| Abstract:
This skill building session will focus on the association between field work and data quality criteria using a data assessment model and examples of data collection instruments as solutions to improve data quality for evaluations. Good quality data to measure performance results often presents challenges to project implementers. There are political, economical, social, cultural, environmental issues and circumstances present in all situations that affect project implementation. Moreover, these circumstances also affect the data collection process and hence data quality. To help minimize these circumstances, data collection instruments can be designed to improve data quality by observing data quality criteria: validity, integrity, precision, reliability, timeliness. These criteria will be elaborated in a data assessment model as well as some of the data collection instruments, such as monitoring procedures, questionnaires, data entry guides, data definition codebook.
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