The predictive role of L2 motivation in receptive and productive informal digital learning of English: A chain mediation model

This article draws attention to the ways in which Hong Kong university students are motivated to engage in informal digital learning of English (IDLE) activities. Drawing upon the second language (L2) Motivational Self System (Dörnyei, 2009), it seeks to examine how Hong Kong students’ L2 motivational components, including the ideal L2 self, the ought-to L2 self, and L2 learning experiences, predict their receptive IDLE activities (RIA), and productive IDLE activities (PIA). Using an adapted and validated questionnaire, we collected data from 310 undergraduate students in a Hong Kong public university and analyzed the data following a structural equation modeling approach (Collier, 2020). Results supported that Hong Kong university students’ ideal L2 selves could positively predict their L2 learning experiences, RIA and PIA, while the ought-to selves could only directly influence L2 learning experiences. Our findings based on the mediation analysis also highlighted that L2 learning experiences and RIA could partially mediate the impact of the ideal L2 self on PIA and fully channel the indirect effect of the ought-to L2 self on PIA. These findings not only add to the existing understanding of IDLE in a localized Hong Kong context but also disclose the dynamic interactions between L2 motivation, and receptive and productive out-of-class learning activities in the digital age.

Authors

Institutions

Publication Details

Journal
Digital Applied Linguistics
Published
2024-11-13
DOI
https://doi.org/10.29140/dal.v1.2229
Citations
3
Primary Topic
Innovations in Education and Learning Technologies
Type
article
Field-Weighted Citation Impact
2.34
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The predictive role of L2 motivation in receptive and productive informal digital learning of English: A chain mediation model

Guangxiang Liu, Wilkinson Daniel Wong Gonzales, K. C. Geoffrey Ng
3 citations
Digital Applied Linguistics
Innovations in Education and Learning Technologies
2.34
article

The predictive role of L2 motivation in receptive and productive informal digital learning of English: A chain mediation model

Guangxiang Liu, Wilkinson Daniel Wong Gonzales, K. C. Geoffrey Ng
article en
3 citations

Abstract

This article draws attention to the ways in which Hong Kong university students are motivated to engage in informal digital learning of English (IDLE) activities. Drawing upon the second language (L2) Motivational Self System (Dörnyei, 2009), it seeks to examine how Hong Kong students’ L2 motivational components, including the ideal L2 self, the ought-to L2 self, and L2 learning experiences, predict their receptive IDLE activities (RIA), and productive IDLE activities (PIA). Using an adapted and validated questionnaire, we collected data from 310 undergraduate students in a Hong Kong public university and analyzed the data following a structural equation modeling approach (Collier, 2020). Results supported that Hong Kong university students’ ideal L2 selves could positively predict their L2 learning experiences, RIA and PIA, while the ought-to selves could only directly influence L2 learning experiences. Our findings based on the mediation analysis also highlighted that L2 learning experiences and RIA could partially mediate the impact of the ideal L2 self on PIA and fully channel the indirect effect of the ought-to L2 self on PIA. These findings not only add to the existing understanding of IDLE in a localized Hong Kong context but also disclose the dynamic interactions between L2 motivation, and receptive and productive out-of-class learning activities in the digital age.

Digital Applied LinguisticsVol. 1
Chinese University of Hong Kong (HK)
Openalex Percentile: Top 9%
Innovations in Education and Learning Technologies
2.34
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

The predictive role of L2 motivation in receptive and productive informal digital learning of English: A chain mediation model — Guangxiang Liu, Wilkinson Daniel Wong Gonzales, et al. · Digital Applied Linguistics (2024) | TGRS Research Map | TGRS