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Maurício D. Martins; Zoe Bergmann; Elena Leonova; Roberta Bianco; Daniela Sammler; Arno Villringer – Cognitive Science, 2025
Recursive hierarchical embedding allows humans to generate multiple hierarchical levels using simple rules. We can acquire recursion from exposure to linguistic and visual examples, but only develop the ability to understand "multiple-level" structures like "[[second] red] ball]" after mastering "same-level"…
Descriptors: Psychomotor Skills, Adults, Adult Learning, Learning Processes
Gabriel J. Cler; Samantha Bartolo; Jiwon Kim; Anna Nolan; Sophia Banel – Journal of Speech, Language, and Hearing Research, 2024
Purpose: Developmental language disorder (DLD) is a neurodevelopmental disorder that impacts approximately 7% of the population and is characterized by unexplained deficits in expressive and/or receptive components of language. A common procedural learning task, serial reaction time (SRT), has been used to develop models of the basis of DLD.…
Descriptors: Adult Learning, Language Impairments, Sequential Learning, Neurodevelopmental Disorders
Isaac N. Treves; Jonathan Cannon; Eren Shin; Cindy E. Li; Lindsay Bungert; Amanda O'Brien; Annie Cardinaux; Pawan Sinha; John D. E. Gabrieli – Journal of Autism and Developmental Disorders, 2024
Some theories have proposed that autistic individuals have difficulty learning predictive relationships. We tested this hypothesis using a serial reaction time task in which participants learned to predict the locations of a repeating sequence of target locations. We conducted a large-sample online study with 61 autistic and 71 neurotypical…
Descriptors: Autism Spectrum Disorders, Adults, Learning Processes, Visual Perception
Jinnie Shin; Bowen Wang; Wallace N. Pinto Junior; Mark J. Gierl – Large-scale Assessments in Education, 2024
The benefits of incorporating process information in a large-scale assessment with the complex micro-level evidence from the examinees (i.e., process log data) are well documented in the research across large-scale assessments and learning analytics. This study introduces a deep-learning-based approach to predictive modeling of the examinee's…
Descriptors: Prediction, Models, Problem Solving, Performance

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