Agricultural Monitoring and Evaluation Officer

About Course

Learn to track agricultural activities and use evidence to understand their results. This course prepares learners to help agribusinesses and agricultural programmes measure progress, identify problems and improve their work.
Learners will practise developing indicators, setting targets, preparing data collection tools and conducting field surveys. They will learn to check data quality, analyse simple datasets, compare results against plans and write clear reports. The course also covers obtaining informed consent, protecting participants’ information and using findings to recommend practical improvements.
Designed for aspiring monitoring and evaluation officers, field staff and agricultural programme teams, this course builds practical skills in collecting reliable information and turning it into useful decisions.

Course Content

Module 1: Start with the decision, not the questionnaire
Understand what an agricultural monitoring and evaluation officer does, agree the work brief and separate delivery, learning and claims about change.

Lesson 1: Introduction
Lesson 2: Watch and practise: Start with the decision, not the questionnaire
Lesson 3: Visual guide: Decision Users
Lesson 4: Read the practical role guide
Lesson 5: Portfolio practice: A one-page monitoring brief with decision users and evidence limits
Lesson 6: Discussion:
Module 1: Start with the decision, not the questionnaire — knowledge check

Module 2: Build a believable results pathway
Map activities, outputs, outcomes and assumptions, then turn the pathway into a results framework that can be checked.

Module 3: Define indicators, baselines and targets clearly
Write indicator reference sheets that preserve population, numerator, denominator, time, source and interpretation.

Module 4: Plan measurement around people, seasons and limits
Choose a feasible measurement approach, distinguish a roster from a sample and prepare a realistic fieldwork and analysis plan.

Module 5: Build and test useful data-collection tools
Translate indicator definitions into clear questions and observations, then test form behaviour with practical scenarios.

Module 6: Run respectful, reliable fieldwork
Practise consent, enumerator preparation, offline workflows, daily supervision and appropriate handling of sensitive information.

Module 7: Clean data without losing the evidence
Preserve raw records, apply explicit cleaning rules, record exceptions and reconcile the cleaned dataset to its source.

Module 8: Analyse results with the right comparison
Calculate and interpret disaggregated attendance, matched learning changes, follow-up rates and complete-record agricultural yield.

Module 9: Listen, code and triangulate qualitative evidence
Use interview notes to understand experience, preserve context and negative cases, and compare evidence sources without overstating certainty.

Module 10: Report clearly and turn findings into action
Write an evidence-led report, choose honest charts and maintain a learning and action register that records follow-through.

Module 11: Ask evaluation questions and interpret costs responsibly
Select useful evaluation questions, recognise causal limits and calculate descriptive costs without inventing benefits.

Module 12: Work professionally and show your skills
Use job descriptions, role KPIs, SOPs and carefully bounded AI support to present truthful evidence of entry-level monitoring work.

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Agricultural Monitoring and Evaluation Officer

About Course

What Will You Learn?

Course Content

Module 1: Start with the decision, not the questionnaire Understand what an agricultural monitoring and evaluation officer does, agree the work brief and separate delivery, learning and claims about change.

Lesson 1: Introduction

Lesson 2: Watch and practise: Start with the decision, not the questionnaire

Lesson 3: Visual guide: Decision Users

Lesson 4: Read the practical role guide

Lesson 5: Portfolio practice: A one-page monitoring brief with decision users and evidence limits

Lesson 6: Discussion:

Module 1: Start with the decision, not the questionnaire — knowledge check

Module 2: Build a believable results pathway Map activities, outputs, outcomes and assumptions, then turn the pathway into a results framework that can be checked.

Lesson 1: Introduction

Lesson 2: Watch and practise: Build a believable results pathway

Lessson 3: Visual guide: Results Pathway

Lesson 4: Portfolio practice: A results pathway and a small logical framework

Lesson 5: Discussion

Module 2: Build a believable results pathway — knowledge check

Module 3: Define indicators, baselines and targets clearly Write indicator reference sheets that preserve population, numerator, denominator, time, source and interpretation.

Lesson 1: Introduction

Lesson 2: Watch and practise: Define indicators, baselines and targets clearly

Lesson 3: Visual guide: Cohorts and Denominators

Lesson 4: Define and report useful measures

Lesson 5: Portfolio practice: Four indicator reference sheets and a denominator dictionary

Lesson 6: Discussion:

Module 3: Define indicators, baselines and targets clearly — knowledge check

Module 4: Plan measurement around people, seasons and limits Choose a feasible measurement approach, distinguish a roster from a sample and prepare a realistic fieldwork and analysis plan.

Lesson 1: Introduction:

Lesson 2: Watch and practise: Plan measurement around people, seasons and limits

Lesson 3: Portfolio practice: A measurement and fieldwork plan with sampling limitations

Lesson 4: Discussion:

Module 4: Plan measurement around people, seasons and limits — knowledge check

Module 5: Build and test useful data-collection tools Translate indicator definitions into clear questions and observations, then test form behaviour with practical scenarios.

Lesson 1: Introduction

Lesson 2: Watch and practise: Build and test useful data-collection tools

Lesson 3 :Practical demonstration: Build and preview a practical monitoring form

Lesson 4: Visual guide: Form Test Paths

Lesson 5: Use the SOP and form-testing guide

Lesson 6: Portfolio practice: A tested follow-up form and a question dictionary

Lesson 7: Discussion

Module 6: Run respectful, reliable fieldwork Practise consent, enumerator preparation, offline workflows, daily supervision and appropriate handling of sensitive information.

Lesson 1: Introduction

Lesson 2: Watch and practise: Run respectful, reliable fieldwork

Lesson 3: Visual guide: Offline Handover

Lesson 4: Portfolio practice: A field protocol, consent rehearsal and daily review log

Lesson 5: Discussion

Module 7: Clean data without losing the evidence Preserve raw records, apply explicit cleaning rules, record exceptions and reconcile the cleaned dataset to its source.

Lesson 1: Introduction

Lesson 2: Watch and practise: Clean data without losing the evidence

Lesson 3: Practical demonstration: Work with a monitoring table in Google Sheets

Lesson 4: Visual guide: Cleaning Audit

Lesson 5: Portfolio practice: A clean dataset, three-row audit log and reconciliation

Lesson 6: Discussion:

Module 8: Analyse results with the right comparison Calculate and interpret disaggregated attendance, matched learning changes, follow-up rates and complete-record agricultural yield.

Lesson 1: Introduction

Lesson 2: Watch and practise: Analyse results with the right comparison

Lesson 3: Visual guide: Matched Learning

Lesson 4: Visual guide: Yield and Missingness

Lesson 5: Portfolio practice: An analysis table with calculations, cohort notes and limitations

Lesson 6: Discussion

Module 9: Listen, code and triangulate qualitative evidence Use interview notes to understand experience, preserve context and negative cases, and compare evidence sources without overstating certainty.

Lesson 1: Introduction

Lesson 2: Watch and practise: Listen, code and triangulate qualitative evidence

Lesson 3: Visual guide: Qualitative Evidence

Lesson 4: Portfolio practice: A coded evidence matrix and a triangulated finding

Lesson 5: Discussion:

Module 10: Report clearly and turn findings into action Write an evidence-led report, choose honest charts and maintain a learning and action register that records follow-through.

Lesson 1: Introduction

Lesson 2: Watch and practise: Report clearly and turn findings into action

Lesson 3: Practical demonstration: Summarise and chart a clean table with an Excel PivotTable

Lesson 4: Visual guide: Attendance Chart

Lesson 5: Portfolio practice: A two-page findings brief, one chart and an action register

Lesson 6: Discussion

Module 11: Ask evaluation questions and interpret costs responsibly Select useful evaluation questions, recognise causal limits and calculate descriptive costs without inventing benefits.

Lesson 1: Introduction

Lesson 2: Watch and practise: Ask evaluation questions and interpret costs responsibly

Lesson 3: Visual guide: Unit Cost and Scope

Lesson 4: Review the report and unit-cost explanation

Lesson 5: Portfolio practice: An evaluation question matrix and a scoped unit-cost note

Module 1: Start with the decision, not the questionnaire
Understand what an agricultural monitoring and evaluation officer does, agree the work brief and separate delivery, learning and claims about change.

Module 2: Build a believable results pathway
Map activities, outputs, outcomes and assumptions, then turn the pathway into a results framework that can be checked.

Module 3: Define indicators, baselines and targets clearly
Write indicator reference sheets that preserve population, numerator, denominator, time, source and interpretation.

Module 4: Plan measurement around people, seasons and limits
Choose a feasible measurement approach, distinguish a roster from a sample and prepare a realistic fieldwork and analysis plan.

Module 5: Build and test useful data-collection tools
Translate indicator definitions into clear questions and observations, then test form behaviour with practical scenarios.

Module 6: Run respectful, reliable fieldwork
Practise consent, enumerator preparation, offline workflows, daily supervision and appropriate handling of sensitive information.

Module 7: Clean data without losing the evidence
Preserve raw records, apply explicit cleaning rules, record exceptions and reconcile the cleaned dataset to its source.

Module 8: Analyse results with the right comparison
Calculate and interpret disaggregated attendance, matched learning changes, follow-up rates and complete-record agricultural yield.

Module 9: Listen, code and triangulate qualitative evidence
Use interview notes to understand experience, preserve context and negative cases, and compare evidence sources without overstating certainty.

Module 10: Report clearly and turn findings into action
Write an evidence-led report, choose honest charts and maintain a learning and action register that records follow-through.

Module 11: Ask evaluation questions and interpret costs responsibly
Select useful evaluation questions, recognise causal limits and calculate descriptive costs without inventing benefits.

Module 12: Work professionally and show your skills
Use job descriptions, role KPIs, SOPs and carefully bounded AI support to present truthful evidence of entry-level monitoring work.