Overview

Water, Sanitation and Hygiene (WASH) is a critical public health sector, with sustainable access recognized as a global development priority under Sustainable Development Goal 6. The WASH sector is complex and multi-faceted, requiring specialized monitoring and evaluation methods to track progress and impact. This course equips participants with practical skills to design, implement, and manage robust M&E systems for WASH projects. Participants will learn to develop indicators, collect and analyze data using statistical software, leverage GIS, and evaluate WASH programmes for evidence-based decision-making.

Target Audience

Researchers, project staff, development practitioners, managers, and decision makers working in WASH projects and programmes.

Learning Outcomes / Objectives

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

• Evaluate WASH programmes against objectives and targets.
• Define and apply WASH indicators effectively.
• Track performance indicators over project life cycles.
• Design WASH projects and programmes using logical framework analysis.
• Understand the role of gender in M&E of WASH programmes.
• Develop and implement M&E systems and comprehensive plans.
• Use statistical software (Stata, SPSS, R, Excel) for data analysis.
• Collect data using mobile tools and apply GIS for spatial analysis.

Duration

5 days

Modules / Course Content

Module 1: Introduction to M&E in WASH projects Strategic Information in WASH Projects

• Need for reliable information
• Components of strategic information
• Uses of strategic information
• Strategic information and project life cycle
• Decision making using strategic information

Introduction to Monitoring and Evaluation

• Definition of Monitoring and Evaluation
• Why Monitoring and Evaluation is important
• Key principles and concepts in M&E
• M&E in project lifecycle
• Complementary roles of Monitoring and Evaluation

M&E Frameworks

• Conceptual Frameworks
• Results Frameworks
• Logical Framework Analysis (LFA)
• Designing projects using LogFrame

M&E Indicators

• Indicator selection and metrics
• Linking indicators to results
• Indicator matrix
• Tracking of indicators

M&E Plans in WASH Projects and Programmes

• Importance of an M&E Plan
• Documenting M&E System in the M&E Plan
• Components of M&E Plan
• Using M&E Plan to implement M&E in a Project

Module 2: Data Collection and Quality in WASH Projects Data Collection Tools and Techniques

• Sources of M&E data – primary and secondary
• Sampling during data collection
• Qualitative data collection methods
• Quantitative data collection methods
• Participatory data collection methods
• Introduction to data triangulation

Data Quality in WASH Projects

• Importance of data quality
• Data quality elements
• Routine Data Quality Assessments
• Data Quality Audit
• Data Quality Assurance

Data Management and Analysis

• Introduction to Stata/SPSS/Excel
• Introduction to statistics concepts
• Data structures and variable types
• Data management using statistical software
• Output management
• Basics of Stata/SPSS programming

Descriptive Statistics and Visualization

• Describing quantitative data
• Describing qualitative data
• Graphing quantitative data
• Graphing qualitative data

Module 3: Correlation, Chi-square, and Mean Comparison Analysis Correlation Analysis

• Correlation
• Subgroup correlations
• Scatterplots of data by subgroups
• Overlay scatterplots

Chi-Square Tests

• Goodness of Fit Chi-Square All Categories Equal
• Goodness of Fit Chi-Square Categories Unequal
• Chi-Square for contingency tables

Comparing Means

• One-Sample t-tests
• Paired Sample t-tests
• Independent Samples t-tests
• Comparing Means using One-Way ANOVA

Factorial ANOVA

• Factorial ANOVA using GLM Univariate
• Simple Effects

Nonparametric Statistics

• Mann-Whitney Test
• Wilcoxon’s Matched Pairs Signed-Ranks Test
• Kruskal-Wallis One-Way ANOVA
• Friedman’s Rank Test for k Related Samples

Module 4: Regression Analysis, GIS, and Spatial Data Regression Analysis

• Assumptions of selected types of regression
• Linear regression; Binary logistic; Ordered logistic; Multinomial logistic; Poisson regression

Use of GIS in WASH Projects

• Benefits of using GIS
• Introduction to ArcGIS software

Editing and Management of GIS Data

• Adding features to GIS data
• Reducing GIS data
• Cutting points of interest in image datasets
• Transforming GIS data

Geo-Spatial Analysis

• Geo-processing
• Creating views and themes
• Working with attribute tables
• Spatial query and analysis
• Working with charts

Cartographic Visualization and Mapping

• Components of a map
• Map design, symbol design, and name placement
• Concept of scale
• Map projections
• Data pre-processing techniques
• Thematic and digital mapping
• Mapping for abundance and distribution

Module 5: Qualitative Analysis, Evaluation, and Data Use Qualitative Data Analysis in WASH Projects

• Principles of qualitative data analysis
• Data preparation for qualitative analysis
• Linking and integrating multiple datasets
• Thematic and content analysis
• Manipulation and analysis using NVivo

WASH Projects and Programmes Evaluation

• Determining evaluation points from results framework
• Implementation and process evaluation components
• Evaluation designs: experimental, quasi-experimental, non-experimental
• Performance evaluation process
• Sharing and dissemination of evaluation findings

Data Demand and Use for WASH Projects

• Using data to inform policies and programmes
• Determinants of data use
• Understanding data and information flow
• Linking data to action
• Knowledge management for data use

Training Methodology

The course will employ a hands-on, practical approach to ensure participants develop both conceptual understanding and technical proficiency. Each module will integrate interactive lectures, guided software demonstrations, and individual or group exercises based on real-world illustrations. Participants will receive continuous feedback and personalized coaching to reinforce learning. By the end of the training, they will have completed a mini project that demonstrates their ability to apply the acquired skills in a practical context.

More Details

Upon successful completion of this course, participants will be issued a certificate.