Surveys are a critical resource for social, economic, and health research. The ability to efficiently collect these data and develop accurate post-survey adjustments depends upon reliable data about effort required to recruit sampled units. Level-of-effort paradata are data generated by interviewers during the process of collecting data in surveys. These data are often used as predictors in nonresponse adjustment models or to guide data collection efforts. However, recent research has found that these data may include measurement errors, which would lead to inaccurate decisions in the field or reduced effectiveness for adjustment purposes (Biemer, et al., 2013; West and Little, 2013). In order to assess whether errors occur in level-of-effort paradata, we introduce a new source of validation data for call records — Global Positioning System (GPS) data generated by smartphones carried by interviewers. We examine the quality of the GPS data and then use the GPS data to characterize interviewer travel within sampled area segments. We also link the GPS data with the interviewer-reported call records in order to identify potential errors in the call records. Given the lack of a gold standard, we perform a sensitivity analysis under various assumptions to see how this would change our conclusions.