多模态智能自适应学习系统及其促进学习者在线学习参与的模式研究

ZHANG Chao, SHI Qing, TONG Mingwen
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引用次数: 0

摘要

随着人工智能领域的不断发展,多模态学习分析和智能自适应学习系统的应用也在不断发展。这一趋势有可能促进教育资源的均等化、教育方法的智能化和教育改革的现代化,以及其他好处。本研究提出了一个基于多模态数据支持的智能自适应学习系统的构建框架。它详细解释了该系统的工作原理和模式,旨在提高学习者在行为、情感和认知方面的在线参与度。本研究旨在解决智能自适应学习系统仅根据学习成果诊断学习者的学习行为的问题,以提高学习者的在线参与度,使他们能够掌握更多所需的知识,并最终获得更好的学习效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study of Multimodal Intelligent Adaptive Learning System and Its Pattern of Promoting Learners’ Online Learning Engagement
As the field of artificial intelligence continues to evolve, so too does the application of multimodal learning analysis and intelligent adaptive learning systems. This trend has the potential to promote the equalization of educational resources, the intellectualization of educational methods, and the modernization of educational reform, among other benefits. This study proposes a construction framework for an intelligent adaptive learning system that is supported by multimodal data. It provides a detailed explanation of the system’s working principles and patterns, which aim to enhance learners’ online engagement in behavior, emotion, and cognition. The study seeks to address the issue of intelligent adaptive learning systems diagnosing learners’ learning behavior based solely on learning achievement, to improve learners’ online engagement, enable them to master more required knowledge, and ultimately achieve better learning outcomes.
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