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Showing 1 to 15 of 16 results Save | Export
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Abdelmadjid Benmachiche; Abdelhadi Sahia; Soundes Oumaima Boufaida; Khadija Rais; Makhlouf Derdour; Faiz Maazouzi – Education and Information Technologies, 2025
In the context of massive open online courses (MOOCs), searching and retrieving information can be challenging because there is a huge amount of unstructured content, which creates a problem and makes it difficult for users to quickly find relevant lessons or resources. As a result, learners and teachers face significant barriers to accessing the…
Descriptors: MOOCs, Natural Language Processing, Artificial Intelligence, Search Engines
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Alexis Lebis; Jérémie Humeau; Anthony Fleury; Flavien Lucas; Mathieu Vermeulen – International Journal of Artificial Intelligence in Education, 2024
The personalization of curriculum plays a pivotal role in supporting students in achieving their unique learning goals. In recent years, researchers have dedicated efforts to address the challenge of personalizing curriculum through diverse techniques and approaches. However, it is crucial to acknowledge the phenomenon of student forgetting, as…
Descriptors: Individualized Instruction, Curriculum Development, Curriculum Implementation, Memory
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Adil Baqach; Amal Battou – Education and Information Technologies, 2024
Nowadays, e-learning is a significant learning option, especially in light of the COVID-19 pandemic. However, it is a very challenging task because, in online courses, tutors have no direct interaction with students, which causes most of them to lose interest and ultimately drop out of their studies. In regular classes, teachers can see how each…
Descriptors: MOOCs, Student Attitudes, Student Reaction, Tutors
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Skulmowski, Alexander – Educational Psychology Review, 2023
This review is aimed at synthesizing current findings concerning technology-based cognitive offloading and the associated effects on learning and memory. While cognitive externalization (i.e., using the environment to outsource mental computation) is a highly useful technique in various problem-solving tasks, a growing body of research suggests…
Descriptors: Mental Computation, Learning Processes, Memory, Problem Solving
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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
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Sarsa, Sami; Leinonen, Juho; Hellas, Arto – Journal of Educational Data Mining, 2022
New knowledge tracing models are continuously being proposed, even at a pace where state-of-the-art models cannot be compared with each other at the time of publication. This leads to a situation where ranking models is hard, and the underlying reasons of the models' performance -- be it architectural choices, hyperparameter tuning, performance…
Descriptors: Learning Processes, Artificial Intelligence, Intelligent Tutoring Systems, Memory
Shafee Mohammed – ProQuest LLC, 2020
Predicting learning and human behavior in general is a challenging endeavor. Machine learning driven predictive modeling have been an increasingly popular means to understand disparities in student performance. With more than a handful of approaches to predictive modeling, the current literature of predicting learning is plagued with issues such…
Descriptors: Prediction, Short Term Memory, Blended Learning, Student Behavior
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Knabe, Melina L.; Vlach, Haley A. – First Language, 2020
Ambridge argues that there is widespread agreement among child language researchers that learners store linguistic abstractions. In this commentary the authors first argue that this assumption is incorrect; anti-representationalist/exemplar views are pervasive in theories of child language. Next, the authors outline what has been learned from this…
Descriptors: Child Language, Children, Language Acquisition, Models
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Musso, Mariel F.; Kyndt, Eva; Cascallar, Eduardo C.; Dochy, Filip – Frontline Learning Research, 2013
Many studies have explored the contribution of different factors from diverse theoretical perspectives to the explanation of academic performance. These factors have been identified as having important implications not only for the study of learning processes, but also as tools for improving curriculum designs, tutorial systems, and students'…
Descriptors: Prediction, Academic Achievement, Networks, Learning Processes
Clancey, W. J. – 1990
A major error in cognitive science has been to suppose that the meaning of a representation in the mind is known prior to its production. Representations are inherently perceptual--constructed by a perceptual process and given meaning by subsequent perception of them. The person perceiving the representation determines what it means. This premise…
Descriptors: Artificial Intelligence, Cognitive Processes, Cognitive Structures, Learning Processes
Norman, Donald A. – 1979
The studies summarized in this report on instructional theory and computer based tutorial systems were directed at two aspects of the study of learning and instruction: the theoretical understanding of human memory and the development of intelligent interactive computer systems for instruction. Two major computer-based tutorial systems developed…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Learning Processes, Memory
Norman, Donald A. – 1979
Cognitive science is a science of intelligence, of knowledge and its uses. Research is psychological theory follows four major themes: Perception, Attention, Memory, and Performance. Only when the range of cognitive mechanisms and functions is known, can possible theoretical approaches characterizing human thought and cognition be distinguished.…
Descriptors: Artificial Intelligence, Biological Influences, Cognitive Processes, Intellectual Development
Thorndyke, Perry W. – 1977
A framework for viewing human text comprehension, memory, and recall is presented that assumes patterns of abstract conceptual relations are used to guide processing. These patterns consist of clusters of knowledge that encode prototypical co-occurrences of situations and events in narrative texts. The patterns are assumed to be a part of a…
Descriptors: Artificial Intelligence, Cognitive Processes, Information Processing, Learning Processes
Allison, Dennis J. – 1984
A theory of memory is introduced, which seeks to respond to the shortcomings of existing theories based on metaphors. Memory is presented as a mechanism, a comparison process in which information held in some form of immediate storage (whether based on perception or previous cognition or both) is compared to previously stored long-term storage.…
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Science, Computers
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Waldrop, M. Mitchell – Science, 1988
Describes an artificial intelligence system known as SOAR that approximates a theory of human cognition. Discusses cognition as problem solving, working memory, long term memory, autonomy and adaptability, and learning from experience as they relate to artificial intelligence generally and to SOAR specifically. Highlights the status of the…
Descriptors: Artificial Intelligence, Cognitive Processes, Cognitive Psychology, Cognitive Structures
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