Monitoring and Evaluation for Agricultural Extension Programmes Training Course

Course overview

Agricultural extension programmes need credible evidence that advisory services are reaching intended farmers, changing practices and contributing to better production, income, resilience or nutrition outcomes. Yet many teams collect attendance figures and farmer stories without a results framework, baseline, data-quality controls or a practical way to interpret whether extension methods are working. This course addresses the operational challenge of monitoring field agents, demonstration plots, farmer field schools, digital advisory channels and producer groups while producing evidence that programme managers, funders and government counterparts can use.

Participants learn to build an agriculture-specific monitoring and evaluation system from programme theory to reporting. They develop results chains and logframes; define SMART indicators for reach, adoption, yield, women’s participation, climate-smart practice uptake and service quality; design baseline and endline approaches; construct sampling plans; and prepare mobile data-collection instruments. The course also covers OECD DAC evaluation criteria, data-quality assessments, disaggregation by sex, age and location, descriptive analysis in Excel, dashboard design and evidence-based recommendations.

Instruction combines facilitator-led technical sessions with a running agricultural extension case involving smallholder farmers, frontline extension workers and demonstration sites. Participants work with sample datasets, KoboToolbox forms and reporting templates to diagnose weak indicators, clean field data and present findings to decision-makers. Each participant leaves with an M&E package for an agricultural extension programme: a results framework, indicator reference sheet, data-collection plan, sample questionnaire, reporting dashboard specification and a 90-day implementation plan.

The course is designed for professionals who already support, manage or assess agriculture and rural development interventions and need to move from activity reporting to defensible performance evidence.

Course objectives

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

• Construct a theory of change and logframe for an agricultural extension programme
• Define SMART indicators for farmer reach, advisory quality, practice adoption and production outcomes
• Prepare indicator reference sheets with definitions, disaggregation, sources, frequency and responsibility
• Design baseline, follow-up and endline data-collection plans using appropriate sampling methods
• Build a KoboToolbox questionnaire for farmer, extension-worker and demonstration-plot monitoring
• Conduct data-quality assessments using completeness, timeliness, validity, consistency and integrity checks
• Analyse extension monitoring data in Microsoft Excel using pivot tables, disaggregation and trend comparisons
• Produce an evaluation findings brief with OECD DAC criteria, conclusions and actionable recommendations

Benefits of attending

Target competencies

Who should attend

• Agricultural Extension Managers — who need evidence on field-agent performance and farmer adoption
• Monitoring and Evaluation Officers — who design indicators, tools and reporting systems for agriculture projects
• Programme Managers — who must use performance evidence to adjust extension delivery and resource allocation
• Project Coordinators — who oversee farmer groups, demonstration plots and field-level implementation
• Government Agricultural Officers — who monitor public advisory services and report against sector plans
• NGO and Donor Programme Staff — who assess results, accountability and learning across rural development grants

Requirements and prerequisites

Participants should have practical exposure to an agricultural, rural development or extension programme and understand basic project concepts such as activities, outputs, outcomes, targets and workplans. They should be comfortable using Microsoft Excel for entering data, sorting and applying simple formulas. Familiarity with farmer surveys, logframes or mobile data collection is helpful but not essential. Participants should bring a laptop with Excel access for exercises. This is not a statistics, econometrics or GIS course; prior knowledge of sampling calculations, Power BI, KoboToolbox or formal evaluation methods is not required.

Training methodology

The course uses a single running case of an agricultural extension programme serving smallholder producers through field agents, demonstration plots and farmer groups. Short instructor-led sessions introduce each method, followed by guided work on logframes, indicators, sampling decisions, KoboToolbox forms and Excel datasets. Teams review realistic field-monitoring problems, including missing records, inconsistent yield units and low participation by women farmers. Daily outputs are peer-reviewed against practical criteria. On the final day, participants assemble their own M&E package and identify actions for implementation within 90 days.

Course outline

Day 1: Results-Based M&E for Agricultural Extension

• Extension service delivery models and their measurement implications
• Results chains linking advisory activities to farmer outcomes
• Theory of change assumptions for practice adoption
• Logframe structure for agricultural extension interventions
• Output, outcome and impact indicator distinctions
• Stakeholder information needs for farmers, managers and funders
• M&E system roles, reporting flows and decision cycles

Workshop: Participants map a results chain and draft a logframe for a smallholder extension programme focused on climate-smart production practices.

Day 2: Indicators, Targets and Data Sources

• SMART indicator criteria for extension performance
• Reach, frequency and quality indicators for advisory services
• Practice-adoption indicators and verification methods
• Yield, income and resilience outcome measurement limitations
• Sex, age, disability and geographic disaggregation
• Indicator reference sheets and indicator performance tracking tables
• Target setting using baselines, seasonal calendars and implementation capacity

Workshop: Participants create an indicator reference sheet and target matrix for farmer outreach, adoption and service-quality indicators.

Day 3: Field Data Collection and Quality Assurance

• Baseline, routine monitoring, follow-up and endline study designs
• Probability and purposive sampling for farmer populations
• Sample-size considerations, respondent selection and replacement rules
• Questionnaire design for farmer surveys and extension-worker supervision
• KoboToolbox form logic, constraints, skip patterns and validation rules
• Demonstration-plot observation checklists and field verification protocols
• Data-quality assessment dimensions and corrective-action logs

Workshop: Participants build a KoboToolbox farmer monitoring form and a data-quality checklist for field supervisors.

Day 4: Analysis, Evaluation and Learning

• Data cleaning procedures for field-monitoring datasets
• Excel pivot tables for farmer and extension-agent performance analysis
• Cross-tabulation by sex, location, crop and farmer category
• Adoption-rate, coverage-rate and target-achievement calculations
• Interpreting yield and income data without overstating attribution
• OECD DAC evaluation criteria in agricultural extension evaluations
• Contribution analysis, triangulation and qualitative farmer feedback

Workshop: Participants clean a sample extension dataset, calculate adoption and coverage results, and prepare evidence statements for an evaluation review.

Day 5: Reporting, Use and M&E Implementation Planning

• Management dashboards for extension programme decisions
• Power BI dashboard requirements and visual selection
• Results narratives that distinguish facts, interpretation and recommendations
• Evaluation findings, conclusions and recommendation writing
• Adaptive management triggers for underperforming extension services
• Donor reporting schedules and evidence audit trails
• Ninety-day M&E system implementation planning

Workshop: Participants present an agricultural extension M&E package, including a reporting dashboard specification and a 90-day implementation plan, for peer and facilitator review.

Tools & standards covered

KoboToolbox, Microsoft Excel, Microsoft Power BI, OECD DAC Evaluation Criteria

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