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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
Wind, Stefanie A.; Ge, Yuan – Measurement: Interdisciplinary Research and Perspectives, 2023
In selected-response assessments such as attitude surveys with Likert-type rating scales, examinees often select from rating scale categories to reflect their locations on a construct. Researchers have observed that some examinees exhibit "response styles," which are systematic patterns of responses in which examinees are more likely to…
Descriptors: Goodness of Fit, Responses, Likert Scales, Models
DeCarlo, Lawrence T. – Journal of Educational Measurement, 2023
A conceptualization of multiple-choice exams in terms of signal detection theory (SDT) leads to simple measures of item difficulty and item discrimination that are closely related to, but also distinct from, those used in classical item analysis (CIA). The theory defines a "true split," depending on whether or not examinees know an item,…
Descriptors: Multiple Choice Tests, Test Items, Item Analysis, Test Wiseness
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
Berger, Stéphanie; Verschoor, Angela J.; Eggen, Theo J. H. M.; Moser, Urs – Journal of Educational Measurement, 2019
Calibration of an item bank for computer adaptive testing requires substantial resources. In this study, we investigated whether the efficiency of calibration under the Rasch model could be enhanced by improving the match between item difficulty and student ability. We introduced targeted multistage calibration designs, a design type that…
Descriptors: Simulation, Computer Assisted Testing, Test Items, Difficulty Level
Susanti, Yuni; Tokunaga, Takenobu; Nishikawa, Hitoshi – Research and Practice in Technology Enhanced Learning, 2020
The present study focuses on the integration of an automatic question generation (AQG) system and a computerised adaptive test (CAT). We conducted two experiments. In the first experiment, we administered sets of questions to English learners to gather their responses. We further used their responses in the second experiment, which is a…
Descriptors: Computer Assisted Testing, Test Items, Simulation, English Language Learners
Lu, Ru; Guo, Hongwen; Dorans, Neil J. – ETS Research Report Series, 2021
Two families of analysis methods can be used for differential item functioning (DIF) analysis. One family is DIF analysis based on observed scores, such as the Mantel-Haenszel (MH) and the standardized proportion-correct metric for DIF procedures; the other is analysis based on latent ability, in which the statistic is a measure of departure from…
Descriptors: Robustness (Statistics), Weighted Scores, Test Items, Item Analysis
Abulela, Mohammed A. A.; Rios, Joseph A. – Applied Measurement in Education, 2022
When there are no personal consequences associated with test performance for examinees, rapid guessing (RG) is a concern and can differ between subgroups. To date, the impact of differential RG on item-level measurement invariance has received minimal attention. To that end, a simulation study was conducted to examine the robustness of the…
Descriptors: Comparative Analysis, Robustness (Statistics), Nonparametric Statistics, Item Analysis
Albano, Anthony D.; Cai, Liuhan; Lease, Erin M.; McConnell, Scott R. – Journal of Educational Measurement, 2019
Studies have shown that item difficulty can vary significantly based on the context of an item within a test form. In particular, item position may be associated with practice and fatigue effects that influence item parameter estimation. The purpose of this research was to examine the relevance of item position specifically for assessments used in…
Descriptors: Test Items, Computer Assisted Testing, Item Analysis, Difficulty Level
Pelánek, Radek; Effenberger, Tomáš; Kukucka, Adam – Journal of Educational Data Mining, 2022
We study the automatic identification of educational items worthy of content authors' attention. Based on the results of such analysis, content authors can revise and improve the content of learning environments. We provide an overview of item properties relevant to this task, including difficulty and complexity measures, item discrimination, and…
Descriptors: Item Analysis, Identification, Difficulty Level, Case Studies
Ozturk, Nagihan Boztunc; Dogan, Nuri – Educational Sciences: Theory and Practice, 2015
This study aims to investigate the effects of item exposure control methods on measurement precision and on test security under various item selection methods and item pool characteristics. In this study, the Randomesque (with item group sizes of 5 and 10), Sympson-Hetter, and Fade-Away methods were used as item exposure control methods. Moreover,…
Descriptors: Computer Assisted Testing, Item Analysis, Statistical Analysis, Comparative Analysis
Zhang, Jinming; Li, Jie – Journal of Educational Measurement, 2016
An IRT-based sequential procedure is developed to monitor items for enhancing test security. The procedure uses a series of statistical hypothesis tests to examine whether the statistical characteristics of each item under inspection have changed significantly during CAT administration. This procedure is compared with a previously developed…
Descriptors: Computer Assisted Testing, Test Items, Difficulty Level, Item Response Theory
Yip, Chi Kwong; Man, David W. K. – International Journal of Rehabilitation Research, 2009
This study investigates the validity of a newly developed computerized cognitive assessment system (CCAS) that is equipped with rich multimedia to generate simulated testing situations and considers both test item difficulty and the test taker's ability. It is also hypothesized that better predictive validity of the CCAS in self-care of persons…
Descriptors: Test Items, Content Validity, Predictive Validity, Patients
Peer reviewedMazor, Kathleen M.; And Others – Educational and Psychological Measurement, 1994
A variation of the Mantel Haenszel procedure is proposed that improves detection rates of nonuniform differential item functioning (DIF) without increasing the Type I error rate. The procedure, which is illustrated with simulated examinee responses, involves splitting the sample into low- and high-performing groups. (SLD)
Descriptors: Difficulty Level, Identification, Item Analysis, Item Bias
Groome, Mary Lynn; Groome, William R. – 1979
Angoff's method for identifying possible biased test items was applied to four computer-generated hypothetical tests, two of which contained no biased items and two of which contained a few biased items. The tests were generated to match specifications of a latent trait model. Angoff's method compared item difficulty estimates for two different…
Descriptors: Difficulty Level, Identification, Item Analysis, Mathematical Models
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