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DiVirgilio, Raymond – ProQuest LLC, 2023
This study examined whether athletic training students in a four-year undergraduate entry-level accredited athletic training program in a postsecondary institution perceived the PEARLS model as effective in providing feedback. Although students look to the feedback process to help them better understand their skill and performance level when…
Descriptors: Undergraduate Students, Athletics, Feedback (Response), Models
Mark L. Davison; David J. Weiss; Joseph N. DeWeese; Ozge Ersan; Gina Biancarosa; Patrick C. Kennedy – Journal of Educational and Behavioral Statistics, 2023
A tree model for diagnostic educational testing is described along with Monte Carlo simulations designed to evaluate measurement accuracy based on the model. The model is implemented in an assessment of inferential reading comprehension, the Multiple-Choice Online Causal Comprehension Assessment (MOCCA), through a sequential, multidimensional,…
Descriptors: Cognitive Processes, Diagnostic Tests, Measurement, Accuracy
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Nieto, Ricardo; Casabianca, Jodi M. – Journal of Educational Measurement, 2019
Many large-scale assessments are designed to yield two or more scores for an individual by administering multiple sections measuring different but related skills. Multidimensional tests, or more specifically, simple structured tests, such as these rely on multiple multiple-choice and/or constructed responses sections of items to generate multiple…
Descriptors: Tests, Scoring, Responses, Test Items
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Xiao, Yue; Veldkamp, Bernard; Liu, Hongyun – Educational Measurement: Issues and Practice, 2022
The action sequences of respondents in problem-solving tasks reflect rich and detailed information about their performance, including differences in problem-solving ability, even if item scores are equal. It is therefore not sufficient to infer individual problem-solving skills based solely on item scores. This study is a preliminary attempt to…
Descriptors: Problem Solving, Item Response Theory, Scores, Item Analysis
Ryan Derickson – ProQuest LLC, 2022
Item Response Theory (IRT) models are a popular analytic method for self report data. We show how traditional IRT models can be vulnerable to specific kinds of asymmetric measurement error (AME) in self-report data, because the models spread the error to all estimates -- even those of items that do not contribute error. We quantify the impact of…
Descriptors: Item Response Theory, Measurement Techniques, Error of Measurement, Models
Jing Ouyang; Gongjun Xu – Grantee Submission, 2022
Latent class models with covariates are widely used for psychological, social, and educational research. Yet the fundamental identifiability issue of these models has not been fully addressed. Among the previous research on the identifiability of latent class models with covariates, Huang and Bandeen-Roche (Psychometrika 69:5-32, 2004) studied the…
Descriptors: Item Response Theory, Models, Identification, Psychological Studies
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Maria Bolsinova; Jesper Tijmstra; Leslie Rutkowski; David Rutkowski – Journal of Educational and Behavioral Statistics, 2024
Profile analysis is one of the main tools for studying whether differential item functioning can be related to specific features of test items. While relevant, profile analysis in its current form has two restrictions that limit its usefulness in practice: It assumes that all test items have equal discrimination parameters, and it does not test…
Descriptors: Test Items, Item Analysis, Generalizability Theory, Achievement Tests
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Meijuan Li; Hongyun Liu; Mengfei Cai; Jianlin Yuan – Education and Information Technologies, 2024
In the human-to-human Collaborative Problem Solving (CPS) test, students' problem-solving process reflects the interdependency among partners. The high interdependency in CPS makes it very sensitive to group composition. For example, the group outcome might be driven by a highly competent group member, so it does not reflect all the individual…
Descriptors: Problem Solving, Computer Assisted Testing, Cooperative Learning, Task Analysis
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Zhichen Guo; Daxun Wang; Yan Cai; Dongbo Tu – Educational and Psychological Measurement, 2024
Forced-choice (FC) measures have been widely used in many personality or attitude tests as an alternative to rating scales, which employ comparative rather than absolute judgments. Several response biases, such as social desirability, response styles, and acquiescence bias, can be reduced effectively. Another type of data linked with comparative…
Descriptors: Item Response Theory, Models, Reaction Time, Measurement Techniques
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Stefan Vermeent; Ethan S. Young; Meriah L. DeJoseph; Anna-Lena Schubert; Willem E. Frankenhuis – Developmental Science, 2024
Childhood adversity can lead to cognitive deficits or enhancements, depending on many factors. Though progress has been made, two challenges prevent us from integrating and better understanding these patterns. First, studies commonly use and interpret raw performance differences, such as response times, which conflate different stages of cognitive…
Descriptors: Early Experience, Trauma, Cognitive Processes, Children
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Anna Moni – Online Learning, 2024
Despite extensive research on feedback models, there is still sparse empirical evidence of their validity and application in higher education learning settings, whether online, hybrid, or face-to-face. Understanding how a feedback framework--integrated in the instructional cycle--is perceived by the learners can provide empirical support about its…
Descriptors: Student Attitudes, Feedback (Response), Electronic Learning, Blended Learning
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Hyeongdon Moon; Richard Lee Davis; Seyed Parsa Neshaei; Pierre Dillenbourg – International Educational Data Mining Society, 2025
Knowledge tracing models have enabled a range of intelligent tutoring systems to provide feedback to students. However, existing methods for knowledge tracing in learning sciences are predominantly reliant on statistical data and instructor-defined knowledge components, making it challenging to integrate AI-generated educational content with…
Descriptors: Artificial Intelligence, Natural Language Processing, Automation, Information Management
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Nehyba, Jan; Štefánik, Michal – Education and Information Technologies, 2023
Social sciences expose many cognitively complex, highly qualified, or fuzzy problems, whose resolution relies primarily on expert judgement rather than automated systems. One of such instances that we study in this work is a reflection analysis in the writings of student teachers. We share a hands-on experience on how these challenges can be…
Descriptors: Models, Language, Reflection, Writing (Composition)
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Zinsser, Katherine M.; Curby, Timothy W.; Gordon, Rachel A.; Moberg, Sarah – Learning Environments Research, 2023
Modeling, responding, and instructing have all been investigated as ways in which adults promote children's emotional competence, but they have largely been investigated separately. To facilitate the development of effective professional development models which promote teachers' engagement in emotion-focused teaching, it is important to…
Descriptors: Faculty Development, Models, Teaching Methods, Psychological Patterns
Philip I. Pavlik; Luke G. Eglington – Grantee Submission, 2023
This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…
Descriptors: Students, Models, Regression (Statistics), Alternative Assessment
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