结构方程模型与神经网络混合方法研究学生对E-LMS的接受程度

IF 0.4 Q4 EDUCATION & EDUCATIONAL RESEARCH International Journal of Learning Technology Pub Date : 2023-01-01 DOI:10.1504/ijlt.2023.10059508
Shard ., Devesh Kumar, Sapna Koul
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A Hybrid Structural Equation Modelling and Neural Network Approach to Examine Stufents' Acceptance of E-LMS
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来源期刊
International Journal of Learning Technology
International Journal of Learning Technology EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
1.20
自引率
16.70%
发文量
9
期刊介绍: IJLT is an international, refereed, scholarly journal providing an interdisciplinary forum for the presentation and discussion of important ideas, concepts, and exemplars that can deeply influence the role of learning technologies in learning and instruction. This unique and dynamic journal focuses on the epistemological thrust of learning vis-à-vis instruction and the technologies and tools that support the process. IJLT publishes papers related to theoretical foundations, design and implementation, and effectiveness and impact issues related to learning technologies. Topics covered include: -Communities of learners (practice), computer-mediated communication -[Social] constructivism, computer-supported collaborative learning -Cognitive tools, intelligent agents, semantic web -Distributed/intelligent learning/tutoring, multimedia/interactive learning environments -Virtual reality environments, human-computer interface issues -Learning objects for personalised learning, building learning communities -Technology-facilitated learning in complex domains -Learning technology systems'' evaluation, technological standardisation -Simulation-supported learning/instruction -Learning technology in education and commerce -Disciplinary-related inquiry, e.g., learning technologies for science inquiry -MOOCs, social media and cloud computing in e-learning -Data analytics and big data in education -E-learning evaluation and content; e-portfolios -Smart education; internet of things/technology adoption and diffusion for learning
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