Monitoring and Evaluation (M&E) in Development Projects

Understand how monitoring and evaluation drive project management, enabling accountability and adaptive learning through routine data on outcomes and impact, and distinguish ongoing monitoring from midterm and final evaluations.

Navigate project cycles by integrating monitoring and evaluation—from planning with participatory data collection to midterm and end-line evaluations, using PMP, indicators, and data management.

Explore how performance monitoring plan supports monitoring and evaluation systems by tracking progress against indicators. The PMP provides a systematic tool for decision making and reporting to donors and beneficiaries.

Explore the logic model by linking inputs, activities, outputs, outcomes, and impact, including training, income effects, and climate-related goals, with monitoring and evaluation guiding assessment.

Explore the four-column, four-row logical framework, indicators, means of verification, data sources, risks, and assumptions, illustrated by a pest management training example in Cambodia.

Present a logical framework template and spreadsheet from a USAID project with downloadable templates and indicators. Set annual targets over a five-year plan and record actual values beside targets.

Discover a practical workplan example as a core tool for performance monitoring and project management, with downloadable templates for indicators, logical framework, and other free resources.

Learn to collect data with primary and secondary sources in development projects, using surveys, polls, interviews, delphi techniques, and focus groups, and leverage government, NGO, and census data.

Explore statistical methods for data collection, including finite and unlimited population size calculations. Learn probability and non-probability sampling, with simple random, systematic, stratified, and cluster methods, and an Excel template.

Explore non-probability sampling methods used in field interviews, including convenience sampling, purposive sampling, snowball sampling, and quota sampling, with emphasis on non-random selection.

Explore data collection software such as Google Forms, Kobo Toolbox, and SurveyMonkey for electronic and mobile data collection, and why they beat hard copies.

Explore four data analysis types—descriptive, diagnostic, predictive, and others—within M&E, covering sample size, center, spread, shapes, and visuals like histograms and box plots to guide recommendations.

Explore data analysis in Microsoft Excel using a survey dataset of household income in country A, formatting as a table and computing average, maximum, and standard deviation for development projects.

Learn to analyze data in Excel with the analyze data feature, generating quick insights on gender, age, and income by job, with clear charts for monitoring and evaluation.

Learn to use Microsoft Excel's data analysis toolpak to perform descriptive statistics on numeric data, including mean, median, standard deviation, and more, with step-by-step setup.

Learn how data visualization uses charts, maps, and graphs to present research findings clearly for audience and donor, including bar, line, scatter, histogram, and composition charts.

Design and build a Power BI dashboard from scratch to visualize sales data, including units sold and profit by month and country, with time slicers and data import.

Create and customize a Power BI dashboard with cross-sell and profit visualizations, including monthly and country filters, charts, and slicers for year and quarter, plus sharing options.

Explore different evaluation types across project cycles, including end-of-process feedback, multi-phase end-of-phase reviews, ex-post assessments for sustainability, and real-time formative evaluation to guide decision-makers.

Learn to refresh pivot tables to update summaries from data sheets, so changes like quarter one values are reflected in totals by using the refresh option or icon.

Learn to calculate values in pivot tables by creating a pivot table and dragging fields. Switch between sum, count, and maximum to see the value results by product.

Learn to create a calculated field in pivot tables to compute net profit by multiplying the sell amount by 50%.

Create a pivot chart from the data table to visualize product-type sales as a pie chart, then adapt to line or column charts to aid senior management in quick comparisons.

Learn to create a slicer in a pivot table to filter data by fields, such as regions, and quickly clear all filters for analysis.

Create a pivot table timeline to filter dates by inserting a timeline and selecting the date field, then filter by month ranges and clear selections across regions and homelands.