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Enakshi Saha – ProQuest LLC, 2021
We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…
Descriptors: Bayesian Statistics, Probability, Nonparametric Statistics, Data Analysis
Stoevenbelt, Andrea H.; Wicherts, Jelte M.; Flore, Paulette C.; Phillips, Lorraine A. T.; Pietschnig, Jakob; Verschuere, Bruno; Voracek, Martin; Schwabe, Inga – Educational and Psychological Measurement, 2023
When cognitive and educational tests are administered under time limits, tests may become speeded and this may affect the reliability and validity of the resulting test scores. Prior research has shown that time limits may create or enlarge gender gaps in cognitive and academic testing. On average, women complete fewer items than men when a test…
Descriptors: Timed Tests, Gender Differences, Item Response Theory, Correlation
Vasil, Jared; Moore, Charlotte; Tomasello, Michael – First Language, 2023
Shared intentionality theory posits that at age 3, children expand their conception of plural agency to include 3- or more-person groups. We sought to determine whether this conceptual shift is detectable in children's pronoun use. We report the results of a series of Bayesian hierarchical generative models fitted to 479 English-speaking…
Descriptors: Form Classes (Languages), Preschool Children, Language Acquisition, Language Usage
Ritter, Frauke; Standl, Bernhard – Informatics in Education, 2023
We live in a digital age, not least accelerated by the COVID-19 pandemic. It is all the more important in our society that students learn and master the key competence of algorithmic thinking to understand the informatics concepts behind every digital phenomena and thus is able to actively shape the future. For this to be successful, concepts must…
Descriptors: Algorithms, Information Science Education, Computer Science Education, COVID-19
Wagner, Richard K.; Moxley, Jerad; Schatschneider, Chris; Zirps, Fotena A. – Scientific Studies of Reading, 2023
Purpose: Bayesian-based models for diagnosis are common in medicine but have not been incorporated into identification models for dyslexia. The purpose of the present study was to evaluate Bayesian identification models that included a broader set of predictors and that capitalized on recent developments in modeling the prevalence of dyslexia.…
Descriptors: Bayesian Statistics, Identification, Dyslexia, Models
Zwick, Rebecca; Ye, Lei; Isham, Steven – Journal of Educational Measurement, 2018
In typical differential item functioning (DIF) assessments, an item's DIF status is not influenced by its status in previous test administrations. An item that has shown DIF at multiple administrations may be treated the same way as an item that has shown DIF in only the most recent administration. Therefore, much useful information about the…
Descriptors: Test Bias, Testing, Test Items, Bayesian Statistics
Dynamic Bayesian Networks in Educational Measurement: Reviewing and Advancing the State of the Field
Reichenberg, Ray – Applied Measurement in Education, 2018
As the popularity of rich assessment scenarios increases so must the availability of psychometric models capable of handling the resulting data. Dynamic Bayesian networks (DBNs) offer a fast, flexible option for characterizing student ability across time under psychometrically complex conditions. In this article, a brief introduction to DBNs is…
Descriptors: Bayesian Statistics, Measurement, Student Evaluation, Psychometrics
Lorah, Julie Ann – AERA Online Paper Repository, 2018
The Bayesian information criterion (BIC) can be useful for model selection within multilevel modeling studies. However, the formula for BIC requires a value for N, which is unclear in multilevel models, since N is observed in at least two levels. The present study uses simulated data to evaluate the rate of false positives and power when using a…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, Computation, Statistical Analysis
Ozdemir, Burhanettin; Gelbal, Selahattin – Education and Information Technologies, 2022
The computerized adaptive tests (CAT) apply an adaptive process in which the items are tailored to individuals' ability scores. The multidimensional CAT (MCAT) designs differ in terms of different item selection, ability estimation, and termination methods being used. This study aims at investigating the performance of the MCAT designs used to…
Descriptors: Scores, Computer Assisted Testing, Test Items, Language Proficiency
Christian Michael Smith; Noah Hirschl – Grantee Submission, 2022
In 2015, Wisconsin began mandating the ACT college entrance exam and the WorkKeys career readiness assessment. With population-level data and several quasi-experimental designs, we assess how this policy affected college attendance. We estimate a positive policy effect for middle/high-income students, no effect for low-income students, and greater…
Descriptors: Disadvantaged Youth, Low Income Students, College Attendance, College Readiness
Verhavert, San; Bouwer, Renske; Donche, Vincent; De Maeyer, Sven – Assessment in Education: Principles, Policy & Practice, 2019
Comparative Judgement (CJ) aims to improve the quality of performance-based assessments by letting multiple assessors judge pairs of performances. CJ is generally associated with high levels of reliability, but there is also a large variation in reliability between assessments. This study investigates which assessment characteristics influence the…
Descriptors: Meta Analysis, Reliability, Comparative Analysis, Value Judgment
CadwalladerOlsker, Todd – Mathematics Teacher, 2019
Students studying statistics often misunderstand what statistics represent. Some of the most well-known misunderstandings of statistics revolve around null hypothesis significance testing. One pervasive misunderstanding is that the calculated p-value represents the probability that the null hypothesis is true, and that if p < 0.05, there is…
Descriptors: Statistics, Mathematics Education, Misconceptions, Hypothesis Testing
Merkle, E. C.; Furr, D.; Rabe-Hesketh, S. – Grantee Submission, 2019
Typical Bayesian methods for models with latent variables (or random effects) involve directly sampling the latent variables along with the model parameters. In high-level software code for model definitions (using, e.g., BUGS, JAGS, Stan), the likelihood is therefore specified as conditional on the latent variables. This can lead researchers to…
Descriptors: Bayesian Statistics, Comparative Analysis, Computer Software, Models
Orona, Gabe A. – Arts and Humanities in Higher Education: An International Journal of Theory, Research and Practice, 2021
In recent decades, philosophy has been identified as a general approach to enhance the maturity of higher education as a field of study by enriching theory and method. In this article, I offer a new set of philosophical recommendations to spur the disciplinary development of higher education, departing from previous work in several meaningful…
Descriptors: Higher Education, Educational Philosophy, Educational Theories, Student Centered Curriculum
De Bondt, Niki; De Maeyer, Sven; Donche, Vincent; Van Petegem, Peter – High Ability Studies, 2021
The aim of this study is to provide -- first theoretically and, subsequently, through an empirical analysis -- a rationale for including the concept of overexcitability in talent research, beyond the five-factor model personality traits. Moreover, the empirical part of this study makes use of an innovative statistical method to address the problem…
Descriptors: Personality Traits, Talent, Research, Gifted