Revisiting informal digital learning of English (IDLE): a structural equation modeling approach in a university EFL context

Abstract

Informal digital learning of English (IDLE) is an increasingly important subfield of inquiry in Computer-Assisted Language Learning (CALL) for its concentration on the language learning practices of the digital native EFL students in out-of-class contexts. Attention in mainstream research of IDLE has been directed to (meta)cognition, learning outcomes, etc. as separate domains of IDLE; however, these significant efforts have neither clarified the blurry boundary between semi-structured IDLE practices and unstructured extramural practices nor investigated factors that positively predict learners’ IDLE-enhanced learning outcomes or practices on the four language skills: listening, speaking, reading, and writing. As such, the present study sets out to extend the discussion of informal digital learning of English (IDLE) by establishing a recontextualized model of IDLE. To this end, a total of 1080 Chinese university EFL learners were invited to complete an IDLE questionnaire survey developed and validated in the context of China. Using IBM SPSS Amos 22, structural equation modeling was run to examine the inter-factorial relationships among six IDLE sub-constructs by examining eight hypotheses. The results confirm that 1) learners’ IDLE-enhanced benefits are positively predicted by support from their important others, resources and cognition, but not learners’ authentic L2 experience and IDLE frequency and devices, and 2) learners’ IDLE practices can be significantly predicted by resources and cognition, authentic L2 experience, and IDLE frequency and devices. Based on these findings, we put forward an expanded conceptual framework of IDLE and suggest more replication studies in the future to testify this study’s generalizability and to arrive at more stable conclusions.

Keywords:

• IDLE
• informal digital learning of English
• Chinese EFL context
• structural equation modeling
• language learning beyond the classroom

Acknowledgments

We are indebted to Dr. Ron Darvin and Professor Phil Benson for their professional advice and kind help while writing this paper. Many thanks also go to all participants involved in this study and those who helped a lot with data collection.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The raw data can be made available upon request.

Appendices

Additional information

Notes on contributors

Yue Zhang

Yue Zhang is a Ph.D. in Applied English Linguistics candidate in the Department of English, The Chinese University of Hong Kong, Hong Kong. She has earned her M.Phil. in Applied English Linguistics from The Chinese University of Hong Kong. Her research interests include identity and investment, L2 motivation, language teacher education. She has published in System and Chinese Journal of ESP.

Guangxiang Liu

Guangxiang Liu is a Ph.D. in Applied English Linguistics student in the Department of English, The Chinese University of Hong Kong, Hong Kong. He has earned his M.Sc. in TESOL from The University of Edinburgh, UK. His research interests include identity and investment, digital literacies, linguistic landscape. His recent research has appeared in SSCI journals Journal of Second Language Writing and Journal of Linguistic Anthropology.