
  • Charts selected for categorical, time-series and distributional data

Participants can code qualitative data and develop evidence-based themes.

  • Transcription standards preserving meaning, pauses, anonymity and contextual notes
  • Inductive coding generates labels from participants' accounts and observations
  • Deductive coding applies a predefined framework or evaluation matrix
  • Codebooks define code names, inclusion criteria and exclusions
  • Thematic analysis identifies patterns, contrasts, exceptions and explanatory mechanisms
  • Framework matrices compare themes across participant groups and locations

Participants can judge evidence quality and make appropriately bounded interpretations.

  • Triangulation compares methods, sources, researchers and theoretical explanations
  • Researcher reflexivity records assumptions, positionality and influence on interpretation
  • Selection bias, social desirability bias and recall bias assessed
  • Negative case analysis tests themes against contradictory evidence
  • Confidence intervals interpreted without overstating statistical certainty
  • Limitations statements distinguish evidence gaps from programme performance findings

Participants can communicate findings clearly and connect recommendations to management action.

  • Finding statements combine evidence, interpretation, scope and confidence
  • Evidence tables link claims to data sources and methodological limits
  • Recommendations specify action, owner, timeframe and required resources
  • Results chains connect findings to programme adaptation decisions
  • Evaluation reports structured around questions, methods, findings and conclusions
  • Dissemination plans tailor products for communities, managers, donors and partners

Participants can build, review and present a complete social research protocol for a defined programme question.

  • Research protocol integrates purpose, questions, design and theory of change
  • Evaluation matrix aligns questions, indicators, sources, methods and analysis
  • Sampling plan states frame, selection method, size and limitations
  • Data-collection instruments demonstrate neutral wording and ethical safeguards
  • Analysis plan specifies codes, tables, comparisons and triangulation procedures
  • Peer review tests feasibility, credibility, safeguarding and decision usefulness

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Decision-focused research question template
  2. Theory of Change and evaluation matrix
  3. Probability and qualitative sampling plan
  4. Survey questionnaire and interview-guide templates
  5. Research ethics and fieldwork quality checklist
  6. Complete social research protocol

Who should attend

  • Monitoring and Evaluation Officers — need defensible designs and credible evidence for programme decisions
  • Programme Managers — need to commission and use research without misreading findings
  • Evaluation Managers — need to oversee evaluation questions, methods, quality and reporting
  • Humanitarian Needs Assessment Staff — need rapid but ethical approaches to primary data collection
  • Research Officers — need stronger sampling, instrument design, analysis and reporting methods
  • Donor Programme Staff — need to assess research quality and evidence claims from implementers

Skills and tools covered

Research designSampling strategyQualitative interviewingSurvey designData analysisEvaluation reporting

Tools and standards

Theory of Change, OECD DAC evaluation criteria, FINER criteria, GDPR principles

How the course runs

Training methodology

Instructor briefings introduce each method before participants apply it to development and humanitarian cases. Small groups compare research designs, construct sampling approaches, critique questionnaires, code qualitative material and interpret datasets. Simulations address consent, interviewer bias, difficult interviews and fieldwork quality checks. Participants progressively build a protocol for their own assignment or a supplied case, receiving instructor and peer feedback at defined review points. Facilitated discussions connect methodological choices to donor requirements, community accountability and programme decision-making.

Requirements and prerequisites

Participants should have experience working with development, humanitarian, public-service or social programmes and a basic understanding of programme objectives, indicators or reporting requirements. They should be comfortable reading tables, percentages and short reports. Prior involvement in surveys, interviews, assessments or evaluations is useful but not essential. The course does not require advanced statistics, statistical software expertise, prior academic research training or a university qualification in social science. Participants may bring an active research question, programme document or draft terms of reference.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

You should understand the programme area in which you work and be able to read basic tables and percentages. Previous research experience is helpful but not required; advanced statistics and statistical software are not assumed.

Bring a current programme document, draft terms of reference, indicator framework or research question if you have one. These materials can be used to develop a practical protocol during the course.

It is intended for M&E, programme, research, evaluation and assessment staff in development, humanitarian, public-sector and NGO settings. It is also useful for managers who commission research and need to judge methodological quality.

This course concentrates on the social research methods used to collect, analyse and interpret evidence. It includes M&E and evaluation applications, but gives greater attention to sampling, instruments, qualitative inquiry, ethics and data quality.

Participants build a research protocol that can be adapted for an assessment, evaluation, baseline, survey or qualitative study. The templates support review of consultant proposals, partner research plans and internal data-collection activities.

The first week establishes research design, measurement, sampling and data-collection methods. The second week focuses on ethics, fieldwork management, analysis, interpretation, reporting and a final protocol presentation; each day runs from 08:30 to 16:30 with about 6.5 contact hours.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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