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International Training on Monitoring and Evaluation for Development Results

By: Datastat Research Center


24 Feb - 06 Mar, 2020  12 days

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USD 900

Venue: Datastat Training Center, Nairobi, Kenya

Other Dates

Venue Date Fee  
Datastat Training Center, Nairobi, Kenya, Kenya 16 - 27 Mar, 2020 USD1800
Datastat Training Center, Nairobi, Kenya, Kenya 06 - 17 Apr, 2020 USD1800

This course is designed to develop monitoring and evaluation skills, which are in high demand in today’s job market, particularly in development industries. On successful completion, you will gain the ability to design and manage monitoring and evaluation systems that meet the standards of donor agencies.

Learning Objectives

  • Build a Monitoring and Evaluation system
  • Benefit from a proactive approach based on real life cases
  • Gain insights on how multilateral agencies manage their operations
  • Communicate findings to stimulate learning and reflection.
  • Get access to resources that you require in order to start your training program on Monitoring and Evaluation
  • Getet acquainted with key issues about measures such as reliability, validity credibility, and precision
  • Use data analysis software package (Stata).
  • Learn how to select data collection strategies
  • Use GPS and Geographic Information Systems (GIS) to gather data and share information.
  • Work in groups together with professionals from around the world, in a multicultural and diverse environment

Who Should Attend?

This course targets Project Management Officials from NGO’s, Education Researchers, National Statistics Offices, Government ministries, Central banks, National Institutes and Planning Ministries, and University Researchers, among others.

Course Content

  • M and E fundamentals
  • Identifying the challenges that face Monitoring and evaluation professionals
  • Introduction to M and E?
  • Key components of M and E
  • Relating Monitoring and evaluation to the project cycle
  • Trends towards result based M and E
  • Managing for development results (MFDR)
  • MFDR core principles
  • Results based management
  • Introduction to result based M and E
  • Essential actions to build result based M and E
  • Performance measurement, performance indicators and performance monitoring
  • Result based M and E cycle
  • Results based M and E outline
  • The power of measuring results
  • What is RBM?
  • Situation analyses/Needs assessment
  • Formative research and analysis
  • Practical/illustrative examples
  • Tools to conduct needs assessment
  • Baseline assessment
  • Examples of baseline study
  • Importance of baseline study
  • Needs assessment versus baseline study
  • What is baseline data and how to collect?
  • Designing the M an dE system
  • Impact path ways
  • M and E frame works
  • Results chain and impact pathways
  • Theory of change
  • Step by step approaches to M and E
  • Design andset up
  • M and E system design practical
  • Principles of M and E system
  • System management
  • M and E frameworks
  • Developing and implementing M and E frameworks
  • Linking M and E frameworks to indicators
  • M and E frameworks for development
  • Using data
  • M and E plans
  • Can M and E plans be amended?
  • Important considerations for an M and E plan
  • What does an M and E plan include?
  • When monitoring activities should be carried out?
  • When should evaluations be conducted?
  • When should M and E be undertaken?
  • Designing indicators and evidence
  • Challenges and considerations when selecting indicators
  • Developing indicators
  • Impact indicators
  • Outcome indicators
  • Output indicators
  • Process indicators
  • Process versus result/impact indicators
  • Result indicators
  • Types of indictors and characteristics
  • Performance monitoring
  • Definition and process
  • Tools used
  • Evaluation techniques
  • Communication of results
  • Data collection and analysis
  • Design
  • Illustrative examples
  • Gender M and E
  • Exploring gender in M and E plans
  • Gender considerations for data interpretation, collection, and use
  • Introduction to M and E in Gender and development
  • Prioritizing gender in M and E plans
  • Selecting indicators to measure gender related outputs and outcomes
  • Evaluation techniques
  • Case study: cost effectiveness
  • Introduction to Economic evaluation
  • Main methods of economic evaluation
  • Communicating M and E results
  • Presentation of findings/results
  • Developing communication system
  • Use of andM and E results
  • Audiences
  • Different uses of results
  • Assessing program impact
  • Impact Assessment in Program Design
  • Introduction to Impact Assessment
  • Program Design Implications
  • Economic evaluations
  • Case study: cost effectiveness
  • Introduction to Economic evaluation
  • Main methods of economic evaluation
  • Data collection, management and data quality
  • Data collection methods: How to undertake quantitative and qualitative data collection
  • Data collection versus data analysis
  • Data quality and data management
  • Data quality dimensions
  • Functional areas of data management systems
  • Increasing questionnaires response rates
  • Introduction to data analysis and interpretation
  • Basic analysis
  • Data analysis key concepts
  • Introduction
  • Types of variables
  • Summarizing data
  • Graphs and charts for continuous variables
  • Graphs and charts for dichotomous and categorical variables
  • Graphs and charts for ordinal variables
  • Numerical summaries for discrete variables
  • Tables for categorical variables
  • Tables for dichotomous variables
  • Tables for ordinal variables
  • Tabulations for summary statistics for continuous variables
  • Introduction to qualitative data analysis
  • Coding the data
  • Introduction to using a qualitative data analysis software (NVivo)
  • Organizing your data
  • Planning for qualitative data analysis
  • Reviewing the data
  • Quantitative data analysis       
  • Basics for statistical analysis
  • Choosing the correct statistical test
  • Comparison of Data analysis packages
  • Confidence intervals
  • Hypothesis testing versus confidence intervals
  • Interpreting the data
  • Planning for quantitative data analysis
  • Testing for normality of data
  • Tests Hypothesis testing
  • ICT tools for data collection, monitoring and evaluation in development programmes
  • Application
  • How can we use ICTs for qualitative M and E
  • ICT innovations: Mobile data collection
  • Using Mobile phones for data collection
  • GIS techniques for M and E of development programs
  • Data sources for development issues
  • Geographic approaches to development
  • GIS advantages for M and E
  • GIS analysis and mapping techniques
  • Using GIS software and data
  • What is GIS?
Datastat Training Center, Nairobi, Kenya Feb 24 - 06 Mar, 2020
Datastat Training Center, Nairobi, Kenya, Kenya 16 - 27 Mar, 2020
Datastat Training Center, Nairobi, Kenya, Kenya 06 - 17 Apr, 2020
USD 900.00
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Sammy +254724527104

Datastat Research
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