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Msafiri Mgambi Msambwa; Zhang Wen; Kangwa Daniel – European Journal of Education, 2025
Artificial intelligence (AI) has extensively developed, impacting different sectors of society, including higher education, and has attracted the attention of various educational stakeholders, leading to a growing number of research on its integration into education. Hence, this systematic literature review examines the impact of integrating AI…
Descriptors: Influence of Technology, Technology Uses in Education, Artificial Intelligence, Cooperative Learning
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Carl Boel; Tijs Rotsaert; Martin Valcke; Tammy Schellens – Journal of Computer Assisted Learning, 2025
Background: As immersive virtual reality (IVR) is increasingly being used by teachers worldwide, it becomes pressing to investigate how this technology can foster learning processes. Several authors have pointed to this need, as results on the effectiveness of IVR for learning are still inconclusive. Objectives: To address this gap, we first…
Descriptors: Artificial Intelligence, Computer Simulation, Learning Strategies, Middle School Students
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Lasfeto, Deddy Barnabas; Ulfa, Saida – Journal of Educational Computing Research, 2023
This study proposes an online learning model based on fuzzy expert systems to recommend learning contents that are most appropriate for facilitating more efficient learning. The process used two computer applications which are Matlab for fuzzy analysis and the learning management system Moodle platform for online learning environment. Besides,…
Descriptors: Learning Management Systems, Online Courses, Learning Processes, Computer Software
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Joel Weijia Lai; Wei Qiu; Maung Thway; Lei Zhang; Nurabidah Binti Jamil; Chit Lin Su; Samuel S. H. Ng; Fun Siong Lim – Journal of Learning Analytics, 2025
The growing use of generative AI (GenAI) has sparked discussions regarding integrating these tools into educational settings to enrich the learning experience of teachers and students. Self-regulated learning (SRL) research is pivotal in addressing this inquiry. One prevalent manifestation of GenAI is the large-language model (LLM) chatbot,…
Descriptors: Artificial Intelligence, Computer Software, Learning Analytics, Introductory Courses
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Dina Fitria Murad; Meta Amalya Dewi; Arbaiah Inn; Silvia Ayunda Murad; Noor Udin; Taufik Darwis – Journal of Educators Online, 2025
This study aims to produce a more personalized recommendation system for online learning using multicriteria in collaborative filtering and data from the Binus Online Learning repository as a knowledge base. The study uses forecasting (regression) and consists of three stages: (1) collecting data on the results of the learning process; (2) adding…
Descriptors: Electronic Learning, Data Collection, Context Effect, Learning Processes
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Ting-Chia Hsu; Ching Chang; Tien-Hsiu Jen – Interactive Learning Environments, 2024
Young learners' vocabulary learning needs interaction with language input when they are engaged in an activity. Given that AI-supported image recognition technologies offer hands-on learning in authentic contexts, and that self-regulated learning (SRL) enables learners to monitor and evaluate their learning when interacting with multi-sensory…
Descriptors: Metacognition, Multisensory Learning, Vocabulary Development, Learning Strategies
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Viberg, Olga; Kukulska-Hulme, Agnes; Peeters, Ward – International Journal of Mobile and Blended Learning, 2023
Mobile-assisted language learning (MALL) research includes examination and development of second language learners' cognitive and metacognitive self-regulated learning skills, but the affective learning component of self-regulation in this context remains largely unexplored. Support for affective learning, which is defined by learners' beliefs,…
Descriptors: Metacognition, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
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D'Mello, Sidney K. – International Journal of Artificial Intelligence in Education, 2016
There is an inextricable link between attention and learning, yet AIED systems in 2015 are largely blind to learners' attentional states. We argue that next-generation AIED systems should have the ability to monitor and dynamically (re)direct attention in order to optimize allocation of sparse attentional resources. We present some initial ideas…
Descriptors: Artificial Intelligence, Attention, Eye Movements, Attention Control
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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
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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
Lim, Kyu Yon – ProQuest LLC, 2008
The purpose of this study was to investigate the effectiveness of concept mapping strategies with different levels of generativity in terms of knowledge acquisition and knowledge representation. Also, it examined whether or not learners' self-regulated learning (SRL) skills influenced the effectiveness of concept mapping strategies with different…
Descriptors: Concept Mapping, Undergraduate Students, Knowledge Representation, Program Effectiveness
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Dietze, Stefan; Gugliotta, Alessio; Domingue, John – Journal of Interactive Media in Education, 2007
IMS Learning Design (IMS-LD) is a promising technology aimed at supporting learning processes. IMS-LD packages contain the learning process metadata as well as the learning resources. However, the allocation of resources--whether data or services--within the learning design is done manually at design-time on the basis of the subjective appraisals…
Descriptors: Learning Strategies, Learning Processes, Metadata, Resource Allocation
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Duchastel, P.; And Others – Journal of Educational Technology Systems, 1989
Discusses intelligent computer assisted instruction (ICAI) and presents various models of learning which have been proposed. Topics discussed include artificial intelligence; intelligent tutorial systems; tutorial strategies; learner control; system design; learning theory; and knowledge representation of proper and improper (i.e., incorrect)…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer System Design, Instructional Design
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Langley, Pat – Cognitive Science, 1985
Examines processes by which general but weak search methods are transformed into powerful, domain-specific search strategies by classifying types of heuristics learning that can occur and components that contribute to such learning. A learning system--SAGE.2--and its structure, behavior in different domains, and future directions are explored. (36…
Descriptors: Artificial Intelligence, Computer Software, Design, Heuristics
Plaut, David C.; And Others – 1986
This paper describes further research on a learning procedure for layered networks of deterministic, neuron-like units, described by Rumelhart et al. The units, the way they are connected, the learning procedure, and the extension to iterative networks are presented. In one experiment, a network learns a set of filters, enabling it to discriminate…
Descriptors: Artificial Intelligence, Cognitive Structures, Computer Simulation, Discrimination Learning
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