A
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.
Journal ArticleDOI
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.
Journal ArticleDOI
Does the Package Matter? A Comparison of Five Common Multilevel Modeling Software Packages:
D. Betsy McCoach,Graham G. Rifenbark,Sarah D. Newton,Xiaoran Li,Janice Kooken,Dani Yomtov,Anthony J. Gambino,Aarti P. Bellara +7 more
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.