Monitoring, Evaluation, Accountability and Learning Training Course

Duration 10 days 20 modules · 65 contact hours
Level Intermediate Certificate on completion
Who attends MEAL Officers and Coordinators, 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-083

Before you join: Participants should have experience contributing to development or humanitarian projects, such as implementation, reporting, grants management, technical support or community engagement.

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 programmes must show more than activities completed and funds spent. Donors, affected people, delivery partners and senior managers need credible evidence that assistance reached intended groups, met priority needs, caused no avoidable harm and informed timely decisions. Weak indicator design, poor data quality, inaccessible feedback channels and delayed analysis can result in programmes continuing despite limited results or unresolved community concerns.

This course develops the practical Monitoring, Evaluation, Accountability and Learning (MEAL) capability needed to design, manage and use evidence throughout the programme cycle. Participants work through theories of change, logframes, indicator reference sheets, baseline planning, sampling, data collection, data quality assurance, evaluation design, community feedback and complaints mechanisms, and learning processes. The course uses OECD DAC evaluation criteria, Core Humanitarian Standard commitments and Sphere guidance to connect technical methods with accountability duties.

Participants apply each method to a realistic development or humanitarian programme case, building work from the first week and improving it as new methods are introduced. Short instructor briefings are followed by case analysis, group assignments, data interpretation, decision simulations and structured peer review. Each participant leaves with a complete MEAL package: a theory of change, results framework, indicator plan, data collection approach, feedback mechanism, data quality plan and learning agenda ready for adaptation to their own programme.

The course suits programme, MEAL, grants, technical and operational staff who already contribute to project delivery and now need to lead or strengthen evidence and accountability systems. It is particularly relevant for staff working with government services, NGOs, UN agencies, donor-funded programmes, implementing partners and humanitarian response teams.

What you will be able to do

  • Construct a theory of change and logframe with testable causal assumptions
  • Develop indicator reference sheets with disaggregation, targets, sources and collection methods
  • Prepare a baseline and endline plan using appropriate sampling and data collection methods
  • Apply data quality assessments to identify and correct evidence weaknesses
  • Design an evaluation using OECD DAC criteria, evaluation questions and mixed methods
  • Establish accountable feedback and complaints mechanisms aligned with CHS commitments
  • Analyse quantitative and qualitative findings for programme decisions and learning products
  • Present a complete MEAL plan for a development or humanitarian programme

Benefits of attending

For you

  • Produce credible indicator definitions that reduce inconsistent field reporting
  • Plan baselines, endlines and evaluations with defensible methods and budgets
  • Identify data quality problems before findings reach donors or management
  • Handle community feedback as evidence for service improvement and safeguarding escalation
  • Present evidence-based recommendations with clear limits, assumptions and actions

For your organisation

  • Improved donor reporting through traceable indicators, sources and verification records
  • Earlier detection of delivery gaps through routine monitoring and disaggregated analysis
  • More accountable services through functioning feedback, complaints and response procedures
  • Better evaluation commissioning through clear questions, methods and management arrangements
  • Documented learning that informs programme adaptation, proposal design and partner support

Course modules

20 modules over 10 days

Participants can define MEAL functions and connect evidence responsibilities to programme decisions.

  • MEAL functions linked to programme decisions, adaptation and stakeholder obligations
  • Distinguishing monitoring, evaluation, accountability and learning responsibilities within delivery teams
  • Results chains from inputs through activities, outputs, outcomes and impact
  • Donor, government and community evidence requirements mapped against programme cycles
  • Ethical evidence principles: relevance, proportionality, transparency and confidentiality
  • Decision calendars connecting field data, management reviews and donor reporting

Participants can frame evidence needs using context, stakeholder and risk analysis.

  • Problem trees separating root causes, immediate causes and visible effects
  • Stakeholder mapping by influence, interest, exclusion risk and information needs
  • Gender, age and disability analysis informing disaggregation and participation priorities
  • Conflict sensitivity using dividers, connectors and do-no-harm analysis
  • Seasonal calendars identifying timing risks for services, data collection and access
  • Assumption registers recording external conditions required for intended results

Participants can develop a testable theory of change for a defined programme problem.

  • Theory of change statements linking interventions to intended behavioural or systems change
  • Backward mapping from impact to outcomes, outputs and enabling activities
  • Causal pathways tested through evidence, assumptions and alternative explanations
  • Preconditions identified for each outcome pathway and delivery sequence
  • Articulating assumptions as observable propositions rather than untested beliefs
  • External risks separated from internal implementation assumptions and controls

Participants can construct a results framework that supports monitoring and reporting.

  • Logframe hierarchy aligned with theory of change causal pathways
  • Outcome and output statements written as measurable changes or deliverables
  • Objectively verifiable indicators matched to each results level
  • Means of verification assessed for feasibility, frequency, ownership and cost
  • Risk columns maintained through programme reviews and adaptation decisions
  • Results frameworks reconciled with donor templates without weakening causal logic

Participants can specify valid indicators and document consistent measurement procedures.

  • SMART indicator tests applied beyond vague output-counting measures
  • Indicator reference sheets defining numerator, denominator, unit and interpretation
  • Disaggregation requirements set by sex, age, disability, location and status
  • Proxy indicators selected when direct outcome measurement is impractical
  • Targets established from baselines, standards, capacity and implementation timelines
  • Indicator limitations documented with likely bias and intended mitigation actions

Participants can prepare a workable monitoring plan with clear roles and schedules.

  • Monitoring plans linking indicators, tools, frequencies, responsibilities and reporting deadlines
  • Data flow diagrams tracing collection, review, approval, storage and use
  • RACI matrices clarifying MEAL, programme, partner and management accountabilities
  • Field monitoring schedules balanced against access constraints and programme milestones
  • Monitoring budgets covering enumerators, travel, translation, devices and analysis
  • Partner reporting requirements aligned with shared definitions and verification procedures

Participants can plan a baseline study that establishes credible starting values.

  • Baseline purposes distinguished from needs assessments, registration and routine monitoring
  • Population definitions set for beneficiaries, comparison groups and sampling frames
  • Sample size drivers: precision, confidence, variability, design effect and attrition
  • Target setting based on baseline values, benchmarks and programme contribution
  • Baseline terms of reference specifying questions, methods, governance and deliverables
  • Timing decisions account for seasonality, implementation sequence and recall periods

Participants can select and justify sampling approaches for common MEAL questions.

  • Probability sampling methods: simple random, systematic, stratified and cluster samples
  • Purposive sampling for key informants, maximum variation and critical cases
  • Sampling frames assessed for coverage errors, duplication and population changes
  • Stratification used to examine equity gaps among priority population groups
  • Non-response risks managed through call-backs, replacement rules and documentation
  • Sample selection procedures recorded for reproducibility and audit trails

Participants can design quantitative collection processes that produce usable monitoring data.

  • Survey questions structured to avoid ambiguity, double-barrelling and leading wording
  • Questionnaire flow tested through skip logic, filters and response options
  • KoboToolbox forms configured with constraints, required fields and validation checks
  • Enumerator briefings cover consent, neutrality, privacy and referral procedures
  • Daily field checks identify missing values, outliers and interviewer patterns
  • Codebooks document variables, labels, response categories and derived indicators

Participants can use qualitative methods to investigate experiences, mechanisms and unintended effects.

  • Key informant interviews planned around expertise, role and information gaps
  • Focus group discussions segmented to reduce power imbalances and disclosure risks
  • Semi-structured guides use open questions, probes and neutral sequencing
  • Participatory tools include community mapping, ranking, timelines and transect walks
  • Thematic coding converts interview notes into evidence patterns and exceptions
  • Triangulation compares qualitative accounts with monitoring data and document review

Participants can assess data quality and implement corrective actions before reporting.

  • Data quality dimensions: validity, reliability, precision, integrity and timeliness
  • Routine data quality assessments trace reported figures to source documents
  • Verification factor calculations compare source totals against reported results
  • Spot checks test attendance lists, distribution records and service registers
  • Outlier analysis flags implausible values, duplicates and sudden reporting shifts
  • Corrective action logs assign owners, deadlines and evidence of resolution

Participants can protect participants and manage sensitive MEAL information responsibly.

  • Informed consent procedures distinguish participation, recording and data-sharing permissions
  • Data minimisation limits collection to information required for stated purposes
  • Sensitive data classifications guide access controls, retention and destruction schedules
  • Safeguarding referral pathways prepared before collecting protection-related disclosures
  • Anonymisation techniques remove direct identifiers and reduce re-identification risks
  • Research ethics reviews assess risks, benefits, consent and vulnerable participants

Participants can analyse MEAL data and communicate findings without overstating claims.

  • Descriptive statistics calculate counts, proportions, means, medians and percentage changes
  • Cross-tabulations reveal differences by sex, age, disability and location
  • Trend charts compare results against targets, baselines and reporting periods
  • Qualitative matrices organise themes, quotations, sources and contradictory evidence
  • Contribution claims distinguish plausible influence from proven attribution
  • Evidence statements separate findings, interpretations, limitations and recommendations

Participants can design or commission an evaluation with useful questions and credible methods.

  • OECD DAC criteria translated into focused evaluation questions and judgement criteria
  • Evaluation matrices align questions, indicators, sources, methods and analysis plans
  • Process, outcome and impact evaluations matched to programme maturity and purpose
  • Mixed-method designs integrate quantitative estimates with explanatory qualitative evidence
  • Terms of reference specify scope, independence, ethics, deliverables and governance
  • Evaluator selection criteria assess technical expertise, context knowledge and conflicts

Participants can design accountability arrangements that enable informed participation and response.

  • Core Humanitarian Standard commitments translated into programme accountability actions
  • Information-sharing plans specify languages, channels, content and accessibility standards
  • Community participation mapped across assessment, design, delivery and review stages
  • Feedback channels assessed for safety, confidentiality, inclusion and accessibility
  • Complaints categories separate enquiries, dissatisfaction, fraud and safeguarding concerns
  • Closing feedback loops communicates decisions, actions and unresolved constraints

Participants can establish a feedback and complaints system with documented response controls.

  • Standard operating procedures define intake, triage, investigation, response and closure
  • Case registers capture category, location, consent, action owner and status
  • Service standards set acknowledgement and resolution timeframes by complaint severity
  • Escalation pathways protect confidentiality for fraud, exploitation and abuse allegations
  • Root cause analysis identifies recurring service failures behind feedback trends
  • Monthly dashboards report volumes, response times, outcomes and unresolved cases

Participants can convert evidence into documented learning and programme adaptation decisions.

  • Learning agendas prioritise uncertainties with high consequences for programme decisions
  • After-action reviews identify intended results, actual results and causal factors
  • Pause-and-reflect sessions convert monitoring findings into action commitments
  • Decision logs record evidence considered, choices made, owners and review dates
  • Learning products include briefs, learning notes, dashboards and management summaries
  • Adaptation triggers define thresholds requiring programme review or design changes

Participants can prepare decision-focused MEAL reports for different stakeholders.

  • Results reports compare achievements, targets, explanations and corrective actions
  • Donor narratives connect indicator data with implementation evidence and expenditure context
  • Dashboard design prioritises decision-relevant measures over excessive activity counts
  • Data visualisations use clear labels, denominators, sources and reporting periods
  • Management briefings present options, implications, risks and requested decisions
  • Community reporting shares findings in accessible language and appropriate formats

Participants can manage shared MEAL responsibilities with implementing partners.

  • Partner capacity assessments examine systems, skills, tools, staffing and governance
  • Capacity development plans sequence coaching, templates, observation and follow-up reviews
  • Data-sharing agreements define ownership, access, protection and publication arrangements
  • Joint monitoring visits use standard checklists and documented follow-up actions
  • Governance forums review evidence quality, accountability issues and adaptation decisions
  • Escalation protocols address persistent reporting delays, quality failures and non-compliance

Participants can build, review and present a complete MEAL package for a defined programme.

  • Programme scenario translated into a theory of change and results framework
  • Indicator reference sheets specify measures, targets, disaggregation and verification sources
  • Monitoring plan assigns workflows, responsibilities, tools, frequencies and quality controls
  • Baseline, sampling and data collection choices justified against programme constraints
  • Feedback mechanism includes channels, case handling standards and closure reporting
  • Learning agenda links evidence questions, review moments, decisions and adaptations
  • Peer review tests coherence, feasibility, accountability and evidence-use arrangements

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

What you take back to work

  1. Theory of change and logframe template
  2. Indicator reference sheet template
  3. MEAL plan and data flow model
  4. Data quality assessment checklist
  5. Feedback and complaints standard operating procedure
  6. Evaluation terms of reference template

Who should attend

  • MEAL Officers and Coordinators — responsible for monitoring systems, evidence quality and reporting
  • Programme Managers — need evidence to manage delivery, adaptation and partner performance
  • Project Officers — collect and use programme data within implementation teams
  • Monitoring and Evaluation Specialists — need stronger accountability and learning methods
  • Grants and Compliance Staff — assess indicator commitments, donor reporting and verification evidence
  • Technical Advisers — use evidence to improve sector approaches and implementation quality

Skills and tools covered

Results-based monitoringIndicator designEvaluation planningData quality assuranceCommunity accountabilityAdaptive learning

Tools and standards

OECD DAC evaluation criteria, Core Humanitarian Standard, Sphere Handbook, KoboToolbox

How the course runs

Training methodology

The course combines concise instructor briefings with realistic programme cases from humanitarian response and development delivery. Participants build MEAL components in stages, test decisions against donor, community and management requirements, and review sample datasets, reports and feedback records. Group work examines design choices and implementation constraints; simulations cover data quality checks, feedback response and evaluation planning. Facilitated peer review helps participants improve their own programme materials. Individual application planning links each method to a current workplace responsibility.

Requirements and prerequisites

Participants should have experience contributing to development or humanitarian projects, such as implementation, reporting, grants management, technical support or community engagement. They should understand basic project concepts including objectives, activities, outputs and stakeholders, and be comfortable reading simple tables and percentages. Prior responsibility for a monitoring system is helpful but not required. The course does not require advanced statistics, specialist evaluation qualifications, coding skills or prior use of statistical software. Participants should bring a current or recent programme document if they want to adapt course outputs to their own work.

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 basic project delivery and have some exposure to programme reporting, implementation or stakeholder engagement. Advanced statistics, evaluation qualifications and statistical software experience are not required.

Bring a current or recent project proposal, logframe, monitoring plan or donor report if you have one. You can use it as the basis for adapting templates and planning outputs during the course.

It is designed for MEAL staff, programme managers, project officers, grants staff and technical advisers in development and humanitarian organisations. It also suits staff who supervise implementing partners or commission evaluations.

This course links routine monitoring and evaluation with accountability to affected people and structured organisational learning. Participants learn how these functions operate together as one programme evidence system.

The methods produce practical materials such as indicator sheets, data quality checks, feedback procedures and evaluation terms of reference. These can be adapted to active projects, partner support plans and donor reporting cycles.

Each training day runs from 08:30 to 16:30 and provides about 6.5 contact hours. The first week builds programme design, monitoring and data collection materials; the second week covers evaluation, accountability, learning, governance and the final capstone presentation.

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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