Profiling the affective characteristics of EFL learners’ digital informal learning: A person-centered approach

ABSTRACT

Purpose

This study (1) used a person-centered approach to identify specific subgroups of 1,265 EFL learners who participated in Informal Digital Learning of English (IDLE) activities, and (2) looked at how different IDLE profiles are related to important affective variables.

Design/Methodology

: To identify IDLE profiles, we used cluster analysis.

Findings

The L2 motivation, L2 enjoyment, L2 anxiety, and grit levels of the IDLErs with distinct profiles differed significantly. When compared to Profiles 1 (Minimal IDLErs: 33%), 2 (Gaming-Entertainment IDLErs: 16%), and 3 (Entertainment IDLErs: 30%), both Profile 4 (Maximal IDLErs: 11%) and Profile 5 (Entertainment-socializing IDLErs: 10%) demonstrated significantly higher scores on Ideal L2 self, L2 enjoyment-self, L2 enjoyment-others, L2 communication anxiety-offline, and Grit. Profiles 4 and 5 made full use of out-of-school digital environment, which provided several affective benefits for EFL learners.

Originality/value

Methodologically, the analytical and statistical approach could help to move informal language learning research one step closer to being more person-centered. In practice, the various IDLE profiles identified in this study may be of interest to EFL teachers in order to better understand their students’ IDLE activities outside of school and to inform classroom teaching and learning.

KEYWORDS:

• Informal digital learning of English
• L2 motivation
• L2 enjoyment
• L2 anxiety
• grit
• person-centered approach

Acknowledgments

We would like to express our gratitude to the anonymous reviewers and the editor (Professors Hayo Reinders and Terry Lamb) for their assistance and insights in previous drafts of the article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Outliers of Profile 1: There are a few outliers in Profile 1 who had more frequent experience with F1 gaming and F4 socializing; these outliers are only a few and do not affect the main pattern of the profile. Their IDLE engagement patterns are still more similar to the others with Profile 1 than those with other profiles.

2 Outliers of Profile 3: There are a few outliers in Profile 3, who had more frequent engagement with F3 English learning activity and with F4 socializing than the others with this profile. These outliers, however, are only a few and do not affect the main pattern of this profile. Their IDLE engagement patterns are still more similar to the others with Profile 3 than those with other profiles.

3 Both partial eta-squared and Cohen’s f are reported for effect size. In terms of η_p², .01 indicates a small effect; .06 indicates a medium effect and .14 indicates a large effect; In terms of Cohen’s f: f = 0.1 is considered a small effect; f = 0.25 is a medium effect, and f = .40 is a large effect (Salkind 2010). Accordingly, Mot-I and Enjoy-S have a large effect, while the rest of the variables have small to medium effects.

Additional information

Notes on contributors

Ju Seong Lee

Ju Seong Lee is Assistant Professor and Associate Head in the Department of English Language Education at the Education University of Hong Kong. He is the author of Informal Digital Learning of English: Research to Practice (Routledge, 2022). His recent research focuses on integrating technology and positive psychology into formal school settings.

Qin Xie

Qin Xie is Assistant Professor at the Education University of Hong Kong. She has applied Structural Equation Modeling, Rasch measurement, Cognitive Diagnostic Modeling in her research and published her work on peer-reviewed high-impact journals such as Assessing Writing, Language Testing, Language Assessment Quarterly, Language Teaching, Educational Psychology, Research & Development in Higher Education, Studies in Educational Evaluation, Systems among others.