Enhancing Project Monitoring Evaluation Accountability And Learning

Introduction

Data gathered during monitoring and evaluation reveals the success or failure of a project. Moreover, captured data also helps in guiding strategic planning, to design and implement programs and projects, and to allocate, and reallocate resources in efficient ways. What's more, monitoring, and evaluation helps with identifying the most valuable and efficient use of resources. This 10 days course will equip participants with knowledge in capturing quantitative and qualitative data, learn how to design a Monitoring and Evaluation system, gain practical and participatory Monitoring and Evaluation methodologies and tools to boost their program and organizational accountability, decision-making, and learning practices.

Duration

10 days

Course Content

Module 1: Introduction Monitoring & Evaluation

·        M&E and the project/programme cycle

·        Importance of M&E

·        Purposes and uses of M&E

·        Identifying gaps in M&E

·        Barriers to effective M&E

Project Monitoring, Evaluation, Accountability and Learning PMEAL overview

·        Introduction to PMEAL

·        PMEAL Components

·        Purposes and functions of PMEAL

·        PMEAL approach

·        How PMEAL changes M&E

·        Challenges to PMEAL

Module 2: Frameworks and PMEAL Cycle

·        Frameworks and approaches informing PMEAL

·        The language used in PMEAL

·        The PMEAL cycle

·        Exploring key elements of a PMEAL plan

·        Defining indicators

·        Designing, implementation and management of a PMEAL framework 

Module 3: PMEAL Planning and Budgeting

  PMEAL planning

·        Planning and budgeting of PMEAL

·        Planning and Budgeting relationship.

·        Tools for planned monitoring and evaluation activities

·        How do I get started?- Practical’s and application

·          Identifying project/programme goals.

·          Identifying project/programme indicators and targets.

·        Selecting data collection methods and data sources for prioritized indicators in your PMEAL plan

·        Decide upon your data analysis, quality assurance/validation, and management strategy.

• Identify your strategy for reporting and disseminating data.

    PMEAL Budgeting

·        Activities based PMEAL budgeting

·        Components of the Budget

·        Exercise: PMEAL Plan and corresponding budget

Module 4: Accountability and Learning

·        Meaning of accountability mean in practice

·        Aspects of accountability.

·        Importance of Accountability

·        Information sharing

·        Participation

·        Handling Complaints

·        Learning and its role

·        Exercise: Incorporating Accountability and Learning in Projects

Module 5: Baseline and evaluation design and management

·        The purpose and use of baselines and evaluations

·        Purpose and use of needs assessments, situation analysis,

·        Baselines, evaluations and real-time reviews

·        Importance of baseline for monitoring and evaluation

·        Steps in planning and undertaking baselines and evaluations

Module 6: Survey Planning and Implementation Types of surveys

·        The survey design and process

·        Methods of survey sampling and determining the Sample size

·        Data collection techniques and tools

·        Designing survey questionnaires

·        Pretesting research tools for Validity and Reliability

·        Conducting the survey

·        After the survey

·        Exercise: Planning for a survey

Module 7: PMEAL Data Collection: Mobile Based Data Collection (ODK)

·        Introduction to mobile phone data collection

·        Advantages and challenges of Mobile Applications

·        Components of Open Data Kit (ODK)

·        Install ODK Collect into mobile devices

·        Designing and creating Forms

·        ODK Aggregate Server

·        Exercise: Mobile Based Data Collection using ODK

Module 8: Data Quality Management, Tabulation and graphical presentation of data (SPSS/Stata/R)

Data quality management

·        Types of variables (Numerical, discrete variables, dummy variables,

·        Entering categorical and continuous data

·        Defining and labeling variables

·        Validation and Sorting variables

·        Transforming, recording and computing variables

 Tabulation and graphical presentation of data

·        Descriptive Statistics

·        Frequency Tables

·        Tables for categorical data

·        Graphs and charts

·        Exercise: Data Management, Graphing, and Tabulations

Module 9: Data analysis and interpretation and use (SPSS/Stata/R)

·        Hypothesis testing

·        Comparing Means.

·        Regression and Correlation analysis

·        Interpreting the data

·        Introduction to analyzing qualitative data and qualitative data analysis software

·         Exercise: Data Analysis and interpretation

Module 10: Project reporting through PMEAL

·        Use of PMEAL data  in Reporting

·        Communication activities to partners and stakeholders

·        Lessons learned