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Hung, Su-Pin; Huang, Hung-Yu – Journal of Educational and Behavioral Statistics, 2022
To address response style or bias in rating scales, forced-choice items are often used to request that respondents rank their attitudes or preferences among a limited set of options. The rating scales used by raters to render judgments on ratees' performance also contribute to rater bias or errors; consequently, forced-choice items have recently…
Descriptors: Evaluation Methods, Rating Scales, Item Analysis, Preferences
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Garman, Andrew N.; Erwin, Taylor S.; Garman, Tyler R.; Kim, Dae Hyun – Journal of Competency-Based Education, 2021
Background: Competency models provide useful frameworks for organizing learning and assessment programs, but their construction is both time intensive and subject to perceptual biases. Some aspects of model development may be particularly well-suited to automation, specifically natural language processing (NLP), which could also help make them…
Descriptors: Natural Language Processing, Automation, Guidelines, Leadership Effectiveness
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Wang, Wen-Chung; Su, Chi-Ming; Qiu, Xue-Lan – Journal of Educational Measurement, 2014
Ratings given to the same item response may have a stronger correlation than those given to different item responses, especially when raters interact with one another before giving ratings. The rater bundle model was developed to account for such local dependence by forming multiple ratings given to an item response as a bundle and assigning…
Descriptors: Item Response Theory, Interrater Reliability, Models, Correlation
Nye, Benjamin D.; Morrison, Donald M.; Samei, Borhan – International Educational Data Mining Society, 2015
Archived transcripts from tens of millions of online human tutoring sessions potentially contain important knowledge about how online tutors help, or fail to help, students learn. However, without ways of automatically analyzing these large corpora, any knowledge in this data will remain buried. One way to approach this issue is to train an…
Descriptors: Tutoring, Instructional Effectiveness, Tutors, Models
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Nakkula, Michael J.; Harris, John T. – New Directions for Youth Development, 2010
Measuring the various structural aspects of the organizing framework for this volume and relating them to match quality and relevant developmental outcomes is a critical step toward assessing the framework's utility for practitioners, policymakers, and program evaluators. Nakkula and Harris take a step in that direction by exploring core…
Descriptors: Mentors, Evaluators, Prediction, Models
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Zhang, Mo; Breyer, F. Jay; Lorenz, Florian – ETS Research Report Series, 2013
In this research, we investigated the suitability of implementing "e-rater"® automated essay scoring in a high-stakes large-scale English language testing program. We examined the effectiveness of generic scoring and 2 variants of prompt-based scoring approaches. Effectiveness was evaluated on a number of dimensions, including agreement…
Descriptors: Computer Assisted Testing, Computer Software, Scoring, Language Tests
Jia, Yujie – ProQuest LLC, 2013
This study employed Bachman and Palmer's (2010) Assessment Use Argument framework to investigate to what extent the use of a second language oral test as an exit test in a Hong Kong university can be justified. It also aimed to help test developers of this oral test identify the most critical areas in the current test design that might need…
Descriptors: Test Use, Language Tests, Oral Language, Second Language Learning
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Sivo, Stephen; Fan, Xitao – Educational Research and Evaluation, 2008
Autocorrelated residuals in longitudinal data are widely reported as common to longitudinal data. Yet few, if any, researchers modeling growth processes evaluate a priori whether their data have this feature. Sivo, Fan, and Witta (2005) found that not modeling autocorrelated residuals present in longitudinal data severely biases latent curve…
Descriptors: Longitudinal Studies, Models, Data Analysis, Correlation