Format: Live instructor-led online training via Zoom / Microsoft Teams

Qualitative Analysis for Monitoring and Evaluation Professionals with AI Training Course

Course Introduction

Qualitative Analysis for Monitoring and Evaluation Professionals with AI is an advanced and practical training course designed to equip monitoring and evaluation practitioners, researchers, development professionals, project managers, and data analysts with the skills required to collect, manage, analyze, interpret, and report qualitative data using both traditional methodologies and modern Artificial Intelligence (AI) tools. As organizations increasingly seek evidence-based decision-making and impact-driven programming, qualitative analysis has become a critical component of monitoring, evaluation, accountability, and learning (MEAL) systems. This course integrates qualitative research methodologies with cutting-edge AI technologies to enhance data analysis efficiency, accuracy, and insight generation.

The course provides participants with comprehensive knowledge of qualitative research design, data collection techniques, coding frameworks, thematic analysis, content analysis, narrative analysis, grounded theory, case study methodologies, and mixed-methods integration. Participants will learn how AI-powered tools can support transcription, coding, sentiment analysis, thematic identification, text mining, data visualization, report generation, and knowledge management. The training explores the application of AI in software such as NVivo, Atlas.ti, MAXQDA, ChatGPT, Microsoft Copilot, Gemini, and other emerging qualitative analytics platforms.

Through practical exercises, real-world development project datasets, focus group discussions, key informant interviews, field notes, beneficiary feedback systems, and humanitarian and development case studies, participants will gain hands-on experience in transforming qualitative information into actionable insights. The course emphasizes ethical AI use, data quality assurance, triangulation, evidence generation, stakeholder engagement, and learning-oriented evaluation practices.

Upon successful completion of this training, participants will be able to design qualitative studies, conduct rigorous qualitative analysis, leverage AI tools for efficient data processing, generate meaningful findings, communicate evidence effectively, and strengthen monitoring and evaluation systems. The course enhances organizational learning, accountability, program effectiveness, and impact measurement through advanced qualitative analysis techniques supported by artificial intelligence.

Course Objectives

Upon completion of the course, participants will be able to:

1.     Understand qualitative research and evaluation methodologies.

2.     Design qualitative data collection strategies for M&E projects.

3.     Apply coding and thematic analysis techniques effectively.

4.     Utilize AI tools for qualitative data analysis and interpretation.

5.     Conduct content, narrative, and discourse analysis.

6.     Analyze focus group discussions and key informant interviews.

7.     Improve data quality and reliability in qualitative research.

8.     Integrate qualitative findings into monitoring and evaluation systems.

9.     Develop evidence-based reports and recommendations.

10.  Strengthen organizational learning and decision-making through AI-assisted qualitative analysis.

Organizational Benefits

1.     Enhanced monitoring and evaluation effectiveness.

2.     Improved evidence-based program decision-making.

3.     Faster qualitative data processing and reporting.

4.     Increased accuracy and consistency in data analysis.

5.     Enhanced learning and knowledge management systems.

6.     Improved accountability to stakeholders and beneficiaries.

7.     Better understanding of project outcomes and impacts.

8.     Increased efficiency through AI-powered analytics.

9.     Stronger evaluation and reporting capabilities.

10.  Improved organizational performance and program effectiveness.

Target Participants

·       Monitoring and Evaluation Officers

·       MEAL Specialists

·       Researchers and Research Assistants

·       Project Managers

·       Program Officers

·       Data Analysts

·       Development Practitioners

·       Humanitarian Professionals

·       Impact Evaluation Specialists

·       Social Scientists

·       Policy Analysts

·       NGO and CSO Professionals

·       Government Officers

·       Consultants and Evaluators

·       Professionals involved in qualitative research and evaluation

Course Outline

Module 1: Foundations of Qualitative Research and Monitoring & Evaluation

1.     Introduction to qualitative research methods

2.     Role of qualitative analysis in M&E

3.     Research paradigms and methodologies

4.     Qualitative versus quantitative approaches

5.     Ethical considerations in qualitative studies

6.     Case Study: Using qualitative evidence in development programs

Module 2: Qualitative Data Collection Techniques

1.     Designing qualitative research instruments

2.     Conducting key informant interviews

3.     Facilitating focus group discussions

4.     Observation and field note methodologies

5.     Digital qualitative data collection tools

6.     Case Study: Community-based project assessment

Module 3: Data Management and Preparation

1.     Organizing qualitative datasets

2.     Data transcription and translation

3.     Data cleaning and quality assurance

4.     Managing interview and focus group records

5.     Data storage and security considerations

6.     Case Study: Preparing large-scale evaluation datasets

Module 4: Coding and Thematic Analysis

1.     Introduction to coding frameworks

2.     Open, axial, and selective coding

3.     Developing codebooks and coding structures

4.     Identifying themes and patterns

5.     Thematic analysis techniques

6.     Case Study: Thematic analysis of beneficiary feedback

Module 5: Content Analysis and Narrative Analysis

1.     Principles of content analysis

2.     Narrative analysis techniques

3.     Discourse analysis methodologies

4.     Text interpretation frameworks

5.     Identifying key messages and trends

6.     Case Study: Analyzing stakeholder narratives

Module 6: AI Applications in Qualitative Analysis

1.     Introduction to AI in qualitative research

2.     AI-assisted coding techniques

3.     Automated thematic analysis tools

4.     AI-powered transcription technologies

5.     Ethical use of AI in research

6.     Case Study: Using AI to analyze large qualitative datasets

Module 7: NVivo, Atlas.ti and MAXQDA for Qualitative Analysis

1.     Introduction to qualitative analysis software

2.     Importing and organizing qualitative data

3.     Coding within software environments

4.     Querying and exploring datasets

5.     Visualizing qualitative findings

6.     Case Study: Conducting a complete software-based analysis

Module 8: AI-Powered Text Mining and Sentiment Analysis

1.     Fundamentals of text mining

2.     Sentiment analysis applications

3.     Natural language processing concepts

4.     Keyword and phrase extraction

5.     Trend identification techniques

6.     Case Study: Sentiment analysis of stakeholder feedback

Module 9: Triangulation and Mixed Methods Integration

1.     Principles of triangulation

2.     Integrating qualitative and quantitative data

3.     Mixed methods research approaches

4.     Data validation techniques

5.     Strengthening evidence quality

6.     Case Study: Mixed-method evaluation of development interventions

Module 10: Data Visualization and Reporting

1.     Visualizing qualitative findings

2.     Storytelling with qualitative evidence

3.     Developing analytical reports

4.     Dashboard development for M&E reporting

5.     Communicating findings to stakeholders

6.     Case Study: Developing evidence-based evaluation reports

Module 11: Knowledge Management and Learning Systems

1.     Organizational learning frameworks

2.     Capturing lessons learned

3.     Knowledge sharing strategies

4.     AI-supported knowledge management

5.     Learning-oriented evaluation systems

6.     Case Study: Institutionalizing organizational learning

Module 12: Advanced Qualitative Evaluation and AI Innovation

1.     Emerging trends in qualitative analysis

2.     Advanced AI applications in M&E

3.     Predictive insights from qualitative data

4.     Building AI-supported evaluation systems

5.     Developing qualitative analysis action plans

6.     Case Study: AI-enabled monitoring and evaluation transformation

General Information

1.     Customized Training: All our courses can be tailored to meet the specific needs of participants.

2.     Language Proficiency: Participants should have a good command of the English language.

3.     Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.

4.     Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).

5.     Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.

6.     Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.

7.     Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.

8.     Additional Services: Accommodation, pickup services, freight booking, and visa processing arrangements are available upon request at discounted rates.

9.     Equipment: Tablets and laptops can be provided to participants at an additional cost.

10.  Post-Training Support: We offer one year of free consultation and coaching after the course.

11.  Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.

12.  Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.

13.  Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.

14.  Website: Visit our website at www.fdc-k.org for more information.