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Joshua B. Gilbert – Annenberg Institute for School Reform at Brown University, 2024
When analyzing treatment effects on test scores, researchers face many choices and competing guidance for scoring tests and modeling results. This study examines the impact of scoring choices through simulation and an empirical application. Results show that estimates from multiple methods applied to the same data will vary because two-step models…
Descriptors: Scores, Statistical Bias, Statistical Inference, Scoring
The Use of Theory of Linear Mixed-Effects Models to Detect Fraudulent Erasures at an Aggregate Level
Peng, Luyao; Sinharay, Sandip – Educational and Psychological Measurement, 2022
Wollack et al. (2015) suggested the erasure detection index (EDI) for detecting fraudulent erasures for individual examinees. Wollack and Eckerly (2017) and Sinharay (2018) extended the index of Wollack et al. (2015) to suggest three EDIs for detecting fraudulent erasures at the aggregate or group level. This article follows up on the research of…
Descriptors: Cheating, Identification, Statistical Analysis, Testing
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
Onur Demirkaya; Sharon Frey; Sid Sharairi; JongPil Kim – International Electronic Journal of Elementary Education, 2025
This study compares latent profiles derived from student subgroups of varying levels of mathematical skills defined by achievement and ability assessment scores. Achievement and ability cut scores for identifying students at both ends of the mathematics spectrum were applied and the resulting latent profiles within each condition were compared.…
Descriptors: Profiles, Statistical Analysis, Academic Achievement, Mathematics Achievement
Wolfgang Weidermann; Keith C. Herman; Wendy Reinke; Alexander von Eye – Grantee Submission, 2022
Although variable-oriented analyses are dominant in developmental psychopathology, researchers have championed a person-oriented approach that focuses on the individual as a totality. This view has methodological implications and various person-oriented methods have been developed to test person-oriented hypotheses. Configural frequency analysis…
Descriptors: Student Behavior, Behavior Patterns, Monte Carlo Methods, Statistical Analysis
John Jerrim; Alex Jones – School Effectiveness and School Improvement, 2024
School inspections are a common feature of many education systems. These may be informed by quantitative background data about schools. It is recognised that there are pros and cons of using such quantitative information as part of the inspection process, though these have rarely been succinctly set out. This paper seeks to fill this gap by…
Descriptors: Inspection, Foreign Countries, Statistical Analysis, Educational Quality
Mazrekaj, Deni; Witte, Kristof De; Triebs, Thomas P. – Exceptional Children, 2022
We propose using Stochastic Frontier Analysis to estimate pupils' academic underachievement. We model underachievement as the gap between expected achievement and actual achievement, not due to a learning disability. Our data are a panel for 2,228 Belgian pupils observed over 6 years of primary education. We found that the average underachievement…
Descriptors: Academic Achievement, Underachievement, Academically Gifted, Class Size
Dvir, Michal; Ben-Zvi, Dani – Instructional Science: An International Journal of the Learning Sciences, 2023
Estimating and accounting for statistical uncertainty have become essential in today's information age, and crucial for cultivating a sound decision making citizenry. Engaging with statistical uncertainty early on can support the gradual development of uncertainty-related considerations that are often challenging to foster at any age. Statistical…
Descriptors: Learning Processes, Computation, Numeracy, Attitudes
Billion, Lara Kristina – EURASIA Journal of Mathematics, Science and Technology Education, 2022
This paper focuses on the actions of learners on digital and analogue materials while dealing with a statistical problem. To investigate the learners' actions, a semiotic perspective of mathematical learning according to C. S. Peirce is used, since in this perspective learning mathematics is described as visible activities on diagrams. Through a…
Descriptors: Semiotics, Mathematics Instruction, Grade 3, Elementary School Students
Joshua B. Gilbert – Annenberg Institute for School Reform at Brown University, 2022
This simulation study examines the characteristics of the Explanatory Item Response Model (EIRM) when estimating treatment effects when compared to classical test theory (CTT) sum and mean scores and item response theory (IRT)-based theta scores. Results show that the EIRM and IRT theta scores provide generally equivalent bias and false positive…
Descriptors: Item Response Theory, Models, Test Theory, Computation
Chen, Lujie Karen; Ramsey, Joseph; Dubrawski, Artur – Journal of Educational Data Mining, 2021
Human one-on-one coaching involves complex multimodal interactions. Successful coaching requires teachers to closely monitor students' cognitive-affective states and provide support of optimal type, timing, and amount. However, most of the existing human tutoring studies focus primarily on verbal interactions and have yet to incorporate the rich…
Descriptors: Causal Models, Coaching (Performance), Statistical Analysis, Correlation
Nazari, Sanaz; Leite, Walter L.; Huggins-Manley, A. Corinne – Journal of Experimental Education, 2023
The piecewise latent growth models (PWLGMs) can be used to study changes in the growth trajectory of an outcome due to an event or condition, such as exposure to an intervention. When there are multiple outcomes of interest, a researcher may choose to fit a series of PWLGMs or a single parallel-process PWLGM. A comparison of these models is…
Descriptors: Growth Models, Statistical Analysis, Intervention, Comparative Analysis
Watson, Jane; Fitzallen, Noleine; English, Lyn; Wright, Suzie – International Journal of Mathematical Education in Science and Technology, 2020
As STEM education becomes more prominent at the school level, many possibilities could be suggested for beginning experiences to create a foundation for young students as they begin their journeys with respect to STEM learning. The research reported here is based on the premise that building statistical understanding will enhance young students'…
Descriptors: STEM Education, Statistics, Grade 3, Science Activities
Timothy Lycurgus; Ben B. Hansen; Mark White – Grantee Submission, 2022
We present an aggregation scheme that increases power in randomized controlled trials and quasi-experiments when the intervention possesses a robust and well-articulated theory of change. Intervention studies using longitudinal data often include multiple observations on individuals, some of which may be more likely to manifest a treatment effect…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Quasiexperimental Design, Intervention
Estrella, Soledad; Vergara, Andrea; Gonzalez, Orlando – Statistics Education Research Journal, 2021
In order to study the manifestation of data sense and identify ways of thinking about variability in authentically realistic problems in a group of Chilean fifth-grade students, a lesson plan was designed and implemented, within the framework of statistical literacy and using the "lesson study" modality, in which students were urged to…
Descriptors: Foreign Countries, Grade 5, Statistical Analysis, Elementary School Students