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Training on Participatory M and E for Rural Development and Community Managed Programmes

By: Datastat Research Center

Kenya

04 - 08 Mar, 2019  5 days

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USD 900

This course enables participants to broaden their understanding of participatory monitoring and evaluation as a support program management at various levels, and a tool for enhancing local capacity, participation, and people’s confidence and control over development processes and decisions. The training will delve into concepts and principles of participatory monitoring and evaluation as well as the different methods and techniques that have already been tested in the field. 

The course is most suitable to individuals involved in planning, monitoring, and evaluation such as project managers, research officers, extension workers, community facilitators, and advocacy workers with at least two years of direct experience in planning, implementation, or management of activities. Participants will be required to produce information materials describing their experience. English proficiency is another requirement.

Target Audience

Topics to be Covered

  • Introduction to Participatory Monitoring and Evaluation (PME)
  • Aims of Participatory MandE
  • Applicability, advantages and disadvantages of PME
  • Principles of PME
  • What is PME?
  • Steps in the development and implementation of PME process
  • Analyzing Data
  • Gathering Data

Planning the PMandE Process and Determining Objectives and Indicators

  • Sharing the Information and Defining Actions to Be Taken
  • Participatory Monitoring and Evaluation Frameworks
  • Strategic Framework
  • Logical Framework
  • Participatory Monitoring and Evaluation Plans
  • Developing PMandE Plans
  • Implementing and monitoring PMandE Plans
  • Mainstreaming PMandE Plans with Project Plans
  • Techniques and Tools for PMandE
  • Beneficiary Assessment
  • Community records and indicators
  • Participatory Rural Appraisal
  • Photographing the evidence

SARAR

  • Testimonials
  • Visual self-evaluation tools
  • Participatory Planning and Design
  • Developing an action plan for implementation
  • Generating objectives for Project planning
  • Group dynamics of Participatory Decision making process.
  • Involving the community in implementation
  • Selecting indicators for Participatory Monitoring and Evaluation

Definition of an indicator.

  • Factors to consider in selecting indicators.
  • Formulation of indicators.
  • Types of indicators.
  • Participatory Action Research (PAR)
  • PAR Tools
  • Research mapping
  • Research Planning
  • What is Action Research?
  • What is social research?
  • Participatory Baselines
  • The need for Participatory baselines  
  • Tools used for Participatory baseline surveys
  • Data Analysis for Participatory Monitoring and Evaluation
  • Difference between description and interpretation
  • Feedback to Stakeholders
  • Qualitative data analysis: The basic steps
  • Participatory dissemination.
  • Participatory Information gathering Tools and Methods
  • How to increase trustworthiness of findings
  • Using NVivo for qualitative data analysis and management  
  • Value of involving others in the process

Participatory Impact Assessment

  • 8 stages of a Participatory impact assessment
  • Assessing project attribution
  • Participatory Tools and Methods for participatory impact assessment
  • Community defined indicators of project impact
  • Triangulation

What is participatory impact assessment?

  • Participatory M and E Report writing
  • Communicating the different findings among partners
  • Qualities of a good report
  • Sharing experiences with others who may be implementing similar projects.
  • GIS and GPS Techniques for mapping in Participatory MandE
  • Participatory Mapping of M and E indicators
  • Using Google Maps, Google Earth for participatory mapping   
  • Introduction to Participatory GIS Software (Quantum GIS)
Datastat Training Center, Nairobi, Kenya Mar 04 - 08 Mar, 2019

Class Session: 08:00:am - 17:00:pm

USD 900.00
(Convert Currency)

Sammy 0724527104

Datastat Research
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