Incorporating English Learner Progress into State Accountability Systems

This paper identifies key issues and questions for state decision makers to consider and explore with regard to how states should include English learners (ELs) in states' accountability systems under ESSA. The primary audience is anyone in a state agency engaged in making decisions about the state’s accountability system and how ELs are included in that system. According to Hakuta, co-author of this paper and its accompanying paper (Hakuta & Pompa, 2017; see Related Resource below), this technical paper serves four purposes (the list is fully quoted from Hakuta & Pompa, 2017, p. 1):

  1. It illustrates well-known facts about English language proficiency development that could be considered in the creation of an accountability plan.
  2. It delivers a primer on how to model growth in English language proficiency, and the strengths and weaknesses of different options.
  3. It demonstrates the implications of choosing a particular model based on strategy parameters associated with that decision, such as minimum N-size, or counting the number of years that former EL students are included in the EL subgroup.
  4. It encourages states to test each model with their own current data, because different state contexts may impact outcomes.

State leaders are encouraged to engage in thoughtful deliberation around how these issues apply to their own state context by simulating similar scenarios using their existing data and applying their analysis to the construction of the state plan.

Content Comments 

This paper presents informative, yet highly technical, information on growth modeling options for states to consider when developing a meaningful English language progress component of a state's overall accountability system. The authors first present background on ESSA accountability regulations, using descriptive analyses and modeling examples. Then the paper presents several models related to monitoring EL progress (e.g., value added, student growth, simple gain), using data from two states in examples for each model. The authors provide guiding questions for state accountability members to think about when developing an appropriate accountability model for ELs in their state.