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Salvatore G. Garofalo – Journal of Science Education and Technology, 2025
The initial learning experience is a critical opportunity to support conceptual understanding of abstract STEM concepts. Although hands-on activities and physical three-dimensional models are beneficial, they are seldom utilized and are replaced increasingly by digital simulations and laboratory exercises presented on touchscreen tablet computers.…
Descriptors: High School Freshmen, Science Instruction, Chemistry, Molecular Structure
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Houssam El Aouifi; Mohamed El Hajji; Youssef Es-Saady – Education and Information Technologies, 2024
Dropout refers to the phenomenon of students leaving school before completing their degree or program of study. Dropout is a major concern for educational institutions, as it affects not only the students themselves but also the institutions' reputation and funding. Dropout can occur for a variety of reasons, including academic, financial,…
Descriptors: At Risk Students, Potential Dropouts, Identification, Influences
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Ashima Kukkar; Rajni Mohana; Aman Sharma; Anand Nayyar – Education and Information Technologies, 2024
In the profession of education, predicting students' academic success is an essential responsibility. This study introduces a novel methodology for predicting students' pass or fail outcome in certain courses. The system utilises academic, demographic, emotional, and VLE sequence information of students. Traditional prediction methods often…
Descriptors: Predictor Variables, Academic Achievement, Pass Fail Grading, Long Term Memory
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Yueran Yang; Janice L. Burke; Justice Healy – Cognitive Research: Principles and Implications, 2025
"How do witnesses make identification decisions when viewing a lineup?" Understanding the witness decision-making process is essential for researchers to develop methods that can reduce mistaken identifications and improve lineup practices. Yet, the inclusion of fillers has posed a pivotal challenge to this task because the traditional…
Descriptors: Audiences, Audience Response, Identification, Decision Making
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Emiko Tsutsumi; Yiming Guo; Ryo Kinoshita; Maomi Ueno – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing (KT), the task of tracking the knowledge state of a student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines item response theory (IRT) with a deep learning method, provides superior performance. It can express the abilities of each student…
Descriptors: Item Response Theory, Academic Ability, Intelligent Tutoring Systems, Artificial Intelligence
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Michael A. Levine; Huan Chen; Ericka L. Wodka; Brian S. Caffo; Joshua B. Ewen – Journal of Autism and Developmental Disorders, 2025
Background: The Wechsler Intelligence Scale for Children (WISC) employs a hierarchical model of general intelligence in which index scores separate out different clinically-relevant aspects of intelligence; the test is designed such that index scores are statistically independent from one another within the normative sample. Whether or not the…
Descriptors: Autism Spectrum Disorders, Intelligence, Vertical Organization, Models
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Signy Wegener; Anne Castles; Elisabeth Beyersmann; Kate Nation; Hua-Chen Wang; Erik D. Reichle – Reading Research Quarterly, 2025
Spreading out study opportunities over time improves the retention of verbal material compared to consecutive study, yet little is known about the influence of temporal spacing on orthographic learning specifically. The current study addressed four questions: (1) do readers' eye movements during orthographic learning differ under spaced and massed…
Descriptors: Eye Movements, Simulation, Intervals, Orthographic Symbols
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Meng Cao; Philip I. Pavlik Jr.; Wei Chu; Liang Zhang – International Educational Data Mining Society, 2024
In category learning, a growing body of literature has increasingly focused on exploring the impacts of interleaving in contrast to blocking. The sequential attention hypothesis posits that interleaving draws attention to the differences between categories while blocking directs attention toward similarities within categories [4, 5]. Although a…
Descriptors: Attention, Algorithms, Artificial Intelligence, Classification
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Yicong Zheng; Aike Shi; Xiaonan L. Liu – npj Science of Learning, 2024
This Perspective article expands on a working memory-dependent dual-process model, originally proposed by Zheng et al., to elucidate individual differences in the testing effect. This model posits that the testing effect comprises two processes: retrieval-attempt and post-retrieval re-encoding. We substantiate this model with empirical evidence…
Descriptors: Short Term Memory, Models, Individual Differences, Testing
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Rong, Wenge; Xu, Tianfan; Sun, Zhiwei; Sun, Zian; Ouyang, Yuanxin; Xiong, Zhang – IEEE Transactions on Education, 2023
Contribution: In this study, an object tuple model has been proposed, and a quasi-experimental study on its usage in an introductory programming language course has been reported. This work can be adopted by all C language teachers and students in learning pointer and array-related concepts. Background: C language has been extensively employed in…
Descriptors: Models, Introductory Courses, Programming, Computer Science Education
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Julia Ericson; Torkel Klingberg – npj Science of Learning, 2023
A key goal in cognitive training research is understanding whether cognitive training enhances general cognitive capacity or provides only task-specific improvements. Here, we developed a quantitative model for describing the temporal dynamics of these two processes. We analyzed data from 1300 children enrolled in an 8 week working memory training…
Descriptors: Cognitive Processes, Training, Children, Short Term Memory
Peng Peng; H. Lee Swanson – Grantee Submission, 2022
Converging evidence suggests that traditional domain-general working memory (WM) training does not have reliable far-transfer effects, but produces reliable, modest near-transfer effects on structurally similar untrained tasks. Given the critical role of WM in academic development, WM training that incorporates task-specific features may maximize…
Descriptors: Short Term Memory, Academic Achievement, Outcomes of Education, Models
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Strickland, Luke; Heathcote, Andrew; Humphreys, Michael S.; Loft, Shayne – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
Event-based prospective memory (PM) tasks require individuals to remember to perform a previously planned action when they encounter a specific event. Often, the natural environments in which PM tasks occur are embedded are constantly changing, requiring humans to adapt by learning. We examine one such adaptation by integrating PM target learning…
Descriptors: Memory, Models, Cognitive Processes, Accuracy
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Dave Hewitt – For the Learning of Mathematics, 2024
The author has been influenced throughout his time in mathematics education by the work of Caleb Gattegno. Gattegno made extensive use of the word awareness whereas much educational literature from a psychological perspective talks about memory (for example, Justicia-Galiano, MartÌn-Puga, Linares & Pelegrina, 2017). This has, amongst other…
Descriptors: Mathematics Instruction, Teaching Methods, Memory, Mathematics Education
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Michelle L. Rizzella; Edward J. O'Brien – Discourse Processes: A Multidisciplinary Journal, 2024
We examined the impact of prospective information on the processing of information occurring within the present timeline of narrative stories. Participants read target sentences that were consistent with events occurring within a protagonist's present timeline but inconsistent with events in the protagonist's future. When prospective information…
Descriptors: Information Literacy, Information Processing, Sentences, Memory
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