Skip to main content
M&E Studio
Prompts
Indicators
AI for M&E
RubricsPlugins and Skills
M&E Resources
M&E GuidesReference Library
Services
AI Advisory for M&EWorkflowsAboutContact Us
FR · FrançaisES · Español
monitoringevaluationstudio.com/resources/reference/topics/data-collection

From M&E Studio · monitoringevaluationstudio.com/resources/reference/topics/data-collection · free to use with credit

M&E Studio

AI for M&E. Built for the work you're already doing.

AI for M&E

  • AI for M&E
  • Prompts
  • Rubrics
  • Plugins and Skills

M&E Resources

  • M&E Guides
  • Reference Library
  • Indicators

Company

  • Services
  • Workflows
  • About
  • Contact
  • Mission
  • LinkedIn

Legal

  • Terms
  • Privacy
  • Accessibility

© 2026 Logic Lab LLC. Free content: use and share with credit and a link; do not republish whole pages. Terms and content use

  1. M&E Library
  2. Topics
  3. Data Collection & Quality

Data Collection & Quality

Methods, tools, and sampling approaches for collecting M&E data in the field, plus the quality assurance practices that keep data trustworthy through analysis. Surveys, interviews, focus groups, mobile tools, DQAs, cleaning, and validation.

How Do I Choose?

Baseline vs Endline vs Midline Surveys ExplainedWhen you need baseline, midline, and endline surveys, what they collect, and what to do when you missed your baseline.How to Conduct a Data Quality AssessmentA step-by-step guide to conducting a DQA using the five standard dimensions. How to select indicators, design verification procedures, conduct the site visit, and write the DQA report.KoboToolbox vs ODK vs SurveyCTOThe three most common mobile data collection platforms for M&E, compared on features, cost, offline capability, skip logic, and hosting. Plus CommCare for case management.Qualitative vs Quantitative vs Mixed MethodsQualitative, quantitative, and mixed methods are not a quality ranking. They answer different questions. Here's when to use each, how to combine them, and what integration actually looks like.Surveys vs Interviews vs Focus GroupsThe three most common M&E data collection methods, compared. Surveys tell you how many, interviews tell you why, focus groups tell you what people agree on.

Overviews (9)

Baseline DesignA structured approach to collecting initial condition data that directly informs project decisions, minimizes burden, and enables valid comparison with endline measurements.Data Collection BurdenThe total time, effort, and resources required from respondents and implementers to complete data collection activities, balanced against data quality needs and program capacity.Data ManagementThe systematic processes for collecting, storing, securing, and maintaining data quality throughout the data lifecycle to ensure information is accurate, accessible, and usable for decision-making.Data Quality AssuranceA systematic process for verifying that collected data meets five quality dimensions, Validity, Integrity, Precision, Reliability, and Timeliness, ensuring data is fit for decision-making.Focus Group DiscussionsA qualitative data collection method that brings together 6-10 participants to discuss a specific topic, generating rich insights through group interaction and shared experiences.Key Informant Interviews (KII): Meaning, Method and When to Use ThemIn-depth, semi-structured interviews with individuals selected for their specific knowledge, experience, or perspectives relevant to the evaluation questions.Observation Methods: Collecting Data by Watching What Actually HappensA systematic approach to collecting data by directly watching and recording behaviors, interactions, and processes as they occur in natural settings.Survey DesignThe process of designing structured questionnaires and survey protocols to collect reliable, valid, and actionable data from a defined population.Triangulation: Using Multiple Sources and Methods to Verify FindingsUsing multiple data sources, methods, or perspectives to cross-verify findings and strengthen the validity of evaluation conclusions.

Quick Reference (8)

BiasCensus vs Sample: When to Use Each in M&EMidlinePrimary vs Secondary DataQualitative DataQuantitative DataReliabilityValidity (Internal & External)

AI Guides

How to Build Better Surveys with AIMost AI survey tools stop at generating questions. This guide covers the full lifecycle: choosing question types, catching bias, adding skip logic, and piloting before you deploy.How to Clean Messy M&E Data with AITurn 15 hours of manual cleaning into 2 with a 4-step workflow that combines free tools and AI validation to catch errors human review misses.How to Protect Data Privacy When Using AI for M&EBeneficiary data belongs to beneficiaries, not AI servers. The SAFE Framework helps you use AI tools without risking a data protection breach, donor compliance violation, or loss of community trust.

Explore Other Topics

EvaluationDesignIndicatorsSamplingAnalysis

Start with a tool

  • How to Build Better Surveys with AIDraft questions and logic