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This report is the fifth in a series concerning English language proficiency (ELP) assessments for English learners (ELs) in kindergarten through 12th grade in the United States. The series, produced by Educational Testing Service (ETS), is intended to provide theory‐ and evidence‐based principles and recommendations for improving next‐generationELPassessment systems, policies, and practices and to stimulate discussion on better serving K–12ELstudents. The first report articulated a high‐level conceptualization of next‐generationELPassessment systems (Hauck, Wolf, & Mislevy, 2016). The second report addressed accessibility issues in the context ofELPassessments forELsandELswith disabilities (Guzman‐Orth, Laitusis, Thurlow, & Christensen, 2016). The third report focused on critical policy and research issues of summativeELPassessments that state use for accountability purposes (Wolf, Guzman‐Orth, & Hauck, 2016). The fourth report dealt with one of the major uses ofELPassessments—the initial identification and classification of ELs (Lopez, Pooler, & Linquanti, 2016). The present report discusses approaches to using automated scoring technology for the evaluation of student‐spoken responses on K–12ELPassessments. As many states have begun to use computer‐basedELPassessments, there is a growing interest in automated scoring of spoken responses to increase the efficiency of scoring. This report delineates major areas to consider in using automated speech scoring for K–12ELPassessments (i.e., assessment construct and task design, scoring and score reporting, and artificial intelligence (AI) model development and test delivery) and makes recommendations for states on how to evaluate these considerations and determine a path forward.
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