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Nicholas Hobbs; Janet Steele – HAPS Educator, 2025
Formative assessment is a type of low-stakes assessment that can help reduce student anxiety and encourage students to engage in the course regularly. Formative assessment can also help instructors identify knowledge gaps. Students who had completed the first semester of a two-semester sophomore-level anatomy and physiology sequence were surveyed…
Descriptors: Anatomy, Physiology, Tests, Learner Engagement
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Beyza Aksu Dünya; Stefanie A. Wind; Mehmet Can Demir – SAGE Open, 2025
The purpose of this study was to generate an item bank for assessing faculty members' assessment literacy and to examine the applicability and feasibility of a Computerized Adaptive Test (CAT) approach to monitor assessment literacy among faculty members. In developing this assessment using a sequential mixed-methods research design, our goal was…
Descriptors: Assessment Literacy, Item Banks, College Faculty, Adaptive Testing
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Renáta Kiss; Beno Csapó – International Journal of Early Childhood, 2025
Previous research has shown that phonological awareness is one of the most important prerequisites for early reading. Monitoring its development requires reliable, easy-to-use instruments especially in the last years of kindergarten. The present study aims to explore the potential for assessing phonological awareness and some of its subskills…
Descriptors: Phonological Awareness, Kindergarten, Reading Skills, Student Evaluation
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Manoj Patil; Abhay Gaidhane; Zahiruddin Quazi Syed – Journal of Education Human Resources, 2025
The recruitment and selection process are two of the most important human resource functions having a great impact on the growth and success of an organization as compared to other tasks such as retention, onboarding, leadership development, and managing talent. Stepping Stones is a project for scaling the early childhood development of children…
Descriptors: Personnel Selection, Recruitment, Public Health, Young Children
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Luyang Fang; Gyeonggeon Lee; Xiaoming Zhai – Journal of Educational Measurement, 2025
Machine learning-based automatic scoring faces challenges with imbalanced student responses across scoring categories. To address this, we introduce a novel text data augmentation framework that leverages GPT-4, a generative large language model specifically tailored for imbalanced datasets in automatic scoring. Our experimental dataset consisted…
Descriptors: Computer Assisted Testing, Artificial Intelligence, Automation, Scoring
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Jing Huang; Yuxiao Zhang; Jason W. Morphew; Jayson M. Nissen; Ben Van Dusen; Hua Hua Chang – Journal of Educational Measurement, 2025
Online calibration estimates new item parameters alongside previously calibrated items, supporting efficient item replenishment. However, most existing online calibration procedures for Cognitive Diagnostic Computerized Adaptive Testing (CD-CAT) lack mechanisms to ensure content balance during live testing. This limitation can lead to uneven…
Descriptors: Adaptive Testing, Computer Assisted Testing, Cognitive Measurement, Test Items
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Ramnarain-Seetohul, Vidasha; Bassoo, Vandana; Rosunally, Yasmine – Education and Information Technologies, 2022
In automated essay scoring (AES) systems, similarity techniques are used to compute the score for student answers. Several methods to compute similarity have emerged over the years. However, only a few of them have been widely used in the AES domain. This work shows the findings of a ten-year review on similarity techniques applied in AES systems…
Descriptors: Computer Assisted Testing, Essays, Scoring, Automation
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Cui, Zhongmin – Measurement: Interdisciplinary Research and Perspectives, 2022
Although many educational and psychological tests are labeled as computerized adaptive test (CAT), not all tests show the same level of adaptivity -- some tests might not have much adaptation because of various constraints imposed by test developers. Researchers have proposed some indices to measure the amount of adaption for an adaptive test.…
Descriptors: Adaptive Testing, Computer Assisted Testing, Measurement Techniques
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Ingrisone, Soo Jeong; Ingrisone, James N. – Educational Measurement: Issues and Practice, 2023
There has been a growing interest in approaches based on machine learning (ML) for detecting test collusion as an alternative to the traditional methods. Clustering analysis under an unsupervised learning technique appears especially promising to detect group collusion. In this study, the effectiveness of hierarchical agglomerative clustering…
Descriptors: Identification, Cooperation, Computer Assisted Testing, Artificial Intelligence
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Cheng, Yiling – Measurement: Interdisciplinary Research and Perspectives, 2023
Computerized adaptive testing (CAT) offers an efficient and highly accurate method for estimating examinees' abilities. In this article, the free version of Concerto Software for CAT was reviewed, dividing our evaluation into three sections: software implementation, the Item Response Theory (IRT) features of CAT, and user experience. Overall,…
Descriptors: Computer Software, Computer Assisted Testing, Adaptive Testing, Item Response Theory
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Alhadi, Moosa; Zhang, Dake; Wang, Ting; Maher, Carolyn A. – Computers in the Schools, 2023
This research synthesizes studies that used a Digitalized Interactive Component (DIC) to assess K-12 student performance during Computer-based-Assessments (CBAs) in mathematics. A systematic search identified ten studies, including four that provided language assistance and six that provided response-construction support. We reported on the one…
Descriptors: Computer Assisted Testing, Mathematics Tests, Student Evaluation, Elementary Secondary Education
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Gilbert, Kacey; Benson, Nicholas F.; Kranzler, John H. – Contemporary School Psychology, 2023
Despite the fact that the digital administration format of Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V) was published in 2016, no research to date has examined its factor structure using all 10 of the primary subtests to measure intellectual ability. The purpose of this study, therefore, was to use exploratory and confirmatory…
Descriptors: Computer Assisted Testing, Children, Intelligence Tests, Factor Structure
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Xiong, Yao; Schunn, Christian D.; Wu, Yong – Journal of Computer Assisted Learning, 2023
Background: For peer assessment, reliability (i.e., consistency in ratings across peers) and validity (i.e., consistency of peer ratings with instructors or experts) are frequently examined in the research literature to address a central concern of instructors and students. Although the average levels are generally promising, both reliability and…
Descriptors: Peer Evaluation, Computer Assisted Testing, Test Reliability, Test Validity
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Zinovy Radovilsky; Vishwanath Hegde – Curriculum and Teaching, 2023
The issues of academic integrity across online and in-person assessments were addressed by analyzing student total, conceptual, and numerical performance scores in the three modes of assessment: (1) In-person assessment with proctoring; (2) Online unproctored assessment; and (3) Respondus assessment online with proctoring. It was identified that…
Descriptors: Academic Achievement, Educational Technology, Computer Assisted Testing, Evaluation
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Selcuk Acar; Peter Organisciak; Denis Dumas – Journal of Creative Behavior, 2025
In this three-study investigation, we applied various approaches to score drawings created in response to both Form A and Form B of the Torrance Tests of Creative Thinking-Figural (broadly TTCT-F) as well as the Multi-Trial Creative Ideation task (MTCI). We focused on TTCT-F in Study 1, and utilizing a random forest classifier, we achieved 79% and…
Descriptors: Scoring, Computer Assisted Testing, Models, Correlation
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