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Building Consensus to Overcome Research Challenge of Poorly Operationalized High-Need LEA Definition

  • Year 2024
  • NSF Noyce Award # 2243392
  • First Name Melissa
  • Last Name Demetrikopoulos
  • Institution Institute for Biomedical Philosophy
  • Role/Position Co-PI
  • Proposal Type Workshop
  • Workshop Category Track 4: Noyce Research
  • Workshop Disciplines Audience Chemistry, Computer Science, Data Science, Engineering, Geosciences, Life Sciences, Mathematics, Physics, STEM Education (general)
  • Target Audience Co-PIs, Evaluators/Education Researchers, Other Faculty/Staff, Project PIs
  • Topics Assessment/evaluation, Lessons learned from developing/implementing a Track 1 project / Track 2 project / Track 3 project / or Track 4 Research project
  • Additional Presenter(s)

    Molly Weinburgh, Zhan Shi, Daniella Biffi, Dean Williams, John Pecore

Goals

Goal 1: Participants will be able to better recognize how quantitative terms may mask non-operationalized terms and how qualitative descriptions and undefined phrases pose as measurable criteria.Goal 2: Participants will engage in conversations toward building consensus within the Noyce Community on approaches to operationalize the non-defined terms of section 201 of the Higher Education Act of 1965 (20 U.S.C. 1021) defining high-need LEA.Goal 3: Participants will be able to better design measurable goals and objectives for their projects.

Evidence

The definition of high-need LEA spelled out in Section 201 of the HEA of 1965 (and included in the Noyce proposal directions) includes many undefined terms including “low income”, “high percentage”, and “high teacher turnover rate” that lack mathematical/computational definitions, as well as phrases such as, “not teaching in the academic subject areas” which are differentially defined by districts and states. We attempted to find definitions by searching the academic literature as well as many websites (e.g., NCES.ed.gov, Federal Department of Education, numerous State Departments of Education, numerous LEAs). We even attempted asking districts to self-identify their status on various factors, resulting in them asking us to define these terms.

Proposal

Noyce projects are designed to fill the need for highly effective STEM teachers at high-need Local Educational Agencies (LEAs). The program solicitation defines high-need LEAs according to section 201 of the Higher Education Act of 1965 (HEA 1965) (20 U.S.C. 1021). While at first glance the definition appears well operationalized, much of it is not. For example, criteria dealing with student economic circumstances feature cutoffs like “not less than 20%”, yet “low-income”, a crucial term, is undefined. More challenging are criteria concerning teachers which contain un-operationalized terms such as “high percentage”, “not teaching in academic subject areas”, and “high teacher turnover rate” which vary significantly across states and from district to district. Therefore, the necessity of each Noyce project deciding how to operationalize high-need LEAs leads to inconsistencies hindering attempts at meta-analysis and other approaches to synthesize findings across studies. This workshop promotes exploration of varied steps and decision-making trees to operationalize high-need LEAs and build consensus in the Noyce Community. This will be accomplished by guided small group breakout sessions followed by consensus building with all participants. The workshop will provide opportunity to clearly operationalize selection criteria for inclusion while maintaining the purpose of these projects. As part of this process, we will share steps and thought process we went through to operationaliz

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This material is based upon work supported by the National Science Foundation (NSF) under Grant Numbers DUE-2041597 and DUE-1548986. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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