Abstract

The notion of “Micro-Learning” (ML) has been repeatedly accented as a successful learning approach in different learning phenomena. Despite these optimistic emphases, several studies lack a theoretical grounding in adoption of ML, thus missing a shared perspective of the education community. The scarce theoretical justification for understanding the nuanced dynamics of ML restricts the practical use of this pedagogical approach in “Second Language” (L2) instruction. Therefore, this paper seeks to fill the gap by proposing a theoretical model of ML for L2 instruction. First, a brief background on ML is provided evaluating its benefits and pitfalls in general teaching and learning enterprise. Second, three established theories are explicitly discussed based on a careful examination of the conceptual characteristics and empirical observations of ML. A theoretical model of ML is then devised based on relations postulated among proposed theories and application of the model to existing L2 MLs is made explicit. Finally, implications for research and practice are discussed to offer a more robust and descriptive picture of how ML can promote L2 teaching and learning across different contexts. Drawing from these theoretical insights, a principled way to integrating ML into L2 instruction can be made available for future research.

摘要

“微学习”（ML）的概念在不同的学习现象中被反复强调为一种成功的学习方法。尽管有这些乐观的重点，但一些研究缺乏采用 ML 的理论基础，因此缺少教育界的共同观点。理解 ML 微妙动态的稀缺理论依据限制了这种教学方法在“第二语言”（L2）教学中的实际使用。因此，本文试图通过提出用于二语教学的机器学习理论模型来填补这一空白。首先，简要介绍了机器学习的背景，评估了它在一般教学和学习企业中的好处和缺陷。其次，基于对 ML 的概念特征和经验观察的仔细检查，明确讨论了三个已建立的理论。然后基于提出的理论之间假设的关系设计了 ML 的理论模型，并明确了该模型在现有 L2 ML 中的应用。最后，讨论了对研究和实践的影响，以提供关于机器学习如何在不同环境中促进二语教学和学习的更强大和描述性的画面。借鉴这些理论见解，可以为未来的研究提供一种将 ML 集成到 L2 指令中的原则方法。