Monitoring and Evaluation Fundamentals for Development Projects Training Course

Course overview

Development projects are often required to demonstrate results to donors, communities, government counterparts, and senior management, yet teams can struggle to convert a proposal logframe into practical monitoring routines and credible evaluation evidence. Weak indicators, inconsistent baseline data, unclear responsibilities, and reporting focused on activities rather than outcomes can lead to poor management decisions and contested claims of impact. This course helps participants build an M&E system that produces timely, usable information throughout the project cycle.

Participants learn to apply the results chain, theory of change, logical framework, indicator reference sheet, data collection plan, and evaluation questions to a development or humanitarian project. They practise defining SMART indicators, setting disaggregations and targets, selecting data sources, designing practical collection tools, checking data quality, analysing monitoring findings, and communicating results. The course also addresses ethical data collection, informed consent, safeguarding considerations, feedback mechanisms, and the OECD DAC evaluation criteria.

Training combines instructor-led explanation with worked examples from livelihoods, health, education, protection, and resilience programmes. Participants work through a continuing project case, critique sample indicators and reports, build data-collection instruments, and conduct a data-quality review. Each participant leaves with an M&E starter pack for a selected project: a results framework, indicator performance tracking table, indicator reference sheet, data collection and reporting plan, and outline terms of reference for an evaluation.

The course is designed for programme staff who already work with project plans, donor reports, community data, or implementation partners and need a reliable grounding in practical M&E. It is equally valuable for managers approving project designs and seeking more defensible evidence for adaptive management and accountability.

Course objectives

By the end of this course, participants will be able to:

• Construct a project results chain linking inputs, activities, outputs, outcomes, and intended impact
• Develop a theory of change with assumptions, risks, and evidence needs
• Write SMART output and outcome indicators with defined units, disaggregation, targets, and frequency
• Produce indicator reference sheets specifying definitions, sources, collection methods, and responsibilities
• Design a monitoring plan and indicator performance tracking table for a development project
• Create practical survey, observation, and focus-group data collection tools using KoboToolbox templates
• Conduct a data quality assessment using checks for validity, reliability, timeliness, precision, and integrity
• Draft evaluation questions and an evaluation terms-of-reference outline using OECD DAC criteria

Benefits of attending

Target competencies

Who should attend

• M&E Officers — who need to build and operate project monitoring systems and produce credible results reports
• Programme Officers — who translate implementation plans into measurable outputs, outcomes, and corrective actions
• Project Managers — who require timely performance evidence to manage delivery risks and donor commitments
• NGO Programme Coordinators — who oversee multiple field teams and need consistent indicator definitions and reporting routines
• Donor-Funded Project Staff — who must meet logframe, baseline, target, and narrative reporting requirements
• Humanitarian and Development Consultants — who support project design, evaluations, and partner capacity strengthening

Requirements and prerequisites

Participants should have experience working on, supporting, or reviewing a development or humanitarian project and should understand basic project concepts such as objectives, activities, outputs, workplans, and donor reporting. Familiarity with a project proposal, logframe, or results framework is helpful, as participants will use these documents in exercises. Basic spreadsheet skills, including entering data and using simple formulas in Microsoft Excel, are assumed. No prior formal M&E qualification, statistical software, coding ability, or experience conducting an evaluation is required. Complete beginners should expect a structured introduction with practical terminology and guided templates.

Training methodology

The five-day course uses short instructor-led modules followed by applied work on a continuing development-project case. Participants annotate a logframe, test a theory of change, rewrite weak indicators, build an indicator performance tracking table in Microsoft Excel, and configure a simple KoboToolbox collection form. Small groups review sample datasets, identify data-quality weaknesses, and prepare findings for a programme management meeting. Daily feedback connects each method to participants’ own projects. The final session includes an application-planning workshop that converts the course templates into a practical first-90-days M&E improvement plan.

Course outline

Day 1: Results-Based M&E Foundations

• Purpose of monitoring, evaluation, accountability, and learning in development projects
• Project cycle entry points for M&E design and use
• Results chains: inputs, activities, outputs, outcomes, and impact
• Theory of change pathways, assumptions, and external risks
• Logical framework structure and vertical logic testing
• Distinguishing outputs, outcomes, indicators, targets, and milestones
• Roles and responsibilities across programme, M&E, finance, and partner teams

Workshop: Participants diagnose the logic of a sample livelihoods project and produce a corrected results chain with assumptions and risks.

Day 2: Indicators, Baselines, and Targets

• SMART indicator design for output and outcome measurement
• Quantitative, qualitative, proxy, and composite indicators
• Indicator disaggregation by sex, age, disability, location, and vulnerability group
• Baseline, target, milestone, and endline measurement decisions
• Indicator reference sheet fields and standard definitions
• Means of verification and source-of-data selection
• Indicator performance tracking tables in Microsoft Excel

Workshop: Participants convert weak logframe statements into a set of defined indicators and complete two indicator reference sheets.

Day 3: Data Collection and Data Quality

• Monitoring data collection plans, calendars, and responsibility matrices
• Sampling basics for household surveys and beneficiary monitoring
• Survey question design, response options, and skip logic
• Observation checklists, key-informant interviews, and focus-group discussion guides
• KoboToolbox form structure and mobile data-collection workflow
• Informed consent, confidentiality, safeguarding, and do-no-harm controls
• Data quality assessment dimensions: validity, reliability, precision, integrity, and timeliness

Workshop: Participants build a short KoboToolbox monitoring form and conduct a data-quality assessment of a flawed partner dataset.

Day 4: Analysis, Reporting, and Adaptive Management

• Data cleaning checks and version control for monitoring datasets
• Descriptive analysis using counts, percentages, averages, and disaggregated comparisons
• Variance analysis against targets, milestones, and implementation plans
• Triangulation of quantitative monitoring data and qualitative evidence
• Dashboard and results-table design for management reporting
• Narrative reporting of progress, challenges, assumptions, and corrective actions
• Feedback loops, community accountability mechanisms, and adaptive management decisions

Workshop: Participants analyse a project monitoring dataset in Excel and produce a one-page results brief with recommended management actions.

Day 5: Evaluation Planning and Workplace Application

• When monitoring is sufficient and when an evaluation is required
• OECD DAC criteria: relevance, coherence, effectiveness, efficiency, impact, and sustainability
• Formulating evaluation purpose, users, questions, and evidence requirements
• Evaluation designs: baseline-endline, pre-post, comparison groups, and mixed methods
• Evaluation terms of reference, scope, deliverables, and evaluator selection criteria
• Using findings, management responses, and learning dissemination plans
• Ninety-day M&E system improvement planning

Workshop: Participants draft an evaluation TOR outline and a 90-day action plan for implementing their project M&E starter pack.

Tools & standards covered

Microsoft Excel, KoboToolbox, OECD DAC evaluation criteria, DCED Standard for Results Measurement

A typical training day

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

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions