Training Course on ICT Tools for Modern Monitoring and Evaluation-Rwanda

About the Course

Modern monitoring and evaluation call for use of a variety of ICT tools for mobile data collection, data analysis (quantitative and qualitative) and reporting. A monitoring and evaluation practitioner is expected to interact with numerous software/application such as ODK, SPSS, Stata, NVivo, just to mention a few. This course aims to illustrate how the various ICT tools are applied in monitoring and evaluation.  

Target Participants

This course is designed for researchers, project staff, development practitioners, managers, and decision-makers who are responsible for project or program-level M&E. The course aims to enhance the skills of professionals who need to research, supervise, manage, plan, implement, monitor, and evaluate development projects.

What you will learn

By the end of the course the learner should be able to:

• Understand qualitative and quantitative analysis approaches
• Understand different qualitative and quantitative data collection methods
• Use statistical software such as SPSS, Stata and Microsoft Excel for data analysis in monitoring and evaluation
• Use qualitative research software such as NVivo for data analysis in monitoring and evaluation
• Learn how to visualize monitoring and evaluation results
• Use software like ArcGIS or QGIS for spatial data analysis and mapping of M&E data

Course duration

5 days

Course Outline

Data Collection Methods and Tools

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

Mobile Data Collection

• Introduction to mobile data collection
• Setting up of mobile data collection platforms
• Setting up the server
• Design of data collection forms

Introduction to Data Analysis

• Introduction statistics and data analysis
• Understanding descriptive vs inferential statistics
• Understanding variables
• Introduction to data types

Statistical Data Management

• Data cleaning and management
• Exploring Data
• Descriptive analysis
• Frequencies
• Basic univariate analysis
• Cross tabulations
• Basic univariate analysis
• Cross tabulations

Comparison Tests

• Understanding parametric vs non-parametric tests
• Choosing a test – decision tree
• Parametric data- T test, ANOVA
• Non-parametric data
• Proportions

Tests of Association

• Introduction to correlation analysis
• Parametric data – Pearson correlation
• Nonparametric data – Spearman rank correlation

Regression Analysis

• Introduction to regression analysis
• Regression diagnostics – measurement error, multicollinearity, heteroskedasticity, endogeneity, non-normality
• Parametric data – linear regression analysis (simple and multiple regression)
• Non-parametric data – non parametric regression
• Categorical dependent variables – logit and probit regression models

 Data Visualization

• Pivot tables
• Graphs and charts
• Dashboards

Introduction to Qualitative Research

• What is qualitative research?
• Dimensions of qualitative methods
• Qualitative research approaches
• Qualitative data collection methods
• Qualitative research study design

Introduction to NVIVO

• NVIVO Projects
• Nodes in NVIVO
• Classifications
• Coding
• Thematic Analysis using NVIVO
• Memos Annotations and Links
• Queries using NVIVO
• Qualitative Analysis Results Interpretation
• Qualitative Report Writing

Introduction to GIS

• Principles of GIS and  Remote Sensing
• Components of GIS Systems
• GIS Capabilities and Functions
• Spatial Data Infrastructure
• Introduction to GIS data
• Spatial Reference Systems
• GIS data acquisition
• Map making using ArcGIS or QGIS software
• Loading GIS Data into a GIS software
• Key Options of Geospatial Data Representations
• Styling geographical features
• Producing final map (Spatial Analysis and Point pattern analysis)
• Buffer analysis
• Join analysis
• Point in polygon analysis