Training Course On Project Performance Evaluation

INTRODUCTION

The projects implemented by organizations need to be aligned with the objectives of the institution to be effective. This course is aimed to guide development organizations to conduct precise and appropriate project evaluations, and then communicate and use the results of evaluation.

COURSE OBJECTIVES

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

• Understand the difference between monitoring and evaluation
• Identify project indicators for evaluation
• Design and plan for an evaluation
• Apply mixed methods of data collection during evaluation
• Perform both quantitative and qualitative data analysis
• Use findings to make evaluation conclusions and recommendations

DURATION

10 days 

WHO SHOULD ATTEND

This course is targeted at researchers, project staff, managers, development practitioners, policy makers in government, NGOs and development organizations who want to determine the performance of their interventions.

COURSE OUTLINE

Overview of M&E Fundamentals for Project Evaluation

• Results Framework
• Project Indicators of M&E
• Logical Framework

Introduction to Project Evaluation

• Meaning of project evaluation
• Project evaluation importance
• Monitoring versus Evaluation
• Design of Project Evaluation

Developing Evaluation Plan

• Purpose of Evaluation
• Evaluations Types
• Criteria of Evaluation
• Evaluation Questions Development

Planning for Data Collection

• Evaluation Data Sources Identification
• Data Collection Methods
• Data Analysis Methods
• Completing Evaluation Matrix

Organizing Evaluation Work

• Tasks Distribution
• Evaluation Work plan
• Evaluation Budget

Implementing Evaluation Plan

• Evaluation Indicators Identification
• Evaluation Tools
• Use of Monitoring data in evaluation
• Mixed methods of data collection management

Mobile Data Collection

• Conversion of paper based questions to ODK forms
• Configuration of ODK server aggregate
• Collection of field data using ODK collect
• Export of data from ODK for further analysis

Quantitative Data Analysis – (Using SPSS/Stata)

• Introducing statistical concepts
• Variables creation and data entry
• Reconstruction of data
• Manipulation of Variables
• Descriptive statistics
• Data weighting
• Inferential statistics: hypothesis testing, T-test, ANOVA, regression analysis

Qualitative Data Analysis

• Qualitative data analysis principles
• Preparation of data for qualitative analysis
• Linking and integrating multiple data sets in different forms
• Qualitative data Thematic analysis
• Qualitative data Content analysis
• Using Nvivo to manipulate and analyze data
• Data triangulation

Developing Evaluation Findings

• Evaluation Matrix Consolidation
• Data triangulation
• Developing evaluation questions answers

Evaluation Report

• Conclusions
• Recommendations
• Final evaluation report
• Dissemination of evaluation results