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Yannick Rothacher; Carolin Strobl – Journal of Educational and Behavioral Statistics, 2024
Random forests are a nonparametric machine learning method, which is currently gaining popularity in the behavioral sciences. Despite random forests' potential advantages over more conventional statistical methods, a remaining question is how reliably informative predictor variables can be identified by means of random forests. The present study…
Descriptors: Predictor Variables, Selection Criteria, Behavioral Sciences, Reliability
Richard Churches; Kate Wastie; Max Jones; Nina Dhillon – Education Development Trust, 2024
This report provides advice to policymakers and school leaders on the use of assessment centres as part of a teacher selection approach. It discusses the relationship between assessment centre scores prior to joining teaching, and teacher effectiveness over a six-year period. It draws from various stages of a wider research project, the overall…
Descriptors: Beginning Teachers, Classroom Techniques, Prediction, Teacher Selection
Zhenqiu Lu; Zhiyong Zhang – Grantee Submission, 2022
Bayesian approach is becoming increasingly important as it provides many advantages in dealing with complex data. However, there is no well-defined model selection criterion or index in a Bayesian context. To address the challenges, new indices are needed. The goal of this study is to propose new model selection indices and to investigate their…
Descriptors: Models, Goodness of Fit, Bayesian Statistics, Simulation
Chen, Chia-Wen; Wang, Wen-Chung; Chiu, Ming Ming; Ro, Sage – Journal of Educational Measurement, 2020
The use of computerized adaptive testing algorithms for ranking items (e.g., college preferences, career choices) involves two major challenges: unacceptably high computation times (selecting from a large item pool with many dimensions) and biased results (enhanced preferences or intensified examinee responses because of repeated statements across…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
Dan Goldhaber; Matt Kasman; Vanessa Quince; Roddy Theobald; Malcolm Wolff – National Center for Analysis of Longitudinal Data in Education Research (CALDER), 2023
We use publicly available, longitudinal data from Washington state to study the extent to which three interrelated processes--teacher attrition from the state teaching workforce, teacher mobility between teaching positions, and teacher hiring for open positions--contribute to "teacher quality gaps" (TQGs) between students of color and…
Descriptors: Labor Turnover, Teacher Persistence, Teacher Selection, Teacher Competencies
Zureck, Alexander – Problems of Education in the 21st Century, 2021
The range of study programs in finance and the ways how to study due to place, time, and focus has increased in recent years. Students can choose what and how they want to learn. If someone finds an appropriate program he must decide to study face-to-face, online, or in a hybrid format. Finance is often a duty in business administration or related…
Descriptors: Foreign Countries, Active Learning, Media Selection, Reading Material Selection
Gómez Galindo, Alma Adrianna; González Galli, Leonardo; García Franco, Alejandra – Journal of Biological Education, 2021
In this paper, we present a simulation of artificial selection of maize that can be used as a bridging case for the subsequent introduction of natural selection in school. The proposed simulation takes up essential biological elements but also has a cultural meaning for the inhabitants of some regions of Latin America. After implementing a test of…
Descriptors: Science Instruction, Biology, Evolution, Simulation
Craig, Brandon – ProQuest LLC, 2017
The purpose of this study was to determine if using a multistage approach for the empirical selection of anchor items would lead to more accurate DIF detection rates than the anchor selection methods proposed by Kopf, Zeileis, & Strobl (2015b). A simulation study was conducted in which the sample size, percentage of DIF, and balance of DIF…
Descriptors: Simulation, Sample Size, Item Response Theory, Item Analysis
Keller, Bryan; Chen, Jianshen – Society for Research on Educational Effectiveness, 2016
Observational studies are common in educational research, where subjects self-select or are otherwise non-randomly assigned to different interventions (e.g., educational programs, grade retention, special education). Unbiased estimation of a causal effect with observational data depends crucially on the assumption of ignorability, which specifies…
Descriptors: Computation, Influences, Observation, Data
Carroll, Ian A. – ProQuest LLC, 2017
Item exposure control is, relative to adaptive testing, a nascent concept that has emerged only in the last two to three decades on an academic basis as a practical issue in high-stakes computerized adaptive tests. This study aims to implement a new strategy in item exposure control by incorporating the standard error of the ability estimate into…
Descriptors: Test Items, Computer Assisted Testing, Selection, Adaptive Testing
Steiner, Peter M.; Kim, Jee-Seon – Society for Research on Educational Effectiveness, 2015
Despite the popularity of propensity score (PS) techniques they are not yet well studied for matching multilevel data where selection into treatment takes place among level-one units within clusters. This paper suggests a PS matching strategy that tries to avoid the disadvantages of within- and across-cluster matching. The idea is to first…
Descriptors: Computation, Outcomes of Treatment, Multivariate Analysis, Probability
Mosier, Brian; Heidorn, Brent; Johnson, Christie – Strategies: A Journal for Physical and Sport Educators, 2015
The purpose of this article is to provide a basic review of a hiring simulation fair, and to describe strategies for successfully implementing a similar organized event in a college/university teacher education program in order to better prepare students for the interview process.
Descriptors: Simulation, Personnel Selection, Teacher Education Programs, Higher Education
Bar-Hillel, Maya; Peer, Eyal; Acquisti, Alessandro – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2014
When asked to mentally simulate coin tosses, people generate sequences that differ systematically from those generated by fair coins. It has been rarely noted that this divergence is apparent already in the very 1st mental toss. Analysis of several existing data sets reveals that about 80% of respondents start their sequence with Heads. We…
Descriptors: Bias, Selection, Cognitive Processes, Simulation
Kopf, Julia; Zeileis, Achim; Strobl, Carolin – Educational and Psychological Measurement, 2015
Differential item functioning (DIF) indicates the violation of the invariance assumption, for instance, in models based on item response theory (IRT). For item-wise DIF analysis using IRT, a common metric for the item parameters of the groups that are to be compared (e.g., for the reference and the focal group) is necessary. In the Rasch model,…
Descriptors: Test Items, Equated Scores, Test Bias, Item Response Theory
Mustafa, Hassan M. H.; Tourkia, Fadhel Ben; Ramadan, Ramadan Mohamed – Journal of Education and e-Learning Research, 2017
The objective of this piece of research is to interpret and investigate systematically an observed brain functional phenomenon which is associated with proceeding of e-learning processes. More specifically, this work addresses an interesting and challenging educational issue concerned with dynamical evaluation of elearning performance considering…
Descriptors: Electronic Learning, Reaction Time, Brain Hemisphere Functions, Learning Processes

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