Capturing Data Collector Quality Through Field-Based Structured Observation: Toward Standardized, Evidence-Based Core Competencies

• In Event: 43.077 - MTCC Roundtable Session 15
  In Roundtable Session: 43.077-5 - Innovative Approaches

Abstract

It is widely understood that those hired and trained to collect research data have a large and lasting effect on resulting data quality; this is particularly true in developing contexts, where conditions are unpredictable. Yet we are not aware of standardized, evidence-based core competencies of data collector quality. In this pilot study, we introduce an observation protocol designed around inductively- and deductively-generated core competencies of data collector quality. Based on observations of 37 data collectors from eight supervisors in the Diffa region of Niger, we investigate the psychometric functioning of the instrument, including its criterion validity, internal consistency, and latent factors. We argue that evidence-based competencies can be utilized for data collector selection, training, monitoring, and ongoing support.

Authors

• Lindsay Brown, New York University

• Erick Ngoga, International Rescue Committee

• Ha Yeon Kim, New York University

• John Lawrence Aber, New York University Steinhardt