Data Collection Methods in Monitoring and Evaluation: Quantitative, Qualitative, and Mixed Approaches
Author: Dr. Anna Neya Kazanskaia
Publisher: NEYA Global Publishing
Journal: NEYA Global Journal of Non-Profit Studies (ERDO)
Year: 2025
DOI: https://doi.org/10.64357/neya-gjnps-me-datacollection-2025
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About the Article
Data collection is a cornerstone of Monitoring and Evaluation (M&E), shaping the quality, reliability, and usefulness of evidence for decision-making in development programs. This article examines three main methodological traditions—quantitative, qualitative, and mixed methods—highlighting their respective strengths, limitations, and applications. Quantitative approaches, such as surveys and structured interviews, generate measurable insights, while qualitative techniques, including focus groups, case studies, and participatory tools, provide contextual depth. Mixed-methods designs integrate both, enabling holistic perspectives on program outcomes.
The discussion also addresses technological innovations such as mobile surveys, GIS, and social media analytics, which have expanded possibilities for M&E, especially in low-resource contexts. Ethical considerations, including informed consent, privacy, and cultural sensitivity, are underscored as essential for responsible practice. The article concludes that effective data collection requires balancing rigor, ethics, and contextual adaptability, ensuring that M&E systems foster accountability, participation, and sustainable development outcomes.
Key Topics
- Foundations of data collection in M&E
- Quantitative approaches: surveys, interviews, experiments, observations
- Qualitative approaches: focus groups, case studies, participatory methods
- Mixed-methods designs and integration strategies
- Technological innovations: mobile surveys, GIS, big data
- Ethical principles in data collection
- Challenges and solutions in low-resource settings
- Balancing rigor, adaptability, and participation
Academic Value
This article advances scholarship on M&E by critically assessing methodological traditions and their integration. It emphasizes that robust data collection is not only a technical process but also an ethical and participatory practice. By examining innovations and challenges in diverse contexts, the study provides academics with insights into evolving evaluation methodologies and offers practitioners guidance on designing data collection systems that are feasible, inclusive, and context-sensitive. Ultimately, it situates data collection as a dynamic process central to evidence-based decision-making and sustainable development.
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