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Gyamfi, Abraham; Acquaye, Rosemary – Acta Educationis Generalis, 2023
Introduction: Item response theory (IRT) has received much attention in validation of assessment instrument because it allows the estimation of students' ability from any set of the items. Item response theory allows the difficulty and discrimination levels of each item on the test to be estimated. In the framework of IRT, item characteristics are…
Descriptors: Item Response Theory, Models, Test Items, Difficulty Level
Sweeney, Sandra M.; Sinharay, Sandip; Johnson, Matthew S.; Steinhauer, Eric W. – Educational Measurement: Issues and Practice, 2022
The focus of this paper is on the empirical relationship between item difficulty and item discrimination. Two studies--an empirical investigation and a simulation study--were conducted to examine the association between item difficulty and item discrimination under classical test theory and item response theory (IRT), and the effects of the…
Descriptors: Correlation, Item Response Theory, Item Analysis, Difficulty Level
Thompson, Kathryn N. – ProQuest LLC, 2023
It is imperative to collect validity evidence prior to interpreting and using test scores. During the process of collecting validity evidence, test developers should consider whether test scores are contaminated by sources of extraneous information. This is referred to as construct irrelevant variance, or the "degree to which test scores are…
Descriptors: Test Wiseness, Test Items, Item Response Theory, Scores
Camenares, Devin – International Journal for the Scholarship of Teaching and Learning, 2022
Balancing assessment of learning outcomes with the expectations of students is a perennial challenge in education. Difficult exams, in which many students perform poorly, exacerbate this problem and can inspire a wide variety of interventions, such as a grading curve. However, addressing poor performance can sometimes distort or inflate grades and…
Descriptors: College Students, Student Evaluation, Tests, Test Items
Roger Young; Emily Courtney; Alexander Kah; Mariah Wilkerson; Yi-Hsin Chen – Teaching of Psychology, 2025
Background: Multiple-choice item (MCI) assessments are burdensome for instructors to develop. Artificial intelligence (AI, e.g., ChatGPT) can streamline the process without sacrificing quality. The quality of AI-generated MCIs and human experts is comparable. However, whether the quality of AI-generated MCIs is equally good across various domain-…
Descriptors: Item Response Theory, Multiple Choice Tests, Psychology, Textbooks
Tsutsumi, Emiko; Kinoshita, Ryo; Ueno, Maomi – International Educational Data Mining Society, 2021
Knowledge tracing (KT), the task of tracking the knowledge state of each student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines Item Response Theory (IRT) with a deep learning model, provides superior performance. It can express the abilities of each student…
Descriptors: Item Response Theory, Prediction, Accuracy, Artificial Intelligence
Mimi Ismail; Ahmed Al - Badri; Said Al - Senaidi – Journal of Education and e-Learning Research, 2025
This study aimed to reveal the differences in individuals' abilities, their standard errors, and the psychometric properties of the test according to the two methods of applying the test (electronic and paper). The descriptive approach was used to achieve the study's objectives. The study sample consisted of 74 male and female students at the…
Descriptors: Achievement Tests, Computer Assisted Testing, Psychometrics, Item Response Theory
Alicia A. Stoltenberg – ProQuest LLC, 2024
Multiple-select multiple-choice items, or multiple-choice items with more than one correct answer, are used to quickly assess content on standardized assessments. Because there are multiple keys to these item types, there are also multiple ways to score student responses to these items. The purpose of this study was to investigate how changing the…
Descriptors: Scoring, Evaluation Methods, Multiple Choice Tests, Standardized Tests
Yoo Jeong Jang – ProQuest LLC, 2022
Despite the increasing demand for diagnostic information, observed subscores have been often reported to lack adequate psychometric qualities such as reliability, distinctiveness, and validity. Therefore, several statistical techniques based on CTT and IRT frameworks have been proposed to improve the quality of subscores. More recently, DCM has…
Descriptors: Classification, Accuracy, Item Response Theory, Correlation
Moritz Waitzmann; Ruediger Scholz; Susanne Wessnigk – Physical Review Physics Education Research, 2024
Clear and rigorous quantum reasoning is needed to explain quantum physical phenomena. As pillars of true quantum physical explanations, we suggest specific quantum reasoning derived from quantum physical key ideas. An experiment is suggested to support such a quantum reasoning, in which a quantized radiation field interacts with an optical beam…
Descriptors: Physics, Science Instruction, Teaching Methods, Quantum Mechanics
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
Musa Adekunle Ayanwale; Jamiu Oluwadamilare Amusa; Adekunle Ibrahim Oladejo; Funmilayo Ayedun – Interchange: A Quarterly Review of Education, 2024
The study focuses on assessing the proficiency levels of higher education students, specifically the physics achievement test (PHY 101) at the National Open University of Nigeria (NOUN). This test, like others, evaluates various aspects of knowledge and skills simultaneously. However, relying on traditional models for such tests can result in…
Descriptors: Item Response Theory, Difficulty Level, Item Analysis, Test Items
Musa Adekunle Ayanwale – Discover Education, 2023
Examination scores obtained by students from the West African Examinations Council (WAEC), and National Business and Technical Examinations Board (NABTEB) may not be directly comparable due to differences in examination administration, item characteristics of the subject in question, and student abilities. For more accurate comparisons, scores…
Descriptors: Equated Scores, Mathematics Tests, Test Items, Test Format
Saatcioglu, Fatima Munevver; Atar, Hakan Yavuz – International Journal of Assessment Tools in Education, 2022
This study aims to examine the effects of mixture item response theory (IRT) models on item parameter estimation and classification accuracy under different conditions. The manipulated variables of the simulation study are set as mixture IRT models (Rasch, 2PL, 3PL); sample size (600, 1000); the number of items (10, 30); the number of latent…
Descriptors: Accuracy, Classification, Item Response Theory, Programming Languages
Ferrara, Steve; Steedle, Jeffrey T.; Frantz, Roger S. – Applied Measurement in Education, 2022
Item difficulty modeling studies involve (a) hypothesizing item features, or item response demands, that are likely to predict item difficulty with some degree of accuracy; and (b) entering the features as independent variables into a regression equation or other statistical model to predict difficulty. In this review, we report findings from 13…
Descriptors: Reading Comprehension, Reading Tests, Test Items, Item Response Theory