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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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David I. Hanauer; Tong Zhang; Mark Graham; Graham Hatfull – CBE - Life Sciences Education, 2025
The aim of inclusive education is to provide a supportive space for students from every background. The theory of intersectionality suggests that multiple identities intersect within social spaces to construct specific positionalities. To support the heterogeneity of all students, there is a need to understand who is in our Science, Technology,…
Descriptors: STEM Education, Student Characteristics, Identification, Intersectionality
Mauer, Victoria; Savell, Shannon; Davis, Alida; Wilson, Melvin N.; Shaw, Daniel S.; Lemery-Chalfant, Kathryn – Journal of Early Adolescence, 2021
This study examined caregivers' longitudinal reports of adolescent multiracial categorization across the ages of 9.5, 10.5, and 14 years, and adolescents' reports of their own multiracial categorization at the age of 14 years. A portion of caregivers' reports of adolescent multiracial status were inconsistent across the years of the study; some…
Descriptors: Adolescents, Multiracial Persons, Classification, Identification
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Freya Wright; Anastasia Hronis; Rachel Roberts; Lynette Roberts; Ian Kneebone – Educational and Developmental Psychologist, 2025
Objective: People with intellectual disabilities have historically often been excluded from cognitive based therapies, due to their cognitive deficits. However, adults with intellectual disabilities have been found to have the core cognitive abilities necessary to engage in Cognitive Behaviour Therapy. Despite this emerging evidence, the capacity…
Descriptors: Intellectual Disability, Cognitive Restructuring, Children, Child Behavior
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Austin Wyman; Zhiyong Zhang – Grantee Submission, 2025
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…
Descriptors: Artificial Intelligence, Algorithms, Computer Software, Identification
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Murray Parker; Dirk H. R. Spennemann; Jennifer Bond – Field Methods, 2025
Single and multiple sense stimuli create sensescapes, which combine to be perceived as multisensory integrated products. Such encounters may be experienced across multiple spaces and have importance due to esthetic sensuality, cultural value, economic benefit, or religious significance. This article presents a methodological protocol for the…
Descriptors: Identification, Documentation, Sensory Experience, Multisensory Learning
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Marta Marcilla-Jorda; Catarina Grande; Vera Coelho; César Rubio-Belmonte; Micaela Moro-Ipola – Journal of Autism and Developmental Disorders, 2025
Autism spectrum disorder (ASD) is characterized by impairments in many functional areas requiring long-term interventions to promote autonomy. This study aims to map The Sensory Profile™ 2 (SP-2), one of the most widely used assessment tools in children with ASD, with the International Classification of Functioning, Disability and Health for…
Descriptors: Sensory Experience, Profiles, Autism Spectrum Disorders, Classification
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Zifeng Liu; Wanli Xing; Xinyue Jiao; Chenglu Li; Wangda Zhu – Education and Information Technologies, 2025
The ability of large language models (LLMs) to generate code has raised concerns in computer science education, as students may use tools like ChatGPT for programming assignments. While much research has focused on higher education, especially for languages like Java and Python, little attention has been given to K-12 settings, particularly for…
Descriptors: High School Students, Coding, Artificial Intelligence, Electronic Learning
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Muhammad Bilal Saqib; Saba Zia – Journal of Applied Research in Higher Education, 2025
Purpose: The notion of using a generative artificial intelligence (AI) engine for text composition has gained excessive popularity among students, educators and researchers, following the introduction of ChatGPT. However, this has added another dimension to the daunting task of verifying originality in academic writing. Consequently, the market…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Evaluation
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Victoria E. Goldman; Jacqueline Antoun; Panteha Hayati Rezvan; Kevin Fang – Journal of School Health, 2025
Background: School absenteeism and health have a close bidirectional link: children with medical conditions miss more school, and chronic absenteeism is tied to poor health outcomes. Despite rising absenteeism, tools to assess school attendance in healthcare settings remain underexplored. Brief, standardized attendance screening may help address…
Descriptors: Attendance, Attendance Patterns, Screening Tests, Special Health Problems
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Richard M. Kubina Jr.; Madeline Halkowski; Kirsten K. L. Yurich; Kimberly Ghorm; Nora M. Healy – Journal of Behavioral Education, 2024
Operational definitions have a significant history in applied behavior analysis. The practice's importance stems from the role operational definitions play in detecting an event, human thought, or action. While operationalizing target behaviors has enjoyed widespread practice, some concerns have recently arisen with translation validity and…
Descriptors: Identification, Accuracy, Definitions, Applied Behavior Analysis
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Mike Perkins; Jasper Roe; Darius Postma; James McGaughran; Don Hickerson – Journal of Academic Ethics, 2024
This study explores the capability of academic staff assisted by the Turnitin Artificial Intelligence (AI) detection tool to identify the use of AI-generated content in university assessments. 22 different experimental submissions were produced using Open AI's ChatGPT tool, with prompting techniques used to reduce the likelihood of AI detectors…
Descriptors: Artificial Intelligence, Student Evaluation, Identification, Natural Language Processing
Jessica Gatewood – ProQuest LLC, 2024
This non-experimental causal-comparative study aims to explore the possible effect of expertise on learning experience design (LXD) deviation identification and the classification of these deviations in alignment with provided learning experience design constructs within a learning technology. Additionally, this study challenges Nielsen's (1993)…
Descriptors: Educational Technology, Novices, Expertise, Learning Experience
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Martino Ongis; David Kidd; Jess Miner – Journal of Academic Ethics, 2024
As colleges and universities seek to invigorate ethics education, they need methods to identify where and describe how ethics is already present across their curricula. Meeting this need is complicated by the fact that much ethics education occurs in courses not explicitly focused on ethics or morality. In this paper, we review recent…
Descriptors: Higher Education, Ethics, College Curriculum, Relevance (Education)
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Oscar Karnalim; Hapnes Toba; Meliana Christianti Johan – Education and Information Technologies, 2024
Artificial Intelligence (AI) can foster education but can also be misused to breach academic integrity. Large language models like ChatGPT are able to generate solutions for individual assessments that are expected to be completed independently. There are a number of automated detectors for AI assisted work. However, most of them are not dedicated…
Descriptors: Artificial Intelligence, Academic Achievement, Integrity, Introductory Courses
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