Driven by Data: Using licensure tests to build a strong, diverse teacher workforce

With the release of data never before published, NCTQ focuses on a uniquely challenging point of teacher certification: licensure tests. Their report, Driven by Data: Using Licensure Tests to Build a Strong, Diverse Teacher Workforce, raises many important considerations around the use of licensure exams and their results. After a careful analysis of available data, NCTQ offers the following recommendations:

Recommendation for collaborative action

  • Working together, state education agencies,  teacher prep programs, test publishers,  and school districts need to establish or verify alignment between teacher preparation, licensure tests,  and the job demands of elementary classrooms. 

Recommendations for States

  • Use a valid and reliable elementary education licensure test that separately measures knowledge of language arts, mathematics, science, and social studies. 
  • Set the minimum score needed to pass the licensure  test  at the score that has been recommended by the standard setting process.
  • Improve access to and use of assessment data.  
  • Make sure that the state’s needs are reflected in agreements made with licensure test publishers. 

Recommendations for Teacher Preparation Programs 

  • Look to coursework, not just test prep strategies, to best prepare candidates in the content they need to teach elementary grades. 
  • Review and act on pass rate data to monitor program effectiveness and to inform improvements.
  • Use diagnostic testing to identify candidates’ strengths and weaknesses. 

Recommendations for Testing Companies

  • Standard operating procedure should be to provide first attempt and best-attempt pass rate data and data on the number of attempts for all test takers at the institution level to state education agencies and preparation programs.
  • Strengthen data collection to provide more accurate program-level data.
  • Work with the education field to explore concerns around bias in testing. 

For more, see https://www.nctq.org/publications/Driven-by-Data:-Using-Licensure-Tests-to-Build-a-Strong,-Diverse-Teacher-Workforce

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