Work

Examining the Impact of Digital Linguistic Landscapes on Students’ motivation, and Self‐Perceived Achievement in Second Language Writing

Year: 2025

Type: article

Abstract: ABSTRACT Given the importance of the linguistic landscape in language learning, the digital linguistic landscape (DLL) has emerged as an important multimodal input resource. However, few studies have been conducted to explore the antecedent and predictive effect of the DDL on L2 writing. To address this gap, the study attempted to conceptualize the DLL and to examine its impact on English learners’ motivation and self‐perceived achievement. Quantitative data were collected from 504 university students through a survey, complemented by qualitative data obtained via semi‐structured interviews with six of them. Data analysis employed Dörnyei's L2 Motivational Self System and PLS‐SEM to investigate the relationships among students’ DLL exposure, learning motivation, and writing achievement. The results indicate that DLL exposure significantly enhanced students’ ideal L2 self and intrinsic motivation, exerting a positive impact on their writing achievement. Learning motivation could partially mediate the correlation between DLL exposure and writing achievement, indicating that DLL input directly enhanced language performance and indirectly stimulated writing achievement through motivation. These findings provide a new perspective on the digital expansion of linguistic landscape theory and offer practical insights for the implementation of DLL‐based language teaching practices.

Source: International Journal of Applied Linguistics

DOI: 10.1111/ijal.12801

Authors: Zi Yang, Lawrence Jun Zhang

Institutions: University of Auckland, Nanjing University of Posts and Telecommunications

Language: English

Topic: EFL/ESL Teaching and Learning

Subfield: Language and Linguistics

Field: Arts and Humanities

Domain: Social Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $3,240