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Faster Implicit Motor Sequence Learning of New Sequences Compatible in Terms of Movement Transitions
Susanne Dyck; Christian Klaes – npj Science of Learning, 2025
New information that is compatible with pre-existing knowledge can be learned faster. Such schema memory effect has been reported in declarative memory and in explicit motor sequence learning (MSL). Here, we investigated if sequences of key presses that were compatible to previously trained ones, could be learned faster in an implicit MSL task.…
Descriptors: Learning Processes, Psychomotor Skills, Sequential Learning, Memory
Benjamin M. Rottman; Yiwen Zhang – Cognitive Research: Principles and Implications, 2025
Being able to notice that a cause-effect relation is getting stronger or weaker is important for adapting to one's environment and deciding how to use the cause in the future. We conducted an experiment in which participants learned about a cause-effect relation that either got stronger or weaker over time. The experiment was conducted with a…
Descriptors: Causal Models, Memory, Learning Processes, Time
Laura Ordonez Magro; Leonardo Pinto Arata; Joël Fagot; Jonathan Grainger; Arnaud Rey – Cognitive Science, 2025
Statistical learning allows us to implicitly create memory traces of recurring sequential patterns appearing in our environment. Here, we study the dynamics of how these sequential memory traces develop in a species of nonhuman primates (i.e., Guinea baboons, "Papio papio") that, unlike humans, cannot use language and verbal recoding…
Descriptors: Memory, Sequential Learning, Animals, Repetition
Soonri Choi; Dongsik Kim; Jihoon Song – Educational Technology Research and Development, 2025
Despite the efforts of instructional design (ID) to solve real-life problems, it remains challenging to adapt and be flexible in such situations. In particular, problems that require simultaneous knowledge of multiple domains and contexts are more challenging to solve because real-life problems do not reconstruct the learned experience. This is…
Descriptors: Expertise, Instructional Design, Problem Solving, Cognitive Processes
Jesper Dannath; Alina Deriyeva; Benjamin Paaßen – International Educational Data Mining Society, 2025
Research on the effectiveness of Intelligent Tutoring Systems (ITSs) suggests that automatic hint generation has the best effect on learning outcomes when hints are provided on the level of intermediate steps. However, ITSs for programming tasks face the challenge to decide on the granularity of steps for feedback, since it is not a priori clear…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Undergraduate Students
Jia Yang; Fang-Fang Yan; Tingting Wang; Zile Wang; Qingshang Ma; Jinmei Xiao; Xianyuan Yang; Zhong-Lin Lu; Chang-Bing Huang – npj Science of Learning, 2025
Learning to perform multiple tasks robustly is a crucial facet of human intelligence, yet its mechanisms remain elusive. Here, we formulated four hypotheses concerning task interactions and investigated them by analyzing training sequence effects through a continual learning framework. Forty-nine subjects learned seven tasks sequentially, each of…
Descriptors: Sequential Learning, Interference (Learning), Prior Learning, Perceptual Motor Learning
Felix Krieglstein; Maik Beege; Lukas Wesenberg; Günter Daniel Rey; Sascha Schneider – Educational Psychology Review, 2025
In research practice, it is common to measure cognitive load after learning using self-report scales. This approach can be considered risky because it is unclear on what basis learners assess cognitive load, particularly when the learning material contains varying levels of complexity. This raises questions that have yet to be answered by…
Descriptors: Cognitive Processes, Difficulty Level, Instructional Materials, Problem Solving
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
Sabina Pauen; Jule Bach – Social Development, 2025
Imitation plays a crucial role in early social learning. Numerous studies indicate that young children copy even actions that are clearly irrelevant for goal achievement--a phenomenon called overimitation (OI). The present study tested whether this finding can be generalized to different forms of faithful nonsense imitation presented in different…
Descriptors: Imitation, Young Children, Child Behavior, Behavior Change
Gaia Olivo; Jonas Persson; Martina Hedenius – npj Science of Learning, 2024
Developmental dyslexia (DD) is defined as difficulties in learning to read even with normal intelligence and adequate educational guidance. Deficits in implicit sequence learning (ISL) abilities have been reported in children with DD. We investigated brain plasticity in a group of 17 children with DD, compared with 18 typically developing (TD)…
Descriptors: Dyslexia, Brain, Children, Training
Guoqian Luo; Hengnian Gu; Xiaoxiao Dong; Dongdai Zhou – Education and Information Technologies, 2025
In the realm of e-learning, supporting personalized learning effectively necessitates recommending sequences of learning items that maximize learning efficiency while minimizing cognitive load, all tailored to the learner's goals. These recommendations must account for the prerequisite relationships among learning items and the learner's…
Descriptors: Electronic Learning, Individualized Instruction, Sequential Learning, Learning Processes
Stephen Ferrigno; Samuel J. Cheyette; Susan Carey – Cognitive Science, 2025
Complex sequences are ubiquitous in human mental life, structuring representations within many different cognitive domains--natural language, music, mathematics, and logic, to name a few. However, the representational and computational machinery used to learn abstract grammars and process complex sequences is unknown. Here, we used an artificial…
Descriptors: Sequential Learning, Cognitive Processes, Knowledge Representation, Training
Roman Abel; Anique de Bruin; Erdem Onan; Julian Roelle – Educational Psychology Review, 2024
Distinguishing easily confusable categories requires learners to detect their predictive differences. Interleaved sequences -- switching between categories -- help learners to detect such differences. Nonetheless, learners prefer to block -- switching within a category -- to detect commonalities. Across two 2 × 2-factorial experiments, we…
Descriptors: Sequential Learning, Learning Strategies, Interference (Learning), Classification
Fabian Tomaschek; Michael Ramscar; Jessie S. Nixon – Cognitive Science, 2024
Sequence learning is fundamental to a wide range of cognitive functions. Explaining how sequences--and the relations between the elements they comprise--are learned is a fundamental challenge to cognitive science. However, although hundreds of articles addressing this question are published each year, the actual learning mechanisms involved in the…
Descriptors: Sequential Learning, Learning Processes, Serial Learning, Executive Function
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

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