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Justin Boutilier; Jonas Jonasson; Hannah Li; Erez Yoeli – Society for Research on Educational Effectiveness, 2024
Background: Randomized controlled trials (RCTs), or experiments, are the gold standard for intervention evaluation. However, the main appeal of RCTs--the clean identification of causal effects--can be compromised by interference, when one subject's actions can influence another subject's behavior or outcomes. In this paper, we formalize and study…
Descriptors: Randomized Controlled Trials, Intervention, Mathematical Models, Interference (Learning)
Takashi Kawakami; Akihiko Saeki – Mathematics Education Research Group of Australasia, 2024
This study elaborates on the pivotal roles of mathematical and statistical models in data-driven predictions in an integrated STEM context using the case of Year 4 students: (?) "a descriptive means" to describe the features of trends and variability of data and (?) "an explanatory means" to explain causal relationships behind…
Descriptors: Mathematical Models, Statistical Analysis, Data Use, Prediction
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Yuan Hsiao; Lee Fiorio; Jonathan Wakefield; Emilio Zagheni – Sociological Methods & Research, 2024
Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…
Descriptors: Migration, Migration Patterns, Data Collection, Data Analysis
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Lyrica Lucas; Anum Khushal; Robert Mayes; Brian A. Couch; Joseph Dauer – International Journal of Science Education, 2025
Educational reform priorities such as emphasis on quantitative modelling (QM) have positioned undergraduate biology instructors as designers of QM experiences to engage students in authentic science practices that support the development of data-driven and evidence-based reasoning. Yet, little is known about how biology instructors adapt to the…
Descriptors: Undergraduate Students, College Science, Biology, Classroom Observation Techniques
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Nestler, Steffen – Journal of Educational and Behavioral Statistics, 2018
The social relations model (SRM) is a mathematical model that can be used to analyze interpersonal judgment and behavior data. Typically, the SRM is applied to one (i.e., univariate SRM) or two variables (i.e., bivariate SRM), and parameter estimates are obtained by employing an analysis of variance method. Here, we present an extension of the SRM…
Descriptors: Mathematical Models, Interpersonal Relationship, Maximum Likelihood Statistics, Computation
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McCaffrey, Tony – Journal of Creative Behavior, 2018
A new visual representation for insight problems permits 22 new quantitative measures; which leads to a detailed diagnosis of a person's (or team's) creative weaknesses; which then leads to prescribing targeted, effective counter-techniques for each weakness. Currently, only two measures are consistently used for insight problem solving: the…
Descriptors: Creativity, Problem Solving, Creativity Tests, Teaching Methods
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Battaglia, Onoforio Rosario; Di Paola, Benedetto; Fazio, Claudio – Physical Review Physics Education Research, 2019
A relevant aim of research in education is to find and study the reasoning lines that students deploy when dealing with problematic situations. This can be done through an analysis of the answers students give to a questionnaire. In this paper, we discuss some methodological aspects involved in the quantitative analysis of a questionnaire by means…
Descriptors: Correlation, Coding, Statistical Analysis, Questionnaires
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Petrosino, Anthony J.; Mann, Michele J. – Journal of College Science Teaching, 2018
Although data modeling, the employment of statistical reasoning for the purpose of investigating questions about the world, is central to both mathematics and science, it is rarely emphasized in K-16 instruction. The current work focuses on developing thinking about data modeling with undergraduates in general and preservice teachers in…
Descriptors: Undergraduate Students, Preservice Teachers, Mathematical Models, Data
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Hoogland, Kees; Pepin, Birgit; de Koning, Jaap; Bakker, Arthur; Gravemeijer, Koeno – Research in Mathematics Education, 2018
This article reports on a "post hoc" study using a randomised controlled trial with 31,842 students in the Netherlands and an instrument consisting of 21 paired problems. The trial showed a variability in the differences of students' results in solving contextual mathematical problems with either a descriptive or a depictive…
Descriptors: Word Problems (Mathematics), Mathematics Instruction, Academic Achievement, Foreign Countries
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Gruver, Nate; Malik, Ali; Capoor, Brahm; Piech, Chris; Stevens, Mitchell L.; Paepcke, Andreas – International Educational Data Mining Society, 2019
Understanding large-scale patterns in student course enrollment is a problem of great interest to university administrators and educational researchers. Yet important decisions are often made without a good quantitative framework of the process underlying student choices. We propose a probabilistic approach to modelling course enrollment…
Descriptors: Models, Course Selection (Students), Enrollment, Decision Making
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Rellensmann, Johanna; Schukajlow, Stanislaw; Leopold, Claudia – Educational Studies in Mathematics, 2017
Drawing strategies are widely used as a powerful tool for promoting students' learning and problem solving. In this article, we report the results of an inferential mediation analysis that was applied to investigate the roles that strategic knowledge about drawing and the accuracy of different types of drawings play in mathematical modelling…
Descriptors: Mathematical Models, Freehand Drawing, Mathematics Instruction, Mathematics Achievement
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Lamprianou, Iasonas – Educational and Psychological Measurement, 2018
It is common practice for assessment programs to organize qualifying sessions during which the raters (often known as "markers" or "judges") demonstrate their consistency before operational rating commences. Because of the high-stakes nature of many rating activities, the research community tends to continuously explore new…
Descriptors: Social Networks, Network Analysis, Comparative Analysis, Innovation
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Luo, Yong; Jiao, Hong – Educational and Psychological Measurement, 2018
Stan is a new Bayesian statistical software program that implements the powerful and efficient Hamiltonian Monte Carlo (HMC) algorithm. To date there is not a source that systematically provides Stan code for various item response theory (IRT) models. This article provides Stan code for three representative IRT models, including the…
Descriptors: Bayesian Statistics, Item Response Theory, Probability, Computer Software
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Osler, James Edward, II – Journal of Educational Technology, 2015
This monograph provides an epistemological rational for the Accumulative Manifold Validation Analysis [also referred by the acronym "AMOVA"] statistical methodology designed to test psychometric instruments. This form of inquiry is a form of mathematical optimization in the discipline of linear stochastic modelling. AMOVA is an in-depth…
Descriptors: Statistical Analysis, Test Validity, Test Reliability, Inquiry
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Çiftçi, Serife Koza; Danisman, Sahin; Yalçin, Mikail; Tosuntas, Sule Betül; Ay, Yusuf; Sölpük, Nihan; Karadag, Engin – Educational Sciences: Theory and Practice, 2016
This study aims to create a map for the scientific publications in the field of educational sciences and teacher education in Turkey. A bibliometric analysis was carried out with 7681 articles published in 32 different peer reviewed journals between 2005 and 2014. The findings show that one third of all articles were published in core journals…
Descriptors: Teacher Education, Foreign Countries, Bibliometrics, Scientific Research
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