Traditional feedback mechanisms often rely on time-consuming surveys and focus groups, leading to delayed insights and a limited understanding of a project's real-time impact. These methods can also be difficult to scale and may not reach marginalized or hard-to-access populations. This training course is designed to empower M&E professionals to master AI chatbots for real-time beneficiary feedback. By leveraging conversational AI, participants will learn how to build intelligent systems that can engage beneficiaries in natural, two-way conversations, collecting immediate and continuous data on satisfaction, challenges, and outcomes directly from the communities they serve.

This comprehensive program provides a practical, hands-on roadmap for ethically and effectively deploying chatbots to enhance M&E. Participants will gain skills in everything from conversational design and natural language processing (NLP) to sentiment analysis and data visualization. The course is a strategic investment for organizations committed to empowering the voices of those they serve, ensuring their work is a force for positive change in a world that needs it most.

Duration: 10 days

Target Audience:

• M&E Specialists
• Program and Project Managers
• Communications Professionals
• Humanitarian Aid Workers
• Researchers
• Civil Society Leaders
• Public Policy Analysts
• Human-Centered Design Practitioners
• Consultants
• Strategic Planners

Objectives:

• Understand the core principles of conversational AI and its relevance to M&E.
• Master the process of designing a chatbot-driven M&E framework.
• Learn how to select and measure key indicators of real-time feedback.
• Develop a data collection and analysis plan for chatbot data.
• Integrate ethical considerations and safety protocols.
• Build a more participatory and inclusive approach to monitoring.
• Communicate findings to different audiences while managing risk.
• Ensure ethical considerations and safety protocols in data collection.
• Foster a culture of continuous learning and adaptive management.
• Apply M&E techniques to a wide range of sectors.

Course Modules:

Module 1: Introduction to AI Chatbots for M&E

• The limitations of traditional feedback mechanisms
• Defining conversational AI and its purpose
• The business case for a chatbot-driven approach
• An overview of the AI chatbot workflow
• The difference between a simple and a comprehensive system

Module 2: Foundational Concepts for Conversational AI

• The importance of a clear and focused research question
• Understanding the context and its impact on the project
• The role of a program's theory of change
• The importance of a clear and testable hypothesis
• The "do no harm" principle in an M&E context

Module 3: Designing a Chatbot-Driven Framework

• The importance of a clear and focused framework
• The role of a "digital" framework
• Integrating a gender and social inclusion analysis
• The importance of a "risk and mitigation" plan
• Case studies on effective framework design

Module 4: Conversational Design and User Experience

• The importance of a clear and consistent reporting style
• The use of a simple survey and a focus group discussion
• The role of a "social mapping" and a "trend analysis"
• The use of a simple survey and a focus group discussion
• Practical labs on a basic data collection tool

Module 5: Data Collection and Security

• The importance of a clear and secure data collection protocol
• The role of an encrypted mobile data collection app
• The use of a simple and secure database
• The importance of a data backup and recovery plan
• Protocols for handling sensitive and confidential data

Module 6: Data Analysis and Interpretation

• The importance of a clear data analysis plan
• Using simple statistical analysis for quantitative data
• The role of qualitative data analysis methods
• Interpreting findings from a conversational perspective
• The importance of data triangulation

Module 7: The Art of Storytelling with Data

• The difference between a simple visual and a data story
• The importance of a clear and compelling narrative
• Using dashboards and visualizations to communicate insights
• The role of a "data story map"
• Practical labs on building a data story

Module 8: Ethical Considerations and Safety

• The importance of a "do no harm" approach
• Ensuring the safety and privacy of participants
• The role of informed consent in a crisis
• The importance of a community-led ethical review process
• Protocols for handling sensitive and potentially harmful data

Module 9: M&E for a Diverse Audience

• The importance of knowing your audience
• The role of a "stakeholder analysis"
• Designing reports and dashboards for non-technical audiences
• The importance of accessibility and inclusivity
• Case studies on communicating with different audiences

Module 10: Mainstreaming M&E

• How to integrate M&E into the project cycle
• The importance of a phased implementation strategy
• The role of M&E in the project cycle
• Building a culture of adaptive management
• Case studies on successful integration

Module 11: M&E for a Diverse Sector

• M&E for a technology project
• M&E for a social enterprise
• M&E for a humanitarian project
• M&E for a climate action project
• M&E for a governance project

Module 12: The Role of the M&E Professional

• Shifting from a technician to a facilitator
• The skills required for an M&E professional
• Managing power dynamics and group conflicts
• The importance of a non-judgmental and empathetic approach
• The ethical responsibilities of the M&E professional

Module 13: CBM and Conversational AI

• The potential of community-based monitoring with a focus on conversational AI
• Training community members as monitors
• The importance of a participatory approach
• The role of a feedback mechanism for continuous learning
• The long-term benefits of a community-led system

Module 14: Practical Application and Simulation

• A hands-on simulation of a real-world project
• Participants work in teams to design an M&E framework
• Troubleshooting common challenges in data collection
• Analyzing and interpreting a set of data
• Peer review and feedback sessions on framework design

Module 15: The Future of M&E

• The role of AI and machine learning in automated analysis
• The potential of blockchain for data integrity
• The use of new data sources (e.g., satellite imagery)
• The rise of complexity-aware M&E
• The long-term implications for the sector

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: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute 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 Skills for Africa Training Institute 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: info@skillsforafrica.org, training@skillsforafrica.org  Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 10 working days before commencement of the training.