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Direct linkEbru Boga; Rukiye Arslan; Suna Tarkoçin; Ahmet Temiz; Mehmet Saglam – International Journal of Developmental Disabilities, 2024
Early diagnosis is extremely important for children with autism spectrum disorder (ASD), as other children having developmental disabilities. In early diagnosis, which is one of the most important elements of the treatment process, parents have a special place with different factors. Considering the importance of parents in early diagnosis, the…
Descriptors: Child Development, Autism Spectrum Disorders, Identification, Opinions
Jeff Moher; Anna Delos Reyes; Trafton Drew – Cognitive Research: Principles and Implications, 2024
Irrelevant salient distractors can trigger early quitting in visual search, causing observers to miss targets they might otherwise find. Here, we asked whether task-relevant salient cues can produce a similar early quitting effect on the subset of trials where those cues fail to highlight the target. We presented participants with a difficult…
Descriptors: Attention, Cues, Environmental Influences, Visual Perception
Helen Milojevich; Lana Beasley; Stormie Fuller; Olivia Lane; David Bard – Prevention Science, 2025
Developmental monitoring and promotion efforts are keys to identifying potential developmental concerns and connecting young children to intervention services. Evidence-based home visiting programs are one avenue for developmental monitoring and promotion, particularly for families with young children who may need extra support (e.g., families…
Descriptors: Home Visits, Young Children, Identification, Child Development
Lord J. Hyeamang; Tejas C. Sekhar; Emily Rush; Amy C. Beresheim; Colleen M. Cheverko; William S. Brooks; Abbey C. M. Breckling; M. Nazmul Karim; Christopher Ferrigno; Adam B. Wilson – Anatomical Sciences Education, 2025
Evidence suggests custom chatbots are superior to commercial generative artificial intelligence (GenAI) systems for text-based anatomy content inquiries. This study evaluates ChatGPT-4o's and Claude 3.5 Sonnet's capabilities to interpret unlabeled anatomical images. Secondarily, ChatGPT o1-preview was evaluated as an AI rater to grade AI-generated…
Descriptors: Artificial Intelligence, Anatomy, Identification, Man Machine Systems
Joseph Hin Yan Lam; Michelle N. Ramos; Jiali Wang; Aquiles Iglesias; Elizabeth D. Peña; Lisa M. Bedore; Ronald B. Gillam – Journal of Speech, Language, and Hearing Research, 2025
Purpose: The challenges of language assessment in bilinguals include a lack of assessment tools and bilingual speech-language pathology services. Additionally, the weighting of subtests in standardized tests has not been empirically explored to maximize sensitivity and specificity. Language exposure might also inform the decision to diagnose…
Descriptors: Bilingualism, Young Children, Spanish, English
Baldassari, Mario J.; Moore, Kara N.; Hyman, Ira E., Jr.; Hope, Lorraine; Mah, Eric Y.; Lindsay, D. Stephen; Mansour, Jamal; Saraiva, Renan; Horry, Ruth; Rath, Hannah; Kelly, Lauren; Jones, Rosie; Vale, Shannan; Lawson, Bethany; Pedretti, Josh; Palma, Tomás A.; Cruz, Francisco; Quarenta, Joana; Van der Cruyssen, Ine; Mileva, Mila; Allen, Jessica; Jeye, Brittany; Wiechert, Sara – Cognitive Research: Principles and Implications, 2023
Research on eyewitness identification often involves exposing participants to a simulated crime and later testing memory using a lineup. We conducted a systematic review showing that pre-event instructions, instructions given before event exposure, are rarely reported and those that are reported vary in the extent to which they warn participants…
Descriptors: Memory, Audiences, Attention, Observation
McKinley, Geoffrey L.; Peterson, Daniel J. – Cognitive Research: Principles and Implications, 2023
When selecting fillers to include in a police lineup, one must consider the level of similarity between the suspect and potential fillers. In order to reduce misidentifications, an innocent suspect should not stand out. Therefore, it is important that the fillers share some degree of similarity. Importantly, increasing suspect-filler similarity…
Descriptors: Identification, Human Body, Models, Crime
Patton, Colleen E.; Wickens, Christopher D.; Smith, C. A. P.; Noble, Kayla M.; Clegg, Benjamin A. – Cognitive Research: Principles and Implications, 2023
In a dynamic decision-making task simulating basic ship movements, participants attempted, through a series of actions, to elicit and identify which one of six other ships was exhibiting either of two hostile behaviors. A high-performing, although imperfect, automated attention aid was introduced. It visually highlighted the ship categorized by an…
Descriptors: Intention, Psychological Patterns, Identification, Automation
Holmes, Langdon; Crossley, Scott; Sikka, Harshvardhan; Morris, Wesley – Information and Learning Sciences, 2023
Purpose: This study aims to report on an automatic deidentification system for labeling and obfuscating personally identifiable information (PII) in student-generated text. Design/methodology/approach: The authors evaluate the performance of their deidentification system on two data sets of student-generated text. Each data set was human-annotated…
Descriptors: Open Source Technology, Automation, Identification, Confidentiality
Alessia Rosa; Claudia Chellini – Journal of Media Literacy Education, 2025
Representations of diversity and otherness in cartoons offer metaphors for identity that can affect children's perceptions and attitudes towards the potential and challenges associated with various forms of disability. This contribution analyses a corpus of animations made up of feature films, series, and short films with a focus on how disability…
Descriptors: Cartoons, Films, Attitudes toward Disabilities, Physical Disabilities
Ishtiaque Fazlul; Cory Koedel; Eric Parsons – Educational Evaluation and Policy Analysis, 2025
Measures of student disadvantage--or risk--are critical components of equity-focused education policies. However, the risk measures used in contemporary policies have significant limitations, and despite continued advances in data infrastructure and analytic capacity, there has been little innovation in these measures for decades. We develop a new…
Descriptors: At Risk Students, Public Schools, Identification, Academic Achievement
Peer reviewedMegan N. Imundo; Maria Goldshtein; Micah Watanabe; Jiachen Gong; Nicole Crosby; Tracy Arner; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2025
Academic Status Reports (ASRs) are submitted by an instructor to indicate that a student is succeeding in the course or, more commonly, that the instructor is concerned about their progress or participation in the course (e.g., not attending class or not submitting assignments). ASR notifications are sent to students and may also be shared with…
Descriptors: Undergraduate Students, Academic Achievement, Identification, Early Intervention
R. K. Kapila Vani; P. Jayashree – Education and Information Technologies, 2025
Emotions of learners are fundamental and significant in e-learning as they encourage learning. Machine learning models are presented in the literature to look at how emotions may affect e-learning results that are improved and optimized. Nevertheless, the models that have been suggested so far are appropriate for offline mode, whereby data for…
Descriptors: Electronic Learning, Psychological Patterns, Artificial Intelligence, Models
Katharine M. Bailey; Nancie Im-Bolter – Learning Disability Quarterly, 2025
Children with specific learning disorder (SLD) have poor academic skills, but they also experience difficulties with their peers, including an inability to recognize interpersonal conflict, infer emotion, and resolve social conflict. In addition, children with SLD are known to have problems with language. The importance of language to social…
Descriptors: Cognitive Processes, Learning Disabilities, Social Cognition, Language Acquisition
Promoting Equity for Multilingual Learners with Disabilities. Disability, Culture, and Equity Series
Sara E. N. Kangas – Teachers College Press, 2025
This book examines the nature of equity for one of the most vulnerable populations of K-12 students--multilingual learners (MLs) with disabilities. Drawing from a rich array of research and experiences as a teacher educator and policy consultant, the author demonstrates how MLs with disabilities encounter inequities in predictable, repeated ways…
Descriptors: Equal Education, Bilingual Students, Students with Disabilities, School Policy
