Demographic information often proves useful for finding subpopulations in educational data. Unfortunately, it is often not collected in the log files of online learning systems, which serve as one of the primary sources of data for the Educational Data Mining community. Recent work has sought to address this issue by investigating school-level differences in demographics, which can be used to discover trends in data where individual-level variation may be difficult or impossible to acquire. In this study, we use this approach to investigate the effect of demographic patterns on hint usage in an elementary level mathematics system, comparing this use to performance and motivational measures. In doing so, we expand upon the research into help-seeking behaviors, which typically takes a cognitive approach. Our results suggest the need to better understand what social factors are most likely to motivate help-seeking behaviors, particularly since research on their effectiveness has been mixed. [For the full proceedings, see ED599096.]