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Lang, Joseph B. – Journal of Educational and Behavioral Statistics, 2023
This article is concerned with the statistical detection of copying on multiple-choice exams. As an alternative to existing permutation- and model-based copy-detection approaches, a simple randomization p-value (RP) test is proposed. The RP test, which is based on an intuitive match-score statistic, makes no assumptions about the distribution of…
Descriptors: Identification, Cheating, Multiple Choice Tests, Item Response Theory
Ross, Linette P. – ProQuest LLC, 2022
One of the most serious forms of cheating occurs when examinees have item preknowledge and prior access to secure test material before taking an exam for the purpose of obtaining an inflated test score. Examinees that cheat and have prior knowledge of test content before testing may have an unfair advantage over examinees that do not cheat. Item…
Descriptors: Testing, Deception, Cheating, Identification
Kula, Fulya; Koçer, Rüya Gökhan – Teaching Mathematics and Its Applications, 2020
Difficulties in learning (and thus teaching) statistical inference are well reported in the literature. We argue the problem emanates not only from the way in which statistical inference is taught but also from what exactly is taught as statistical inference. What makes statistical inference difficult to understand is that it contains two logics…
Descriptors: Statistical Inference, Teaching Methods, Difficulty Level, Comprehension
Joshua B. Gilbert; Luke W. Miratrix; Mridul Joshi; Benjamin W. Domingue – Journal of Educational and Behavioral Statistics, 2025
Analyzing heterogeneous treatment effects (HTEs) plays a crucial role in understanding the impacts of educational interventions. A standard practice for HTE analysis is to examine interactions between treatment status and preintervention participant characteristics, such as pretest scores, to identify how different groups respond to treatment.…
Descriptors: Causal Models, Item Response Theory, Statistical Inference, Psychometrics
Joshua B. Gilbert; Luke W. Miratrix; Mridul Joshi; Benjamin W. Domingue – Annenberg Institute for School Reform at Brown University, 2024
Analyzing heterogeneous treatment effects (HTE) plays a crucial role in understanding the impacts of educational interventions. A standard practice for HTE analysis is to examine interactions between treatment status and pre-intervention participant characteristics, such as pretest scores, to identify how different groups respond to treatment.…
Descriptors: Causal Models, Item Response Theory, Statistical Inference, Psychometrics
Reaburn, Robyn – Mathematics Education Research Group of Australasia, 2019
Random sampling and random allocation are essential processes in the practice of inferential statistics. These processes ensure that all members of a population are equally likely to be selected, and that all possible allocations in an experiment are equally likely. It is these characteristics that allow the validity of the subsequent calculations…
Descriptors: Statistics, Comprehension, Introductory Courses, College Students
Sullivan, Patrick – Mathematics Teacher: Learning and Teaching PK-12, 2022
Probabilistic reasoning underpins much of middle school students' future work in data analysis and inferential statistics. Unfortunately for many middle school students, probabilistic reasoning is not intuitive. One specific area in which students seem to struggle is determining the probability of compound events (Moritz and Watson 2000). Research…
Descriptors: Mathematics Instruction, Thinking Skills, Middle School Students, Data Analysis
Lodge, Jason M.; Alhadad, Sakinah S. J.; Lewis, Melinda J.; Gaševic, Dragan – Technology, Knowledge and Learning, 2017
The use of big data in higher education has evolved rapidly with a focus on the practical application of new tools and methods for supporting learning. In this paper, we depart from the core emphasis on application and delve into a mostly neglected aspect of the big data conversation in higher education. Drawing on developments in cognate…
Descriptors: Statistical Inference, Data Interpretation, Interdisciplinary Approach, Higher Education
Hofman, Abe D.; Brinkhuis, Matthieu J. S.; Bolsinova, Maria; Klaiber, Jonathan; Maris, Gunter; van der Maas, Han L. J. – Journal of Intelligence, 2020
One of the highest ambitions in educational technology is the move towards personalized learning. To this end, computerized adaptive learning (CAL) systems are developed. A popular method to track the development of student ability and item difficulty, in CAL systems, is the Elo Rating System (ERS). The ERS allows for dynamic model parameters by…
Descriptors: Teaching Methods, Computer Assisted Instruction, Difficulty Level, Individualized Instruction
Levy, Roy – Educational Psychologist, 2016
In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…
Descriptors: Bayesian Statistics, Models, Educational Research, Innovation