Richardson, IrvingLeone, Elizabeth Lynn2023-04-272023-04-272023-04-11https://hdl.handle.net/10474/3724Data collection and analyzation practices for English language development services are scarcely found in research, but needed in the subgroup of minority students commonly known as English language learners (Wiseman & Bell, 2021). Wiseman and Bell (2021) identified ELLs as one of the most under-documented student subgroups in the American educational system. This quantitative correlational survey study explored the importance of data collection and analyzation practices for New Hampshire ELD educators through the lens of Mandinach et al.'s (2006) data-driven decision-making (DDDM) framework. DDDM is the process of identifying data, collecting it to be analyzed and interpreted, and using it to set goals to improve educational experiences (Mandinach & Schildkamp, 2021a). The present study explored the outcome of the dependent variable of teacher self-reported data collection and analyzation, and teacher-perceived importance of data through a cross-sectional survey and correlational analysis, using the length of teaching experience as the independent variable in the measurement of covariation. Based on the findings, ELD data standards may be evaluated and better informed by the current data collection and analyzation practices in New Hampshire public school districts. With meaningful data and intentional analysis, the DDDM framework and research suggest that instructional quality will likely increase to positively impact student achievement (Dodman et al., 2021), offering exponential benefit to a subgroup of struggling ELLs (Garver, 2022).en-USAuthor retains all ownership rights. Further reproduction in violation of copyright is prohibited.English Language--Study and Teaching--Foreign SpeakersEducational AchievementInstructional EffectivenessData EfficacyData-Driven Decision MakingEnglish Language DevelopmentESSATESOLTitle IIIDissertation