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Suzuki, Sara; Morris, Stacy L.; Johnson, Sara K. – Journal of Adolescent Research, 2021
How researchers use statistical analyses shapes their research toward or away from an anti-racist agenda. In this article, we demonstrate how developmental scientists can use the QuantCrit framework to critically examine the process of conducting quantitative analyses. In particular, we focus on mixture modeling to clearly demonstrate how the…
Descriptors: Statistical Analysis, Critical Theory, Race, Minority Groups
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He, Lingjun; Levine, Richard A.; Fan, Juanjuan; Beemer, Joshua; Stronach, Jeanne – Practical Assessment, Research & Evaluation, 2018
In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of…
Descriptors: Institutional Research, Regression (Statistics), Statistical Analysis, Data Analysis
Schweig, Jonathan; McEachin, Andrew; Kuhfeld, Megan; Mariano, Louis T.; Diliberti, Melissa Kay – RAND Corporation, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
Jonathan Schweig; Andrew McEachin; Megan Kuhfeld; Louis T. Mariano; Melissa Kay Diliberti – Grantee Submission, 2021
The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…
Descriptors: Student Placement, COVID-19, Pandemics, Student Characteristics
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Rankin, Jenny Grant – Universal Journal of Educational Research, 2016
Most data-informed decision-making in education is undermined by flawed interpretations. Educator-driven interventions to improve data use are beneficial but not omnipotent, as data misunderstandings persist at schools and school districts commended for ideal data use support. Meanwhile, most data systems and reports display figures without…
Descriptors: Evidence Based Practice, Data Interpretation, Information Utilization, Standards
Porter, Kristin E.; Balu, Rekha – MDRC, 2016
Education systems are increasingly creating rich, longitudinal data sets with frequent, and even real-time, data updates of many student measures, including daily attendance, homework submissions, and exam scores. These data sets provide an opportunity for district and school staff members to move beyond an indicators-based approach and instead…
Descriptors: Models, Prediction, Statistical Analysis, Elementary Secondary Education
Rankin, Jenny Grant – ProQuest LLC, 2013
There is extensive research on the benefits of making data-informed decisions, but research also contains evidence many educators incorrectly interpret student data. Meanwhile, the types of detailed labeling on over-the-counter medication have been shown to improve use of "non"-medication products, as well. However, data systems most…
Descriptors: Data, Data Analysis, Accuracy, Decision Making
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Lynch, David; Smith, Richard; Provost, Steven; Madden, Jake – Journal of Educational Administration, 2016
Purpose: This paper argues that in a well-organised school with strong leadership and vision coupled with a concerted effort to improve the teaching performance of each teacher, student achievement can be enhanced. The purpose of this paper is to demonstrate that while macro-effect sizes such as "whole of school" metrics are useful for…
Descriptors: Foreign Countries, Teacher Effectiveness, Academic Achievement, Data Interpretation
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Martínez Abad, Fernando; Chaparro Caso López, Alicia A. – School Effectiveness and School Improvement, 2017
In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…
Descriptors: Foreign Countries, Data Collection, Statistical Analysis, Evaluation Methods
Rankin, Jenny Grant – Online Submission, 2013
There is extensive research on the benefits of making data-informed decisions, but research also contains evidence many educators incorrectly interpret student data. Meanwhile, the types of detailed labeling on over-the-counter medication have been shown to improve use of non-medication products, as well. However, data systems most educators use…
Descriptors: Data, Decision Making, Accuracy, Statistical Analysis
Thompson, Bruce – 1994
Too few researchers understand what statistical significance testing does and does not do, and consequently their results are misinterpreted. This Digest explains the concept of statistical significance testing and discusses the meaning of probabilities, the concept of statistical significance, arguments against significance testing,…
Descriptors: Data Analysis, Data Interpretation, Decision Making, Effect Size
Council of Ontario Universities, Toronto. Research Div. – 1991
This publication provides macro-indicators and complementary analyses and supporting data for use by policy and decision makers concerned with Ontario universities. These analytical tools are meant to unambiguously measure what is taking place in Canadian postsecondary education, and therefore, assist in focusing on what decisions need to be made.…
Descriptors: Data Interpretation, Decision Making, Educational Planning, Educational Policy
Creighton, Theodore B. – Corwin Press, 2006
Since the first edition of "Schools and Data", the No Child Left Behind Act has swept the country, and data-based decision making is no longer an option for educators. Today's educational climate makes it imperative for all schools to collect data and use statistical analysis to help create clear goals and recognize strategies for…
Descriptors: Federal Legislation, Program Evaluation, Educational Technology, Decision Making