Learning outcomes

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

• Evaluate Water, Sanitation and Hygiene (WASH) programmes against objectives and targets
• Define different Water, Sanitation and Hygiene (WASH) indicators
• Track performance of WASH related indicators over the life of the project
• Design WASH projects and programmes using logical framework approach
• Understand the gender role in M&E of Water, Sanitation and Hygiene (WASH) projects and programmes
• Develop and implement an M&E system in WASH
• Develop a comprehensive monitoring and evaluation plan
• Use data analysis software (Stata/SPSS/R/Excel)
• Collect data using mobile data collection tools
• Use GIS to analyze and share project data

Who should enroll?

This training course is recommended for researchers, project staff, development practitioners, managers and decision makers who work in Water, Sanitation and Hygiene (WASH) projects and programmes.

Why train with us

Vital Extra Learning guarantees our clients:

• State-of-the-art facilities and training infrastructure
• Extended tradition of hand-holding during post engagement
• Service delivery through highly seasoned industry experts.
• Value for money

TOPICS TO BE COVERED

Module 1: Introduction to M&E

Strategic Information in Health Programs

• Need for reliable information in WASH projects and programmes
• Components of strategic information
• Uses of strategic information
• Strategic information and program life cycle
• Decision making using strategic information

Introduction to M&E

• 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)
• LogFrame - Design of projects using LogFrame

M&E Indicators

• Indicators selection
• Indicator 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-Monitoring and Evaluation components
• Using M&E Plan to implement M&E in a Project

Module 2: Data Collection and Quality in WASH Projects and Programs

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 and Programs

• Importance of data quality in health programs
• 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
• Program window features, data structures and types of variables
• Data Management using statistical softwares
• Output management
• Basics of Stata/SPSS programming

Descriptive Statistics

• Describing quantitative data
• Describing qualitative data (tabulation)

Graphics and Data Visualization

• Graphing quantitative data
• Graphing qualitative data

Module 3: Correlation, Chi-square and mean comparison analysis

Correlation  

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

Chi-Square 

• 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 

Comparing Means Using 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 and Nonparametric Statistics 

Regression Analysis

• Assumptions of selected types of regression
• Linear regression; Binary logistic regression; ordered logistic regression; multinomial logistic regression and Poisson regression

Use of GIS in M&E for WASH Projects and Programs

• Benefits of using GIS in WASH Projects and Programs
• Introduction to ArcGIS software

Editing and Management of GIS Data

• Adding feature 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 themes
• Working with attribute tables
• Spatial query and analysis
• Working with charts

Cartographic visualization and mapping

• Components of a map
• Map design
• Symbol design
• Name design and placement
• Concept of scale
• Map projections
• Data pre-processing techniques
• Thematic mapping;
• Digital mapping
• Mapping for abundance and distribution

Module 5:

Qualitative Data Analysis in WASH Projects and Programs

• Principles of qualitative data analysis
• Data preparation for qualitative analysis
• Linking and integrating multiple data sets in different forms
• Thematic and content analysis for qualitative data
• Manipulation and analysis of data using NVivo

WASH Projects and Programmes Evaluation

• Determining evaluation points from results framework
• Components of evaluations: implementation and process evaluations.
• Evaluation designs- experimental, quasi-experimental and non-experimental
• Performance evaluation process
• Evaluation findings sharing and dissemination

Data Demand and Use for WASH Projects and Programmes

• Using data to inform policies and programs
• Determinants of data use
• Understanding data and information flow
• Linking data to action
• Knowledge management for data use in WASH projects and programs