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Yingjie Liu; Qinglong Zhan; Wenping Zhao – Interactive Learning Environments, 2024
This paper presents a systematic review of the application models, affects, and performance outcomes of VR/AR in vocational education. The analysis is based on journal articles retrieved from renowned databases such as Web of Science, Scopus, and EBSCO, spanning from January 2000 to January 2022. It highlights the pedagogical value of VR/AR in…
Descriptors: Computer Simulation, Artificial Intelligence, Vocational Education, Technology Uses in Education
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Cömert, Zeynep; Samur, Yavuz – Interactive Learning Environments, 2023
Almost in every aspect of life, classification and categorization make it easier for humans to analyze complex structures and systems. In games, the classification of the players based on their demographics, behaviors, expectations and preferences of the game is important to increase players' motivation and satisfaction. Likewise, knowing the…
Descriptors: Classification, Student Characteristics, Models, Student Motivation
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Xiaoxuan Fang; Davy Tsz Kit Ng; Jac Ka Lok Leung; Huixuan Xu – Interactive Learning Environments, 2024
The Attention, Relevance, Confidence, and Satisfaction or ARCS model is an effective motivational model that has been widely accepted by education practitioners. Literature on the ARCS model has focused primarily on aspects of educational settings, research methods, and outcomes. However, few studies have addressed the applications of the ARCS…
Descriptors: Attention, Relevance (Education), Self Esteem, Student Satisfaction
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García-Murillo, Gabriel; Novoa-Hernández, Pavel; Rodri?uez, Rocío Serrano – Interactive Learning Environments, 2023
In this study, we report on a Systematic Mapping Study (SMS) for the application of technology acceptance models to Moodle under the prism of latent variable modeling. Based on an automatic search including primary studies from journals, conferences, and book chapters during 2001 to 2019, 41 primary were selected. We aim to contribute to a better…
Descriptors: Learning Management Systems, College Students, Technology Uses in Education, Educational Research
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Umer, Rahila; Susnjak, Teo; Mathrani, Anuradha; Suriadi, Lim – Interactive Learning Environments, 2023
Predictive models on students' academic performance can be built by using historical data for modelling students' learning behaviour. Such models can be employed in educational settings to determine how new students will perform and in predicting whether these students should be classed as at-risk of failing a course. Stakeholders can use…
Descriptors: Prediction, Student Behavior, Models, Academic Achievement
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Aslina Saad; Suhaila Zainudin – Interactive Learning Environments, 2024
This study delves into the integration of Project-Based Learning (PBL) and Computational Thinking (CT) to enhance 21st century learning. Through a Narrative Literature Review (NLR), pivotal strategies for effective implementation are identified. These include fostering collaborative pedagogy, employing visualization tools, embracing diverse…
Descriptors: Active Learning, Student Projects, Teaching Methods, Computation
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Liu, Chenchen; Hwang, Gwo-Jen – Interactive Learning Environments, 2023
The use of touchscreen mobile devices in early childhood education has gained considerable attention. Several studies have been conducted to investigate the impacts of touchscreen mobile devices on children's cognitive and affective development. Researchers have further indicated the need to probe in which contexts children can learn effectively…
Descriptors: Handheld Devices, Computer Oriented Programs, Technology Uses in Education, Early Childhood Education
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Mavroudi, Anna; Giannakos, Michail; Krogstie, John – Interactive Learning Environments, 2018
Learning Analytics (LA) and adaptive learning are inextricably linked since they both foster technology-supported learner-centred education. This study identifies developments focusing on their interplay and emphasises insufficiently investigated directions which display a higher innovation potential. Twenty-one peer-reviewed studies are…
Descriptors: Student Centered Learning, Evidence Based Practice, Technology Uses in Education, Student Diversity
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Laureano-Cruces, Ana Lilia; Ramirez-Rodriguez, Javier; de Arriaga, Fernando; Escarela-Perez, Rafael – Interactive Learning Environments, 2006
Intelligent learning systems (ILSs) have evolved in the last few years basically because of influences received from multi-agent architectures (MAs). Conflict resolution among agents has been a very important problem for multi-agent systems, with specific features in the case of ILSs. The literature shows that ILSs with cognitive or pedagogical…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Conflict Resolution, Cognitive Style
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Dillenbourg, Pierre; Self, John – Interactive Learning Environments, 1992
Presents a conceptual framework and notation for learner modelling in intelligent tutoring systems based on the computational distinction between behavior, behavioral knowledge, and conceptual knowledge and between the system, the learner, and the system's representation of the learner. Approaches to learner modelling based on a review of the…
Descriptors: Behavior, Error Patterns, Learning Processes, Literature Reviews
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Mitchell, Christine M.; Govindaraj, T. – Interactive Learning Environments, 1990
Discusses the use of intelligent tutoring systems as opposed to traditional on-the-job training for training operators of complex dynamic systems and describes the computer architecture for a system for operators of a NASA (National Aeronautics and Space Administration) satellite control system. An experimental evaluation with college students is…
Descriptors: Analysis of Variance, Artificial Intelligence, Computer Assisted Instruction, Computer Simulation