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Showing all 13 results Save | Export
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Pavel Chernyavskiy; Traci S. Kutaka; Carson Keeter; Julie Sarama; Douglas Clements – Grantee Submission, 2024
When researchers code behavior that is undetectable or falls outside of the validated ordinal scale, the resultant outcomes often suffer from informative missingness. Incorrect analysis of such data can lead to biased arguments around efficacy and effectiveness in the context of experimental and intervention research. Here, we detail a new…
Descriptors: Bayesian Statistics, Mathematics Instruction, Learning Trajectories, Item Response Theory
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Lee, HyeSun; Smith, Weldon Z. – Educational and Psychological Measurement, 2020
Based on the framework of testlet models, the current study suggests the Bayesian random block item response theory (BRB IRT) model to fit forced-choice formats where an item block is composed of three or more items. To account for local dependence among items within a block, the BRB IRT model incorporated a random block effect into the response…
Descriptors: Bayesian Statistics, Item Response Theory, Monte Carlo Methods, Test Format
Klint Kanopka – ProQuest LLC, 2023
As online learning platforms and computerized testing become more common, an increasing amount of data are collected about users. These data include, but are not limited to, response time, keystroke logs, and raw text. The desire to observe these features of the response process reflect an underlying interest in the cognitive processes and…
Descriptors: Scores, Computation, Data Interpretation, Behavior Patterns
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Kaiwen Man – Educational and Psychological Measurement, 2024
In various fields, including college admission, medical board certifications, and military recruitment, high-stakes decisions are frequently made based on scores obtained from large-scale assessments. These decisions necessitate precise and reliable scores that enable valid inferences to be drawn about test-takers. However, the ability of such…
Descriptors: Prior Learning, Testing, Behavior, Artificial Intelligence
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Man, Kaiwen; Harring, Jeffrey R. – Educational and Psychological Measurement, 2021
Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given…
Descriptors: Cheating, Item Response Theory, Reaction Time, Eye Movements
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Shi Pu; Yu Yan; Brandon Zhang – Journal of Educational Data Mining, 2024
We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…
Descriptors: Prediction, Success, Data Analysis, Learning Analytics
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Scoular, Claire; Care, Esther – Educational Assessment, 2019
Recent educational and psychological research has highlighted shifting workplace requirements and change required to equip the emerging workforce with skills for the 21st century. The emergence of these highlights the issues, and drives the importance, of new methods of assessment. This study addresses some of the issues by describing a scoring…
Descriptors: Cooperation, Problem Solving, Scoring, 21st Century Skills
Jing Lu; Chun Wang; Ningzhong Shi – Grantee Submission, 2023
In high-stakes, large-scale, standardized tests with certain time limits, examinees are likely to engage in either one of the three types of behavior (e.g., van der Linden & Guo, 2008; Wang & Xu, 2015): solution behavior, rapid guessing behavior, and cheating behavior. Oftentimes examinees do not always solve all items due to various…
Descriptors: High Stakes Tests, Standardized Tests, Guessing (Tests), Cheating
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Liu, Ming-Tsung; Yu, Pao-Ta – Educational Technology & Society, 2011
A personalized e-learning service provides learning content to fit learners' individual differences. Learning achievements are influenced by cognitive as well as non-cognitive factors such as mood, motivation, interest, and personal styles. This paper proposes the Learning Caution Indexes (LCI) to detect aberrant learning patterns. The philosophy…
Descriptors: Electronic Learning, Statistics, Tutoring, Computer Assisted Instruction
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Gotham, Katherine; Risi, Susan; Pickles, Andrew; Lord, Catherine – Journal of Autism and Developmental Disorders, 2007
Autism Diagnostic Observation Schedule (ADOS) Modules 1-3 item and domain total distributions were reviewed for 1,630 assessments of children aged 14 months to 16 years with an autism spectrum disorder (ASD) or with heterogeneous non-spectrum disorders. Children were divided by language level and age to yield more homogeneous cells. Items were…
Descriptors: Measures (Individuals), Autism, Children, Evaluation Methods
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Waugh, Russell F. – Journal of Applied Measurement, 2003
Designed a questionnaire and created a scale measuring studying and learning based on motivation with items answered from ideal, "capability," and studying and learning behavior perspectives. Results for 372 Australian college students support the view that striving for excellence, desire to learn, and personal incentives are important…
Descriptors: Attitude Measures, Behavior Patterns, College Students, Foreign Countries
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Waugh, Russell F.; Hii, Teck Kiong; Islam, Atique – Journal of Applied Measurement, 2000
Developed a questionnaire of 80 self-report items to measure student approaches to study in higher education, attempting to create a scale and study it with a Rasch measurement model. Results for 350 Australian college students supported the conceptual structure of the scale as involving studying attitudes and behaviors toward the identified five…
Descriptors: Adults, Behavior Patterns, Check Lists, College Students
Harvey-Beavis, Adrian – 1994
How teachers' judgments about student literacy behavior were analyzed under the Rasch model is described. The analysis was done to assist staff of the Western Australian Department of Education to revise aspects of a literacy program called "First Steps" for the early years of school. First Steps uses a developmental continuum of small…
Descriptors: Behavior Patterns, Child Development, Educational Assessment, Elementary Education