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Kristen L. Murphy; David G. Schreurs; Melonie A. Teichert; Cynthia J. Luxford; Jaclyn M. Trate; Jordan T. Harshmann; Jamie L. Schneider – Chemistry Education Research and Practice, 2024
Providing students with feedback on their performance is a critical part of enhancing student learning in chemistry and is often integrated into homework assignments, quizzes, and exams. However, not all feedback is created equal, and the type of feedback the student receives can dramatically alter the utility of the feedback to reinforce correct…
Descriptors: Student Evaluation, Feedback (Response), Science Education, Introductory Courses
Dimitrov, Dimiter M. – Educational and Psychological Measurement, 2020
This study presents new models for item response functions (IRFs) in the framework of the D-scoring method (DSM) that is gaining attention in the field of educational and psychological measurement and largescale assessments. In a previous work on DSM, the IRFs of binary items were estimated using a logistic regression model (LRM). However, the LRM…
Descriptors: Item Response Theory, Scoring, True Scores, Scaling
Cohen, Yoav; Levi, Effi; Ben-Simon, Anat – Applied Measurement in Education, 2018
In the current study, two pools of 250 essays, all written as a response to the same prompt, were rated by two groups of raters (14 or 15 raters per group), thereby providing an approximation to the essay's true score. An automated essay scoring (AES) system was trained on the datasets and then scored the essays using a cross-validation scheme. By…
Descriptors: Test Validity, Automation, Scoring, Computer Assisted Testing
Yao, Lili; Haberman, Shelby J.; Zhang, Mo – ETS Research Report Series, 2019
Many assessments of writing proficiency that aid in making high-stakes decisions consist of several essay tasks evaluated by a combination of human holistic scores and computer-generated scores for essay features such as the rate of grammatical errors per word. Under typical conditions, a summary writing score is provided by a linear combination…
Descriptors: Prediction, True Scores, Computer Assisted Testing, Scoring
Erdodi, Laszlo A.; Richard, David C. S.; Hopwood, Christopher – Journal of Psychoeducational Assessment, 2009
Classical test theory assumes that ability level has no effect on measurement error. Newer test theories, however, argue that the precision of a measurement instrument changes as a function of the examinee's true score. Research has shown that administration errors are common in the Wechsler scales and that subtests requiring subjective scoring…
Descriptors: Scoring, Error of Measurement, True Scores, Intelligence Tests
Gierl, Mark J.; Cui, Ying; Zhou, Jiawen – Journal of Educational Measurement, 2009
The attribute hierarchy method (AHM) is a psychometric procedure for classifying examinees' test item responses into a set of structured attribute patterns associated with different components from a cognitive model of task performance. Results from an AHM analysis yield information on examinees' cognitive strengths and weaknesses. Hence, the AHM…
Descriptors: Test Items, True Scores, Psychometrics, Algebra
Edwards, Michael C.; Vevea, Jack L. – Journal of Educational and Behavioral Statistics, 2006
This article examines a subscore augmentation procedure. The approach uses empirical Bayes adjustments and is intended to improve the overall accuracy of measurement when information is scant. Simulations examined the impact of the method on subscale scores in a variety of realistic conditions. The authors focused on two popular scoring methods:…
Descriptors: Geometric Concepts, True Scores, Scoring, Item Response Theory

Wilcox, Rand R. – Applied Psychological Measurement, 1979
Using a new coefficient, a rescaling of the Bayes risk is examined and a modification of this coefficient is described which yields an index that always has a value between zero and one. (Author/MH)
Descriptors: Bayesian Statistics, Measurement Techniques, Scoring, Technical Reports

Wilcox, Rand R. – Journal of Educational Measurement, 1987
Four procedures are discussed for obtaining a confidence interval when answer-until-correct scoring is used in multiple choice tests. Simulated data show that the choice of procedure depends upon sample size. (GDC)
Descriptors: Computer Simulation, Multiple Choice Tests, Sample Size, Scoring
Rotou, Ourania; Elmore, Patricia B.; Headrick, Todd C. – 2001
This study investigated the number-correct scoring method based on different theories (classical true-score theory and multidimensional item response theory) when a standardized test requires more than one ability for an examinee to get a correct response. The number-correct scoring procedure that is widely used is the one that is defined in…
Descriptors: Item Response Theory, Scoring, Standardized Tests, Test Items
Kim, Dong-In; Brennan, Robert; Kolen, Michael – Journal of Educational Measurement, 2005
Four equating methods (3PL true score equating, 3PL observed score equating, beta 4 true score equating, and beta 4 observed score equating) were compared using four equating criteria: first-order equity (FOE), second-order equity (SOE), conditional-mean-squared-error (CMSE) difference, and the equi-percentile equating property. True score…
Descriptors: True Scores, Psychometrics, Equated Scores, Item Response Theory
Koplyay, Janos B.; And Others – 1972
The relationship between true ability (operationally defined as the number of items for which the examinee actually knew the correct answer) and the effects of guessing upon observed test variance was investigated. Three basic hypotheses were treated mathematically: there is no functional relationship between true ability and guessing success;…
Descriptors: Guessing (Tests), Predictor Variables, Probability, Scoring
Stanley, Julian C. – Educ Psychol Meas, 1970
It is shown that all obtained scores must meet the requirements for classical test-score theory with respect to definitions of true scores and errors of measurement if that frame of reference is to yield valid variance errors of measurement. (DG)
Descriptors: Measurement Techniques, Scores, Scoring, Statistical Analysis
Braun, Henry I.; Wainer, Howard – 1989
A desirable goal would be to develop a methodology for scoring essays so that the final grades are less affected by when or by whom each essay was read. It seems sensible to derive such grades by somehow adjusting the ratings originally given by each reader. This essay describes a solution that relies on statistical adjustment, using the context…
Descriptors: Essay Tests, Estimation (Mathematics), Interrater Reliability, Scoring
Klaas, Alan C. – 1975
Current usage and theory of standard error of measurement calls for one standard error of measurement figure to be used across all levels of scoring. The study revealed that scoring variance across scoring levels is not constant. As scoring ability increases scoring variance decreases. The assertion that low and high scoring subjects will…
Descriptors: Error of Measurement, Guessing (Tests), Scoring, Statistical Analysis