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Jesse Q. Sargent; Lauren L. Richmond; Devin M. Kellis; Maverick E. Smith; Jeffrey M. Zacks – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
Spatial memory is important for supporting the successful completion of everyday activities and is a particularly vulnerable domain in late life. Grouping items together in memory, or chunking, can improve spatial memory performance. In memory for desktop scale spaces and well-learned large-scale environments, error patterns suggest that…
Descriptors: Spatial Ability, Memory, Cognitive Processes, Aging (Individuals)
Babu Noushad; Pascal W. M. Van Gerven; Anique B. H. de Bruin – Advances in Health Sciences Education, 2024
Studying texts constitutes a significant part of student learning in health professions education. Key to learning from text is the ability to effectively monitor one's own cognitive performance and take appropriate regulatory steps for improvement. Inferential cues generated during a learning experience typically guide this monitoring process. It…
Descriptors: Metacognition, Prediction, Cues, Visual Aids
Masahiro Yamada; Omid Ansari; Ali Emami; Alireza Saberi Kakhki; Takehiro Iwatsuki – Journal of Motor Learning and Development, 2025
Motor performance has been shown to be superior when focusing on a physically farther environmental cue (external focus-far, EF-far) instead of a cue proximal to the body (EF-near). However, little is known about whether these foci affect bimanual tasks. Further, the effect of visual information on attentional focus is unclear. In the present…
Descriptors: Psychomotor Skills, Attention, Cues, Proximity
Julie Y. L. Chow; Jessica C. Lee; Peter F. Lovibond – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
People often rely on the covariation between events to infer causality. However, covariation between cues and outcomes may change over time. In the associative learning literature, extinction provides a model to study updating of causal beliefs when a previously established relationship no longer holds. Prediction error theories can explain both…
Descriptors: Beliefs, Learning Processes, Foreign Countries, Attribution Theory
Mahalakshmi Ramamurthy; Alex L. White; Jason D. Yeatman – Developmental Science, 2024
In the search for mechanisms that contribute to dyslexia, the term "attention" has been invoked to explain performance in a variety of tasks, creating confusion since all tasks do, indeed, demand "attention." Many studies lack an experimental manipulation of attention that would be necessary to determine its influence on task…
Descriptors: Children, Adolescents, Dyslexia, Spatial Ability
Hannah Sawyer; Colin Bannard; Julian Pine – Developmental Science, 2024
There is substantial evidence that children's apparent omission of grammatical morphemes in utterances such as "She play tennis" and "Mummy eating" is in fact errors of commission in which contextually licensed unmarked forms encountered in the input are reproduced in a context-blind fashion. So how do children stop making such…
Descriptors: Verbs, Computational Linguistics, Preschool Children, Grammar
Erdin Mujezinovic; Vsevolod Kapatsinski; Ruben van de Vijver – Cognitive Science, 2024
A word often expresses many different morphological functions. Which part of a word contributes to which part of the overall meaning is not always clear, which raises the question as to how such functions are learned. While linguistic studies tacitly assume the co-occurrence of cues and outcomes to suffice in learning these functions (Baer-Henney,…
Descriptors: Morphology (Languages), Phonology, Morphemes, Cues
Geoffrey Currie; Josie Currie; Sam Anderson; Johnathan Hewis – Health Education Journal, 2024
Introduction: In Australia, 54.3% of medical students are women yet they remain under-represented in stereotypical perspectives of medicine. While potentially transformative, generative artificial intelligence (genAI) has the potential for errors, misrepresentations and bias. GenAI text-to-image production could reinforce gender biases making it…
Descriptors: Gender Bias, Artificial Intelligence, Computer Software, Medical Education
Yi Gui – ProQuest LLC, 2024
This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…
Descriptors: Writing Tests, Natural Language Processing, Writing Evaluation, Scoring
Christopher Saarna – International Journal of Technology in Education, 2024
This study seeks to clarify whether teachers are able to distinguish between essays written by English L2 students or generated by ChatGPT. 47 instructors who hold experience teaching English to native speakers of Japanese in universities or other higher education institutions were tested on whether they could identify between human written essays…
Descriptors: Identification, Artificial Intelligence, Computer Software, Grammar
Tran Ngoc Quynh Phuong; Bao Trang Thi Nguyen; Thi Linh Giang Hoang; Vu Quynh Nhu Nguyen; Le Hoang Phuong Ngo – Taiwan Journal of TESOL, 2024
This article examines the use of prompt-based lexical collocations in opinion essays by Vietnamese English as a foreign language (EFL) students. Fifty second-year English majors at a Vietnamese university wrote 100 opinion essays on two topics as progress tests. The AntConc programme (Anthony, 2020) was employed to identify the frequencies of use…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Phrase Structure