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Ziyan Yang; Jia Hu; Shaochun Zhong; Lan Yang; Geyong Min – Education and Information Technologies, 2025
Intelligent technology plays a pivotal role in revolutionizing learning assessments, overcoming the constraints of traditional assessment methods and driving educational innovation. Knowledge tracing (KT) emerges as a critical component for assessing students' learning states and forecasting their future performance. However, existing graph-based…
Descriptors: Learning Processes, Artificial Intelligence, Graphs, Concept Mapping
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Junfeng Man; Rongke Zeng; Xiangyang He; Hua Jiang – Knowledge Management & E-Learning, 2024
At present, the widespread use of online education platforms has attracted the attention of more and more people. The application of AI technology in online education platform makes multidimensional evaluation of students' ability become the trend of intelligent education in the future. Currently, most existing studies are based on traditional…
Descriptors: Cognitive Ability, Student Evaluation, Algorithms, Learning Processes
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Ernest Opoku; Dominic Owusu; Francis Arthur; Iddrisu Salifu; Emmanuel Quayson; Eric Boateng; Francis Obeng Gyedu; Stanley Asare-Bediako; Emmanuel Rungson Attom; Solomon Adjatey Tetteh; Sharon Abam Nortey; Ayishatu Ameen – Discover Education, 2025
The evolving landscape of higher education requires a better understanding of students' cognitive strengths, especially in complex disciplines such as Economics where multiple approaches to problem solving are essential. This study explored students' multiple intelligences (MI) approach to learning Economics and examined gender differences in the…
Descriptors: College Students, Profiles, Multiple Intelligences, Economics Education
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Il Do Ha – Measurement: Interdisciplinary Research and Perspectives, 2024
Recently, deep learning has become a pervasive tool in prediction problems for structured and/or unstructured big data in various areas including science and engineering. In particular, deep neural network models (i.e. a basic core model of deep learning) can be viewed as an extension of statistical models by going through the incorporation of…
Descriptors: Artificial Intelligence, Statistical Analysis, Models, Algorithms
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Zhennan Sun; Mingyong Pang; Yi Zhang – Education and Information Technologies, 2025
The evolution of individual and global learning preferences is influenced by correlation factors. This study introduces a novel evolutionary modeling approach to observe and analyze factors that affect the evolution of learning preferences. The influencing factors considered in this study are closely interwoven with the underlying personality of…
Descriptors: Learning Analytics, Learning Processes, Preferences, Student Characteristics
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Hei-Chia Wang; Yu-Hung Chiang; I-Fan Chen – Education and Information Technologies, 2024
Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…
Descriptors: Natural Language Processing, Test Construction, Test Items, Models
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Jyoti Sharma; B. Biswal; Pankaj Tyagi; Shobha Bagai – Gifted and Talented International, 2024
Academically gifted students or high potential learners don't feel challenged in regular classrooms. Teachers in schools are also not quipped with pedagogical interventions to meet the advanced learning needs of gifted students. Mentoring is considered an effective method to guide, motivate and optimize learning abilities of gifted students. The…
Descriptors: Mentors, Academically Gifted, Program Development, Science Education
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Luis Medina-Gual; José-Luis Parejo – European Journal of Education, 2025
The present research explores AI's impact on education among Mexican undergraduate students through a non-experimental, correlational, cross-sectional study. A validated public questionnaire was distributed to 840 students via Google Forms from February to May 2024. Analysis revealed significant AI exposure and use patterns, primarily influenced…
Descriptors: Artificial Intelligence, Teaching Methods, Ethics, Learning Processes
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Zhaozhen Xu; Amelia Howarth; Nicole Briggs; Nello Cristianini – International Journal of Artificial Intelligence in Education, 2024
Questions have a critical role in learning and teaching. People ask questions to obtain information and express interest in ideas. The Bristol scientific centre "We The Curious" launched "Project What If" in 2017 to inspire residents of Bristol to record their questions and pursue their curiosities. Researching these questions…
Descriptors: Questioning Techniques, Science Teaching Centers, Museums, Science Education
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Swarupa Asish Dash; S. Vijayakumar Bharathi – Journal of Educators Online, 2025
This study delves into the integration of artificial intelligence (AI) with Vedic pedagogy in management education, aiming to bridge the gap between traditional educational frameworks and contemporary technological advancements. By analyzing the application of AI to augment learning processes such as listening, introspection, critical analysis,…
Descriptors: Artificial Intelligence, Teaching Methods, Management Development, Technology Uses in Education
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Radek Pelánek – International Journal of Artificial Intelligence in Education, 2025
While the potential of personalized education has long been emphasized, the practical adoption of adaptive learning environments has been relatively slow. Discussion about underlying reasons for this disparity often centers on factors such as usability, the role of teachers, or privacy concerns. Although these considerations are important, I argue…
Descriptors: Educational Environment, Modeling (Psychology), Barriers, Adjustment (to Environment)
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Hyunkyung Chee; Solmoe Ahn; Jihyun Lee – British Journal of Educational Technology, 2025
This study aims to develop a comprehensive competency framework for artificial intelligence (AI) literacy, delineating essential competencies and sub-competencies. This framework and its potential variations, tailored to different learner groups (by educational level and discipline), can serve as a crucial reference for designing and implementing…
Descriptors: Competence, Digital Literacy, Artificial Intelligence, Technology Uses in Education
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Inna Artemova – Online Learning, 2025
While existing literature documents the benefits and concerns of Generative Artificial Intelligence (GAI) for learning processes, it largely overlooks fundamental learning theories such as Cognitive Load Theory, Constructivism, Activity Theory, and Bloom's Taxonomy. This study employs a scoping review methodology to identify current research gaps…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Research, Risk
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George Veletsianos; Shandell Houlden; Nicole Johnson – TechTrends: Linking Research and Practice to Improve Learning, 2024
Much of the literature on artificial intelligence (AI) in education imagines AI as a tool in the service of teaching and learning. Is such a one-way relationship all that exists between AI and learners? In this paper we report on a thematic analysis of 92 participant responses to a story completion exercise which asked them to describe a classroom…
Descriptors: Artificial Intelligence, Technology Uses in Education, Man Machine Systems, Interaction
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Glenn Hardaker; Liyana Eliza Glenn – International Journal of Information and Learning Technology, 2025
Purpose: The purpose of this systematic literature review is to identify the antecedents that have enabled the adoption of artificial intelligence (AI) in Higher Education (HE) institutions at both a macro and micro level. The term adoption is in reference to the diffusion of technology that is actively chosen for use by the targeted demographic.…
Descriptors: Artificial Intelligence, Individualized Instruction, Technology Uses in Education, Higher Education
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