The Value of Stakeholder Engagement in Developing the Home Language Survey Data Quality Self-Assessment Tool

• In Event: Strengthening the Validity and Utility of Home Language Surveys to Identify Potential English Learners

Abstract

All states and the District of Columbia require or recommend districts use a state- or district-created Home Language Survey (HLS) as a screening tool to identify students who are potential English learner students (Bailey & Kelly, 2010; U.S. Department of Education, 2012). Recent studies, however, point to multiple factors that often undermine HLS data quality (Bailey & Kelley, 2010, 2012; Linquanti & Bailey, 2014). Poor data quality contributes to the under‐ and over‐identification of potential English learner students in many school districts and challenges State Education Agency (SEA) efforts to ensure the allocation of resources to support these students’ programs, services, and subsequent success. Studies suggest that variation in HLS data quality may stem from state practices as much as local practices (Linquanti & Bailey, 2014); however, SEAs currently lack tools and processes to gather and make sense of information from districts that can help them identify and address practices that may be undermining HLS data quality.
This paper describes a research-based project of the English Language Learners Research Alliance, one of eight alliances of the Regional Educational Laboratory–Northeast and Islands (REL-NEI). Specifically, the authors describe several ways in which a two-year collaboration with SEA and district stakeholders has contributed to the development and refinement of the Home Language Survey Data Quality Self-Assessment Tool. This tool is designed to support state and district efforts to improve the quality of data used at the start of a multi-step district process to identify English learner students. By incrementally revising the Self-Assessment Tool with input from stakeholders, the REL-NEI project team is strengthening the relevance, clarity, purpose, and action-based focus of the tool, resulting in a more useful product for practitioners. The paper concludes by describing a Connecticut stakeholder group’s efforts to address data quality challenges that were identified through the initial use of the Self-Assessment Tool. Publication of the tool is forthcoming and will support stakeholders in and beyond the Northeast region to improve the quality of data gathered through home language surveys.

Authors

• Dan Mello, WestEd

• Susan F. Henry, Harvard University

• Caroline E. Parker, Education Development Center, Inc.

• Maria-Paz Avery, Education Development Center, Inc