Project Monitoring and Evaluation with Mobile Data Collection and Analysis Course

Introduction

Monitoring and Evaluation (M&E) is essential for improving the performance, accountability, and learning of development projects and programs. As organizations increasingly demand results-driven approaches, professionals must be equipped with practical tools to design robust M&E systems and to generate actionable insights from project data. The Project Monitoring and Evaluation with Data Management and Analysis Course offers participants a comprehensive understanding of how to plan, implement, and manage effective M&E frameworks that enhance project delivery and impact.

This course integrates core M&E principles with hands-on training in data collection, management, and analysis using relevant tools and software. Participants will learn how to develop M&E plans, create logical frameworks, define key performance indicators, and implement participatory M&E approaches. Special focus is given to collecting high-quality data, ensuring data integrity, and analyzing quantitative and qualitative information for real-time decision-making and project learning.

In addition to the theoretical foundation, the course emphasizes applied skills in digital data tools such as Excel, SPSS, KoboToolbox, and Power BI. Participants will learn to design data collection forms, clean and organize datasets, generate dashboards, and present findings in ways that drive action and accountability. These skills are vital for professionals working in development, humanitarian response, research, and public sector programs.

Designed for M&E officers, project managers, program staff, researchers, and development practitioners, this course strengthens capacity to not only track project performance but also evaluate outcomes and impact effectively. Whether managing small-scale projects or multi-sectoral programs, participants will be empowered to make evidence-based decisions, communicate results to stakeholders, and contribute to a culture of learning and improvement.

Duration

10 days

Who should Attend?

This course is ideal for:

·       Monitoring and Evaluation (M&E) Officers and Specialists responsible for managing performance measurement and reporting systems.

·       Project and Program Managers who oversee the implementation of donor-funded, government, or NGO projects.

·       Data Analysts and Researchers seeking to enhance their skills in project-related data collection, management, and analysis.

·       Development Practitioners and NGO Staff involved in results-based program delivery and learning.

·       Government Officials and Planners working on public sector programs that require systematic monitoring and evidence-based evaluation.

·       Consultants and Independent Evaluators who support organizations in assessing impact, outcomes, and effectiveness.

·       Academics interested in applied M&E methods and data tools for research and fieldwork.

·       Field Officers and Community Project Coordinators involved in collecting, interpreting, and using data for project decision-making.

Course Objectives

By the end of this course the learners should be able to:

·       Understand the core concepts, principles, and importance of Monitoring and Evaluation (M&E) in the context of effective project and program management.

·       Design robust M&E frameworks using tools such as the Logical Framework Approach (LFA), Theory of Change, and Results-Based Management (RBM).

·       Develop and implement comprehensive M&E plans, including setting SMART indicators, establishing baselines, and defining data sources and reporting schedules.

·       Apply both quantitative and qualitative data collection methods, ensuring data reliability, validity, and ethical compliance in M&E practices.

·       Utilize digital tools for data collection and management, including KoboToolbox, Excel, and other mobile and cloud-based platforms.

·       Clean, organize, and analyze project data using software such as Excel, SPSS, or Power BI to generate actionable insights.

·       Interpret and visualize M&E results through charts, dashboards, and performance reports to support data-driven decision-making.

·       Conduct different types of evaluations (formative, summative, process, impact) and understand their role in learning and accountability.

·       Communicate M&E findings effectively to internal and external stakeholders, including donors, partners, and beneficiaries.

·       Build a culture of continuous learning and improvement by integrating M&E into every phase of the project lifecycle.

Course Outline

Module 1: Introduction to Monitoring and Evaluation (M&E)

• Definition and objectives of M&E
• Importance of M&E in project and program management
• Key M&E principles and terminology
• Role of M&E in the project lifecycle
• Results-Based Management (RBM) vs traditional M&E approaches

Module 2: Results-Based Project Management

• Fundamentals of Results-Based Management
• The RBM lifecycle and phases
• The results chain: inputs, outputs, outcomes, and impact
• Setting SMART project objectives and performance indicators
• Aligning M&E with development goals (e.g., SDGs)

Module 3: M&E Planning and System Design

• Components of a results-oriented M&E system
• Steps to designing an M&E system
• Developing M&E plans: structure and content
• Monitoring vs Performance Management Plan (PMP)
• Institutional arrangements and stakeholder roles

Module 4: Logical Framework and Theory of Change

• Introduction to Logical Framework Approach (LFA)
• Designing a logframe: vertical and horizontal logic
• Theory of Change (ToC): principles, development, and application
• Comparing and linking logframe and ToC
• Using logic models to plan and evaluate programs

Module 5: Indicators and Performance Measurement

• Definition and types of indicators
• Developing SMART indicators
• Creating an indicator matrix
• Linking indicators to the results framework
• Tracking and analyzing indicator performance

Module 6: Baseline Studies and Project Evaluation

• Purpose and design of baseline studies
• Evaluation types: formative, summative, process, impact
• Evaluation designs: experimental, quasi-experimental, and non-experimental
• Developing evaluation questions and tools
• Disseminating evaluation findings for learning and accountability

Module 7: Gender and Inclusion in M&E

• Importance of gender-responsive M&E
• Designing gender-sensitive indicators
• Collecting and analyzing sex-disaggregated data
• Mainstreaming gender and social inclusion in project evaluations

Module 8: Data Collection Tools and Techniques

Module 8.1: Understanding Data Sources

• Differentiating between primary and secondary data sources
• Identifying reliable sources of secondary data
• Advantages and limitations of each type
• Using existing data to inform baseline and evaluation design

Module 8.2: Quantitative and Qualitative Data Collection Methods

• Structured and semi-structured questionnaires
• Observation methods and checklist development
• Conducting Focus Group Discussions (FGDs) and Key Informant Interviews (KIIs)
• Integrating mixed-method approaches for comprehensive data gathering

Module 8.3: Participatory M&E Techniques

• Introduction to participatory monitoring and evaluation (PM&E)
• Tools: participatory rural appraisal (PRA), outcome harvesting, most significant change
• Benefits and challenges of participatory approaches
• Engaging beneficiaries and stakeholders in data collection

Module 8.4: Sampling Strategies for Data Collection

• Sampling methods: simple random, stratified, cluster, multistage, purposive
• Determining appropriate sample size and sampling frames
• Dealing with sampling errors and biases
• Application of sampling techniques in field surveys

Module 8.5: Ethical Considerations in Data Collection

• Principles of research ethics in M&E
• Informed consent and voluntary participation
• Ensuring data confidentiality and anonymity
• Ethical approval processes and working with vulnerable groups

Module 8.6: Introduction to Digital Data Collection Tools

• Advantages of mobile-based data collection systems
• Overview of mobile tools: ODK, KoboToolbox, SurveyCTO, and others
• Understanding the workflow of digital data collection
• Offline and online data submission

Module 8.7: Using KoboToolbox and ODK for Data Collection

• Introduction to ODK and KoboToolbox platforms
• Creating forms using XLSForm
• Setting up projects and designing surveys in KoboToolbox
• Installing and configuring ODK Collect on mobile devices
• Collecting, uploading, and managing mobile data
• Monitoring submissions and resolving common field issues

Module 9: Data Quality and Management

• Understanding data quality: dimensions and standards
• Data quality assurance and assessment (DQA)
• Designing data flow and documentation procedures
• Tools for data management and version control

Module 10: Digital Tools and ICT in M&E

• Real-time monitoring tools and platforms
• Digital dashboards and data visualization
• Data security, privacy, and digital ethics in M&E

Module 11: Qualitative Data Analysis

• Thematic and content analysis
• Coding and categorizing responses
• Interpreting qualitative data
• Use of qualitative analysis software (e.g., NVivo)

Module 12: Quantitative Data Analysis (SPSS/Stata)

• Introduction to statistical software
• Data entry, cleaning, and transformation
• Descriptive and inferential statistics
• Hypothesis testing, correlation, regression, and ANOVA
• Data visualization and interpretation of results

Module 13: Impact Evaluation and Attribution

• Introduction to impact evaluation
• Counterfactual thinking and attribution analysis
• Impact evaluation methods: RCT, DiD, PSM
• Selecting appropriate designs based on project context

Module 14: GIS and Spatial Analysis in M&E

• Introduction to Geographic Information Systems (GIS)
• Mapping project data and coverage
• Basic spatial analysis techniques
• Using open-source GIS tools (QGIS) for M&E
• Integrating spatial data in evaluations

Module 15: Using and Communicating M&E Results

• Stakeholder information needs
• Designing M&E reports and dashboards
• Using M&E results for decision-making and learning
• Knowledge management and institutional learning
• Communication strategies for evaluation findings

Module 16: Practical Sessions

• Group work on designing an M&E system
• Hands-on data collection using mobile tools
• Data analysis with SPSS or Excel
• Visualizing and reporting findings

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue

The training will be held at our Upskill Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment

Unless otherwise agreed between the two parties payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.