基于CiteSpace的多模态学习分析研究评述

A Review of Multimodal Learning Analytics Research Based on CiteSpace

摘要: 为厘清多模态学习分析领域的历史演进、研究现状与前沿动态，本研究运用CiteSpace工具，对中国知网(CNKI)与Web of Science (WOS)数据库中2014年~2024年的核心期刊文献开展可视化分析，分析内容涵盖年度发文量、机构共现、关键词共现、关键词聚类以及关键词时间线等维度，研究发现近年该主题下在技术驱动下快速发展，总体呈现出多学科交叉、技术驱动创新和多角度实际应用的趋势。未来相关研究将伴随人工智能技术发展，突破跨学科理论融合与异构数据整合瓶颈，提升教师技术应用与教学设计能力，推动复杂场景的适应性落地，我国亟待构建以领军学者为核心的跨机构合作共同体，驱动本土化理论创新与实践应用，助力教育数字化转型发展。

Abstract: To clarify the historical evolution, research status and cutting-edge trends in the field of multimodal learning analysis, this study utilized the CiteSpace tool to conduct a visual analysis of the core journal literature from 2014 to 2024 in the databases of China National Knowledge Infrastructure (CNKI) and Web of Science (WOS). The analysis covers dimensions such as the annual number of published articles, co-occurrence of institutions, co-occurrence of keywords, keyword clustering, and keyword timelines. The research finds that in recent years, this theme has developed rapidly driven by technology, generally showing a trend of multi-disciplinary intersection, technology-driven innovation, and multi-angle practical application. In the future, related research will follow the development of artificial intelligence technology, break through the bottlenecks of cross-disciplinary theoretical integration and heterogeneous data integration, enhance teachers’ ability to apply technology and design teaching, promote the adaptive implementation in complex scenarios. China urgently needs to build a cross-institutional cooperative community with leading scholars at its core to drive localized theoretical innovation and practical application, and facilitate the digital transformation and development of education.