CALL FOR REGISTRATION:
Professional Training in Monitoring, Evaluation, and Learning (MEL)
Foundation to Intermediate Level • AI-Integrated Practice
DATA+ Rwanda
- Organizers: Data+ Rwanda
- Dates: 4th -24th May 2026
- Duration: 3 weeks (Weekend Program)
- Venue: UR CST Nyarugenge Campus
- Mode: Physical and Virtual Participation Available
- Fee: 50,000 RWF
- Time: 09:00 AM – 4:00 PM
- Certification: Certificates of Merit awarded upon successful completion of the training and capstone project.
- Registration Link:https://dataplusrwanda.com/courses/apply/result-based-monitoring-and-evaluation
1. BACKGROUND AND RATIONALE
In today’s results-driven environment, organizations across the development, public, and private sectors face mounting pressure to demonstrate effectiveness, accountability, and impact. Programs are no longer assessed solely on the activities they deliver, but on the measurable and lasting changes they produce. Monitoring, Evaluation, and Learning (MEL) has therefore become an indispensable function in modern programming, enabling organizations to track progress, generate credible evidence, and continuously improve their work.
Despite its recognized importance, a significant gap persists between the demand for MEL expertise and the availability of professionals with the requisite skills. Many practitioners engaged in program design and implementation lack formal, structured training in MEL. In practice, this translates into weakly articulated program logic, poorly defined indicators, inadequate monitoring systems, and a limited ability to commission or manage evaluations. Critically, available evidence often goes underutilized in organizational decision-making.
At the same time, artificial intelligence is actively reshaping how MEL work gets done. Professionals are already using AI tools to process qualitative data, draft reports, and structure evidence narratives; yet most existing training programs have not kept pace with this shift. A forward-looking MEL curriculum must therefore prepare professionals not only for MEL as it is, but as it is becoming.
These realities point to a clear need: a practical, structured, and progressive capacity-building program that equips professionals with real-world MEL competencies while integrating the responsible use of AI as a natural part of modern practice. In direct response, DATA+ Rwanda and Horizon of Excellence have developed a comprehensive professional training program in MEL, designed to build capacity from foundational principles through to intermediate-level application.
2. OBJECTIVES
Overall Objective
The overall objective of this program is to strengthen participants’ capacity to design, implement, and manage effective MEL systems, thereby enhancing program performance, accountability, and organizational learning; and to equip them to do so with confidence in an increasingly AI-enabled professional environment.
Specific Objectives
By the end of the program, participants will be able to:
- Demonstrate a solid understanding of MEL concepts, principles, and frameworks
- Develop Theory of Change and results frameworks that clearly articulate program logic
- Design relevant and measurable indicators to track program performance, including cross-cutting dimensions such as gender and inclusion
- Design and plan evaluations using appropriate methodologies
- Develop key MEL tools, including evaluation matrices and Terms of Reference (ToRs)
- Apply quality standards and ethical principles in evaluation practice
- Communicate findings effectively to support decision-making and organizational learning
- Use AI tools responsibly and critically to enhance MEL documentation, qualitative analysis, and reporting
3. WHO CAN PARTICIPATE
This program is designed for a broad range of professionals involved in program design, implementation, and oversight. It is particularly suitable for early to mid-level practitioners seeking to build or formalize their MEL competencies. Target participants include:
- Monitoring and Evaluation Officers and Assistants
- Project and Program Officers and Coordinators
- Staff from NGOs, development agencies, and government institutions
- Researchers and independent consultants
- Graduate students and early-career professionals pursuing careers in MEL
4. PROGRAM STRUCTURE AND CONTENT
The training is organized into three progressive levels, each building deliberately on the previous to ensure a coherent and comprehensive learning experience. Participants move from foundational concepts through applied monitoring practice to evaluation design and management. A dedicated AI in Practice thread runs across all three levels, introducing AI tools in direct relation to each level’s focus; progressively building responsible AI fluency alongside core MEL skills.
Level 1: Foundations of Monitoring, Evaluation, and Learning
This level introduces participants to the fundamental concepts, frameworks, and principles that underpin effective MEL systems. It establishes the conceptual foundations on which subsequent levels are built.
Participants will explore:
- The role of MEL within development programming and Results-Based Management
- Core MEL concepts and principles
- Development of Theory of Change and logic models
- Design and selection of performance indicators, integrating cross-cutting considerations such as gender, inclusion, and environmental dimensions
Key Outputs:
- A basic Theory of Change
- An indicator reference framework
- A simple monitoring framework
Level 2: Applied Monitoring Systems
Building on the foundations established in Level 1, this level focuses on translating concepts into practical monitoring systems capable of supporting real program implementation, in line with donor and organizational reporting standards.
Participants will learn how to:
- Develop results frameworks and logframes aligned with donor expectations
- Design Performance Indicator Development Plans (PIPs)
- Establish structured monitoring processes and workflows
- Apply quality assurance mechanisms within monitoring systems
- Track implementation progress and performance effectively
- Prepare structured and actionable monitoring reports
Key Outputs:
- A complete results framework and logframe
- An indicator tracking framework
- A monitoring plan
- A basic monitoring report
Level 3: Evaluation Design and Implementation
This level introduces participants to the principles and practice of evaluation, equipping them to design, plan, and manage evaluations with rigor and professional competence.
Participants will cover:
- Types of evaluations: baseline, midline, endline, impact, and process evaluations
- Formulation of evaluation questions and matrices
- Selection of appropriate evaluation designs and methodologies
- Introduction to mixed-methods approaches
- Development of Terms of Reference (ToRs) for evaluations
- Management of evaluation processes and stakeholder engagement
- Application of evaluation ethics and quality standards
Key Outputs:
- An evaluation matrix
- A draft evaluation Terms of Reference (ToR)
- Conceptual evaluation tools
- An evaluation report outline
5. TRAINING APPROACH AND METHODOLOGY
The program adopts a highly interactive and practice-oriented approach, designed to ensure that participants develop not only knowledge but applicable, transferable skills. The methodology is built on the principle of learning by doing: participants engage directly with tools, frameworks, and real-world scenarios throughout each session, leaving with tangible outputs they can immediately use in their work.
Core elements of the methodology include:
- Facilitated sessions that integrate theory with practical application
- Real-world case studies and contextually relevant examples
- Guided development of MEL tools and frameworks during sessions
- Collaborative group work and peer learning
- Scenario-based exercises that simulate real program contexts
- Hands-on AI tool sessions embedded within relevant modules
- Continuous feedback and mentorship from experienced practitioners
6. CAPSTONE PROJECT
To consolidate and integrate learning across all three levels, participants will complete a capstone project at the close of the program. The project requires each participant to design a comprehensive MEL system for a real or simulated program of their choice, incorporating a Theory of Change, a results framework, a monitoring plan, and an evaluation approach. Participants will be encouraged to document where and how they applied AI tools within their capstone, and to reflect critically on those choices. The capstone provides participants with a practical portfolio output demonstrating their professional MEL competency.
7. EXPECTED RESULTS AND IMPACT
Upon successful completion of the program, participants are expected to demonstrate improved capacity to design and manage MEL systems, apply structured approaches to monitoring program performance, and contribute meaningfully to evaluation planning and implementation within their organizations. They will be better positioned to support evidence-based decision-making, foster a culture of learning and accountability, and navigate the evolving role of AI in professional MEL practice.
At an organizational level, the training is expected to contribute to:
- Improved program effectiveness through stronger design and performance tracking
- Stronger accountability mechanisms grounded in credible evidence
- Enhanced learning and adaptive management practices
- A growing cohort of MEL professionals equipped for contemporary and future practice
8. TRAINING DURATION AND MODALITY
The program is designed to be accessible and compatible with the schedules of working professionals.
- Duration: 6 days, delivered over 3 weekends
- Additional Component: Capstone Project (developed between and after sessions)
- Mode of Delivery: Hybrid; both in-person and virtual participation options are available
- Learning Support: Structured materials and facilitator guidance throughout
9. CERTIFICATION
Participants who successfully complete all program components and meet the minimum performance threshold in the capstone project will be awarded a Certificate in Monitoring, Evaluation, and Learning (Foundation to Intermediate Level), issued by DATA+ Rwanda.
10. VALUE PROPOSITION
This program offers a distinctive combination of features that sets it apart from conventional MEL training offerings in the region:
- A structured and progressive learning pathway that develops competency systematically across three levels
- Strong emphasis on practical application and real-world relevance throughout
- Development of concrete, usable MEL tools and frameworks during the training itself
- An integrated AI thread that prepares participants for modern MEL practice; one of the few programs of its kind in the region
- Alignment with international standards and best practices in MEL
- Delivery by experienced professionals with demonstrated practical field expertise
Registration Details
- Fee: 50,000 RWF per participant
- Payment Options:
- Equity Bank Account: 4002200779105
- Mobile Money (MoMo) Pay Code:92570 (Account Name: Data+ Consultant Ltd)
- Deadline for Registration: 6th May 2026
- Contact for Inquiries: +250 784 857 317
- Email:info@dataplusrwanda.com
- Website: www.dataplusrwada.com
- Registration Link:https://dataplusacademy.com/courses
Secure your spot now to elevate your skills and become proficient in Monitoring, Evaluation, and Learning. Spaces are limited, and the program is offered on a first-come, first-served basis. We look forward to your participation in this empowering training opportunity!
KARARA Benon
CEO, DATA+
Email: info@dataplusrwanda.com
Tel: +250 784857317