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Aarti P. Bellara

Researcher at University of South Florida

Publications -  23
Citations -  383

Aarti P. Bellara is an academic researcher from University of South Florida. The author has contributed to research in topics: Educational leadership & Population. The author has an hindex of 7, co-authored 19 publications receiving 322 citations. Previous affiliations of Aarti P. Bellara include University of Connecticut.

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The Current State of Assessment Education Aligning Policy, Standards, and Teacher Education Curriculum

TL;DR: In this article, the alignment between teacher education accreditation policies, professional standards for teacher assessment practice, and preservice assessment course curriculum was analyzed through a curriculum alignment methodology involving two policy documents, two professional standards documents, and syllabi from 10 Florida-based, Council for Accreditation of Teacher Education certified teacher education.

Propensity score analysis and assessment of propensity score approaches using sas ® procedures

TL;DR: The steps required for a propensity score analysis are described, and SAS code that can be used to implement each step is presented, and the potential bias in estimated effects obtained from observational studies is investigated.
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Pedagogies for Preservice Assessment Education: Supporting Teacher Candidates' Assessment Literacy Development

TL;DR: The authors examined pedagogies that support positive changes in teacher candidates' conceptions of assessment and found four explicit pedagogical constructs that teacher candidates identified as instrumental in contributing to their learning about assessment.
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The Hidden Curriculum Candidate Diversity in Educational Leadership Preparation

TL;DR: In this paper, the authors describe a process of self-assessment attuned to equity and justice in the policies and practices that affect student diversity, namely, those associated with the selection of candidates.
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Does the Package Matter? A Comparison of Five Common Multilevel Modeling Software Packages:

TL;DR: The results of this study suggest that applied researchers should carefully consider which random effects they wish to include in their models, as well as convergence rates, when modeling multiple randomly varying slopes of different magnitudes.