间隔效应在二语词汇习得中的研究进展及展望

Research Progress and Prospects of the Spacing Effect in Second Language Vocabulary Acquisition

摘要: 为系统梳理间隔效应在二语词汇习得领域的研究进展，揭示其研究特点及未来发展方向，文章依据PRISMA文献筛选流程，对2011~2026年中国知网(CNKI)和Web of Science数据库收录的相关文献进行了系统分析。研究发现：二语词汇习得领域已基本形成“间隔学习优于集中学习”的共识，研究重心逐渐由效应验证转向作用机制解释，研究范式由学习效果比较拓展至间隔模式、学习任务、保持时间等多因素综合研究，数字技术的发展进一步推动了研究情境由实验室向真实课堂延伸。然而，现有研究仍存在作用机制阐释不足、最佳间隔策略尚未形成统一结论以及真实教学情境下长期实证研究相对欠缺等问题。未来研究应加强认知心理学与二语习得理论的融合，结合移动辅助语言学习、人工智能和学习分析等数字技术，深化真实课堂环境中的长期追踪研究，探索面向学习者个体差异的自适应间隔学习模式，为二语词汇教学优化与教育数字化实践提供理论支持与实践参考。

Abstract: To systematically review the research on the spacing effect in second language (L2) vocabulary acquisition and identify its major characteristics and future directions, this study conducted a systematic review of relevant studies published between 2011 and 2026 in the China National Knowledge Infrastructure (CNKI) and Web of Science databases, following the PRISMA guidelines. The review reveals that a broad consensus has emerged that spaced learning is generally more effective than massed learning in promoting L2 vocabulary acquisition. Research has gradually shifted from verifying the effectiveness of the spacing effect to exploring its underlying mechanisms. Meanwhile, research paradigms have expanded from simple comparisons of learning outcomes to multifactorial investigations involving spacing schedules, learning tasks, retention intervals, and other influencing variables. Advances in digital technology have also facilitated the extension of research settings from controlled laboratory environments to authentic classroom contexts. Despite these advances, existing research still faces several limitations, including insufficient explanation of the underlying mechanisms, a lack of consensus regarding optimal spacing strategies, and a shortage of longitudinal empirical studies conducted in authentic instructional settings. Future research should further integrate cognitive psychology with theories of second language acquisition, leverage emerging digital technologies such as mobile-assisted language learning, artificial intelligence, and learning analytics, and investigate adaptive spaced learning models that accommodate individual learner differences through longitudinal classroom-based research. Such efforts will provide stronger theoretical foundations and practical guidance for optimizing L2 vocabulary instruction and advancing digitalized language education.