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Showing 1 to 15 of 190 results Save | Export
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Gregory M. Hurtz; Regi Mucino – Journal of Educational Measurement, 2024
The Lognormal Response Time (LNRT) model measures the speed of test-takers relative to the normative time demands of items on a test. The resulting speed parameters and model residuals are often analyzed for evidence of anomalous test-taking behavior associated with fast and poorly fitting response time patterns. Extending this model, we…
Descriptors: Student Reaction, Reaction Time, Response Style (Tests), Test Items
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Martijn Schoenmakers; Jesper Tijmstra; Jeroen Vermunt; Maria Bolsinova – Educational and Psychological Measurement, 2024
Extreme response style (ERS), the tendency of participants to select extreme item categories regardless of the item content, has frequently been found to decrease the validity of Likert-type questionnaire results. For this reason, various item response theory (IRT) models have been proposed to model ERS and correct for it. Comparisons of these…
Descriptors: Item Response Theory, Response Style (Tests), Models, Likert Scales
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van der Linden, Wim J.; Belov, Dmitry I. – Journal of Educational Measurement, 2023
A test of item compromise is presented which combines the test takers' responses and response times (RTs) into a statistic defined as the number of correct responses on the item for test takers with RTs flagged as suspicious. The test has null and alternative distributions belonging to the well-known family of compound binomial distributions, is…
Descriptors: Item Response Theory, Reaction Time, Test Items, Item Analysis
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Cornelia Eva Neuert – Sociological Methods & Research, 2024
The quality of data in surveys is affected by response burden and questionnaire length. With an increasing number of questions, respondents can become bored, tired, and annoyed and may take shortcuts to reduce the effort needed to complete the survey. In this article, direct evidence is presented on how the position of items within a web…
Descriptors: Online Surveys, Test Items, Test Format, Test Construction
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Ö. Emre C. Alagöz; Thorsten Meiser – Educational and Psychological Measurement, 2024
To improve the validity of self-report measures, researchers should control for response style (RS) effects, which can be achieved with IRTree models. A traditional IRTree model considers a response as a combination of distinct decision-making processes, where the substantive trait affects the decision on response direction, while decisions about…
Descriptors: Item Response Theory, Validity, Self Evaluation (Individuals), Decision Making
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Stefanie A. Wind; Beyza Aksu-Dunya – Applied Measurement in Education, 2024
Careless responding is a pervasive concern in research using affective surveys. Although researchers have considered various methods for identifying careless responses, studies are limited that consider the utility of these methods in the context of computer adaptive testing (CAT) for affective scales. Using a simulation study informed by recent…
Descriptors: Response Style (Tests), Computer Assisted Testing, Adaptive Testing, Affective Measures
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Schweizer, Karl; Wang, Tengfei; Ren, Xuezhu – Journal of Experimental Education, 2022
The essay reports two studies on confirmatory factor analysis of speeded data with an effect of selective responding. This response strategy leads test takers to choose their own working order instead of completing the items along with the given order. Methods for detecting speededness despite such a deviation from the given order are proposed and…
Descriptors: Factor Analysis, Response Style (Tests), Decision Making, Test Items
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van der Linden, Wim J. – Journal of Educational and Behavioral Statistics, 2022
Two independent statistical tests of item compromise are presented, one based on the test takers' responses and the other on their response times (RTs) on the same items. The tests can be used to monitor an item in real time during online continuous testing but are also applicable as part of post hoc forensic analysis. The two test statistics are…
Descriptors: Test Items, Item Analysis, Item Response Theory, Computer Assisted Testing
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Colombi, Roberto; Giordano, Sabrina; Tutz, Gerhard – Journal of Educational and Behavioral Statistics, 2021
A mixture of logit models is proposed that discriminates between responses to rating questions that are affected by a tendency to prefer middle or extremes of the scale regardless of the content of the item (response styles) and purely content-driven preferences. Explanatory variables are used to characterize the content-driven way of answering as…
Descriptors: Rating Scales, Response Style (Tests), Test Items, Models
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He, Qingping; Meadows, Michelle; Black, Beth – Research Papers in Education, 2022
A potential negative consequence of high-stakes testing is inappropriate test behaviour involving individuals and/or institutions. Inappropriate test behaviour and test collusion can result in aberrant response patterns and anomalous test scores and invalidate the intended interpretation and use of test results. A variety of statistical techniques…
Descriptors: Statistical Analysis, High Stakes Tests, Scores, Response Style (Tests)
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Leventhal, Brian C.; Gregg, Nikole; Ames, Allison J. – Measurement: Interdisciplinary Research and Perspectives, 2022
Response styles introduce construct-irrelevant variance as a result of respondents systematically responding to Likert-type items regardless of content. Methods to account for response styles through data analysis as well as approaches to mitigating the effects of response styles during data collection have been well-documented. Recent approaches…
Descriptors: Response Style (Tests), Item Response Theory, Test Items, Likert Scales
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Clariana, Roy B.; Park, Eunsung – Educational Technology Research and Development, 2021
Cognitive and metacognitive processes during learning depend on accurate monitoring, this investigation examines the influence of immediate item-level knowledge of correct response feedback on cognition monitoring accuracy. In an optional end-of-course computer-based review lesson, participants (n = 68) were randomly assigned to groups to receive…
Descriptors: Feedback (Response), Cognitive Processes, Accuracy, Difficulty Level
Steven R. Hiner – ProQuest LLC, 2023
The purpose of this study was to determine if there were significant statistical differences between scores on constructed response and computer-scorable questions on an accelerated middle school math placement test in a large urban school district in Ohio, and to ensure that all students have an opportunity to take the test. Five questions on a…
Descriptors: Scores, Middle Schools, Mathematics Tests, Placement Tests
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Liu, Yue; Liu, Hongyun – Journal of Educational and Behavioral Statistics, 2021
The prevalence and serious consequences of noneffortful responses from unmotivated examinees are well-known in educational measurement. In this study, we propose to apply an iterative purification process based on a response time residual method with fixed item parameter estimates to detect noneffortful responses. The proposed method is compared…
Descriptors: Response Style (Tests), Reaction Time, Test Items, Accuracy
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Gummer, Tobias; Roßmann, Joss; Silber, Henning – Sociological Methods & Research, 2021
Identifying inattentive respondents in self-administered surveys is a challenging goal for survey researchers. Instructed response items (IRIs) provide a measure for inattentiveness in grid questions that is easy to implement. The present article adds to the sparse research on the use and implementation of attention checks by addressing three…
Descriptors: Online Surveys, Attention, Response Style (Tests), Context Effect
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