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Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis
by
Halkiopoulos, Constantinos
, Gkintoni, Evgenia
in
Adaptive algorithms
/ Adaptive learning
/ Analysis
/ Artificial intelligence
/ Bias
/ Cognitive ability
/ Cognitive style
/ Computational linguistics
/ Customization
/ Distance learning
/ Education
/ Ethics
/ Language processing
/ Machine learning
/ Methods
/ Natural language interfaces
/ Neuropsychology
/ Online instruction
/ Personalized learning
/ Students
/ System effectiveness
/ Teaching methods
/ Tutoring
2024
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Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis
by
Halkiopoulos, Constantinos
, Gkintoni, Evgenia
in
Adaptive algorithms
/ Adaptive learning
/ Analysis
/ Artificial intelligence
/ Bias
/ Cognitive ability
/ Cognitive style
/ Computational linguistics
/ Customization
/ Distance learning
/ Education
/ Ethics
/ Language processing
/ Machine learning
/ Methods
/ Natural language interfaces
/ Neuropsychology
/ Online instruction
/ Personalized learning
/ Students
/ System effectiveness
/ Teaching methods
/ Tutoring
2024
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Do you wish to request the book?
Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis
by
Halkiopoulos, Constantinos
, Gkintoni, Evgenia
in
Adaptive algorithms
/ Adaptive learning
/ Analysis
/ Artificial intelligence
/ Bias
/ Cognitive ability
/ Cognitive style
/ Computational linguistics
/ Customization
/ Distance learning
/ Education
/ Ethics
/ Language processing
/ Machine learning
/ Methods
/ Natural language interfaces
/ Neuropsychology
/ Online instruction
/ Personalized learning
/ Students
/ System effectiveness
/ Teaching methods
/ Tutoring
2024
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Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis
Journal Article
Leveraging AI in E-Learning: Personalized Learning and Adaptive Assessment through Cognitive Neuropsychology—A Systematic Analysis
2024
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Overview
This paper reviews the literature on integrating AI in e-learning, from the viewpoint of cognitive neuropsychology, for Personalized Learning (PL) and Adaptive Assessment (AA). This review follows the PRISMA systematic review methodology and synthesizes the results of 85 studies that were selected from an initial pool of 818 records across several databases. The results indicate that AI can improve students’ performance, engagement, and motivation; at the same time, some challenges like bias and discrimination should be noted. The review covers the historic development of AI in education, its theoretical grounding, and its practical applications within PL and AA with high promise and ethical issues of AI-powered educational systems. Future directions are empirical validation of effectiveness and equity, development of algorithms that reduce bias, and exploration of ethical implications regarding data privacy. The review identifies the transformative potential of AI in developing personalized and adaptive learning (AL) environments, thus, it advocates continued development and exploration as a means to improve educational outcomes.
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