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Paul T. von Hippel – Educational Evaluation and Policy Analysis, 2025
Educational researchers often report effect sizes in standard deviation units (SD), but SD effects are hard to interpret. Effects are easier to interpret in percentile points, but converting SDs to percentile points involves a calculation that is not transparent to educational stakeholders. We show that if the outcome variable is normally…
Descriptors: Effect Size, Computation, Mathematical Concepts, Statistical Distributions
Haoran Li; Chendong Li; Wen Luo; Eunkyeng Baek – Society for Research on Educational Effectiveness, 2025
Background/Context: Single-case experiment designs (SCEDs) are experimental designs in which a small number of cases are repeatedly measured over time, with manipulation of baseline and intervention phases. Because SCEDs often rely on direct behavioral observations, count data are common. To account for both the clustering and the non-normal…
Descriptors: Research Design, Effect Size, Statistical Analysis, Incidence
Lauren K. Schiller; Roberto A. Abreu-Mendoza; Miriam Rosenberg-Lee – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
Decimal numbers are generally assumed to be a straightforward extension of the base-ten system for whole numbers given their shared place value structure. However, in decimal notation, unlike whole numbers, the same magnitude can be expressed in multiple ways (e.g., 0.8, 0.80, 0.800, etc.). Here, we used a number line task with carefully selected…
Descriptors: Arithmetic, Computation, Numbers, Bias
Computational Learning Theory through a New Lens: Scalability, Uncertainty, Practicality, and beyond
Chen Wang – ProQuest LLC, 2024
Computational learning theory studies the design and analysis of learning algorithms, and it is integral to the foundation of machine learning. In the modern era, classical computational learning theory is growingly unable to catch up with new practical demands. In particular, problems arise in the following aspects: i). "scalability":…
Descriptors: Computation, Learning Theories, Algorithms, Artificial Intelligence
Gabriel Felipe Arantes Bertochi; Jeffer Eidi Sasaki – Measurement in Physical Education and Exercise Science, 2025
This study compared the weekly training load (TL) variation across different measures. Fifty-two runners reported their heart rate and distance ran for each training session during four weeks of training. Heart rate measures were used to calculate the weekly TRaining IMPulse (W-TRIMP), whereas the distance ran was used to calculate the weekly…
Descriptors: Physical Education, Physical Activities, Athletics, Athletes
David Voas; Laura Watt – Teaching Statistics: An International Journal for Teachers, 2025
Binary logistic regression is one of the most widely used statistical tools. The method uses odds, log odds, and odds ratios, which are difficult to understand and interpret. Understanding of logistic regression tends to fall down in one of three ways: (1) Many students and researchers come to believe that an odds ratio translates directly into…
Descriptors: Statistics, Statistics Education, Regression (Statistics), Misconceptions
Beyza Aksu Dunya; Stefanie Wind – International Journal of Testing, 2025
We explored the practicality of relatively small item pools in the context of low-stakes Computer-Adaptive Testing (CAT), such as CAT procedures that might be used for quick diagnostic or screening exams. We used a basic CAT algorithm without content balancing and exposure control restrictions to reflect low stakes testing scenarios. We examined…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Achievement
Ari Decter-Frain; Pratik Sachdeva; Loren Collingwood; Hikari Murayama; Juandalyn Burke; Matt Barreto; Scott Henderson; Spencer Wood; Joshua Zingher – Sociological Methods & Research, 2025
We consider the cascading effects of researcher decisions throughout the process of quantifying racially polarized voting (RPV). We contrast three methods of estimating precinct racial composition, Bayesian Improved Surname Geocoding (BISG), fully Bayesian BISG, and Citizen Voting Age Population (CVAP), and two algorithms for performing ecological…
Descriptors: Voting, Computation, Racial Composition, Bayesian Statistics
Sohaib Ahmad; Javid Shabbir – Measurement: Interdisciplinary Research and Perspectives, 2025
This study aims to suggest a generalized class of estimators for population proportion under simple random sampling, which uses auxiliary attributes. The bias and MSEs are considered derived to the first degree approximation. The validity of the suggested and existing estimators is assessed via an empirical investigation. The performance of…
Descriptors: Computation, Sampling, Data Collection, Data Analysis
Leonidas Zotos; Hedderik van Rijn; Malvina Nissim – International Educational Data Mining Society, 2025
In an educational setting, an estimate of the difficulty of Multiple-Choice Questions (MCQs), a commonly used strategy to assess learning progress, constitutes very useful information for both teachers and students. Since human assessment is costly from multiple points of view, automatic approaches to MCQ item difficulty estimation are…
Descriptors: Multiple Choice Tests, Test Items, Difficulty Level, Artificial Intelligence
Huan Liu; Won-Chan Lee – Journal of Educational Measurement, 2025
This study investigates the estimation of classification consistency and accuracy indices for composite summed and theta scores within the SS-MIRT framework, using five popular approaches, including the Lee, Rudner, Guo, Bayesian EAP, and Bayesian MCMC approaches. The procedures are illustrated through analysis of two real datasets and further…
Descriptors: Classification, Reliability, Accuracy, Item Response Theory
Wörner, C. H. – Physics Teacher, 2023
Bounded by the statements of Feynman and Galileo, I describe certain tricks that can be useful for the teaching of physics. In particular, I describe the calculation of the center of mass (centroid) of an arc of circumference and a circular sector. For this purpose, I also use Pappus's theorems. An Appendix is available with Archimedes' method to…
Descriptors: Physics, Computation, Scientific Concepts, Science Instruction
Riley, Richard D.; Ensor, Joie; Hattle, Miriam; Papadimitropoulou, Katerina; Morris, Tim P. – Research Synthesis Methods, 2023
Individual participant data meta-analysis (IPDMA) projects obtain, check, harmonise and synthesise raw data from multiple studies. When undertaking the meta-analysis, researchers must decide between a two-stage or a one-stage approach. In a two-stage approach, the IPD are first analysed separately within each study to obtain aggregate data (e.g.,…
Descriptors: Data Analysis, Meta Analysis, Models, Computation
Hernandez-Gonzalez, Jeronimo; Herrera, Pedro Javier – IEEE Transactions on Learning Technologies, 2023
In peer assessment, students assess a task done by their peers, provide feedback and usually a grade. The extent to which these peer grades can be used to formally grade the task is unclear, with doubts often arising regarding their validity. The instructor could supervise the peer assessments, but would not then benefit from workload reduction,…
Descriptors: Peer Evaluation, Supervision, Models, Computation
Rrita Zejnullahi; Larry V. Hedges – Research Synthesis Methods, 2024
Conventional random-effects models in meta-analysis rely on large sample approximations instead of exact small sample results. While random-effects methods produce efficient estimates and confidence intervals for the summary effect have correct coverage when the number of studies is sufficiently large, we demonstrate that conventional methods…
Descriptors: Robustness (Statistics), Meta Analysis, Sample Size, Computation

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