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Direct linkSun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Grantee Submission, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Journal of Educational Measurement, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Mitchell-Williams, Missy T.; Skipper, Antonius D.; Alexander, Marvin C.; Wilks, Scott E. – Research on Social Work Practice, 2017
Purpose: Following up an "Research on Social Work Practice" article published a decade ago, this study aimed to examine reference error rates among five, widely circulated social work journals. Methods: A stratified random sample of references was selected from the year 2013 (N = 500, 100/journal). Each was verified against the original…
Descriptors: Accuracy, Social Work, Followup Studies, Error Patterns
Aydogdu, Bülent – Asia-Pacific Forum on Science Learning and Teaching, 2015
The aim of this study is to examine preservice science teachers' skills of formulating hypotheses and identifying variables. The research has a phenomenological research design. The data was gathered qualitatively. In this study, preservice science teachers were first given two scenarios (Scenario-1 & Scenario-2) containing two different…
Descriptors: Preservice Teachers, Science Teachers, Science Process Skills, Hypothesis Testing
Williams, Joseph J.; Griffiths, Thomas L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2013
Errors in detecting randomness are often explained in terms of biases and misconceptions. We propose and provide evidence for an account that characterizes the contribution of the inherent statistical difficulty of the task. Our account is based on a Bayesian statistical analysis, focusing on the fact that a random process is a special case of…
Descriptors: Experimental Psychology, Bias, Misconceptions, Statistical Analysis
Ottmar, Erin; Landy, David – Journal of the Learning Sciences, 2017
Learning algebra is difficult for many students in part because of an emphasis on the memorization of abstract rules. Algebraic reasoners across expertise levels often rely on perceptual-motor strategies to make these rules meaningful and memorable. However, in many cases, rules are provided as patterns to be memorized verbally, with little overt…
Descriptors: Mathematics Instruction, Algebra, Outcomes of Education, Learning Processes
