Evidence for better decisions
Digital Data Collection

Using KoboToolbox for High-Quality Field Data Collection

KoboToolbox improves field data quality when it is combined with strong questionnaire design, validation rules, training and daily review.

Using KoboToolbox for High-Quality Field Data Collection

Digital tools do not automatically create quality data

KoboToolbox can reduce many errors associated with paper forms, but quality depends on design. Poor question wording, weak skip logic and unclear response options can still produce unreliable data. The technology must therefore be supported by strong survey design and field protocols.

Build quality into the XLSForm

A good XLSForm includes relevant constraints, required fields, skip logic, calculations, hints and response choices that match the analysis plan. It should also capture metadata that helps supervisors review fieldwork progress and identify unusual patterns.

Pilot on real devices

Testing should happen on the same types of phones or tablets that enumerators will use. The pilot should check translation, timing, skip logic, response options, GPS capture, consent flow and export structure.

Review data every day

Daily review is essential. Supervisors should check missing values, interview duration, duplicate submissions, inconsistent answers, GPS location, enumerator performance and outlier responses while field teams can still correct procedures.

Document the final dataset

After data collection, the cleaned dataset should be accompanied by a codebook, cleaning log and explanation of indicator calculations. This strengthens transparency and makes the dataset easier to use in future analysis.

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