Exploring Quantity and Diversity of Informal Digital Learning of English (IDLE): A Review of Selected Paper

Abstract

This article reviews research on informal digital English (IDLE) learning that has increased in the field of English language teaching to other language speakers and computer-assisted language learning written by Ju Seong Lee (2019), entitled Quantity and Diversity of informal digital learning of English published by Language Learning & Technology. This present paper uses descriptive qualitative analysis in an attempt to understand how the quantity and diversity of IDLE can make a unique contribution to the English language outcomes of EFL learners from the researcher's perspective. Lee uses hierarchical linear regression analysis to show that IDLE Quantity, Age, and Major are significant predictors of two affective variables (Confidence and Pleasure), while IDLE Diversity and Major significantly predict productive language outcomes (Speaking and Productive Vocabulary Knowledge), score in the standard English Test (TOEIC), and one affective variable (Lack of Anxiety). This present article aims to review and discuss the findings on the strengths and the weaknesses found in Lee’s 2019 article. The article Lee made seems to possess a clear flow on how to explain these two types of education and make this article easy to understand. Therefore, the replication of Lee’s research is easy enough for similar research purposes.