Education researchers use surveys widely. Yet, critics question respondents’ ability to provide high-quality responses. As schools increasingly use student surveys to drive policymaking, respondents’ (lack of) motivation to provide quality responses may threaten the wisdom of using surveys for data-based decision-making. To better understand student satisficing (sub- optimal responding on surveys) and its impact on data quality, we examined the pervasiveness and impact of this practice on a large-scale social-emotional learning survey administered to 409,721 students in grades 2-12. Findings indicated that despite the prevalence of satisficing in our sample, its impact on data quality appeared more modest than anticipated. We conclude by providing an accessible approach for defining and calculating satisficing for researchers, practitioners, and policymakers working with large-scale datasets.