Integrating Sustainable Development Goals (SDGs) and Generative AI to Enhance Language Digital Literacy and Creativity in EFL Learning Environments

Summary

Combining SDGs with generative AI like ChatGPT boosts English learners' motivation, digital literacy, and creativity. Higher engagement strengthens this link, providing teachers with practical strategies for integrating AI in language teaching.

Abstract

This study investigates the integration of Sustainable Development Goals (SDGs) and generative AI, specifically ChatGPT, to enhance language digital literacy, creativity, and motivation in EFL learning environments. Adopting a quantitative, cross-sectional design, the data for this study were collected from n = 420 undergraduate EFL students at one public sector university in China, using validated scales to measure SDG integration (SDG), Use Generative AI like ChatGPT (UCGPT), digital literacy (DL) EFL Students' creativity (SC), EFL Students' motivation (SM) and language learning engagement (LLE). Partial least squares structural equation modeling (PLS-SEM) was employed to analyze direct, mediating, and moderating effects. Findings revealed that SDG integration and UCGPT were significantly associated with SM, which in turn predicted digital literacy and EFL students' creativity. Moreover, LLE moderated the relationship between DL and SC, while SM mediated the effects of SDG integration and UCGPT on digital literacy. These results highlight the transformative potential of integrating SDGs and AI tools in EFL education, providing scalable strategies to develop 21st-century skills. Additionally, the study provides concrete strategies for EFL teachers, such as tasking students with using ChatGPT to prepare for debates on SDG topics, like climate justice, or to co-create multilingual social media campaigns for sustainability awareness. These applications demonstrate how to operationalize SDG-AI integration in everyday lesson planning.

Introduction

The global landscape of English as a Foreign Language (EFL) education is undergoing a profound transformation, driven by the dual imperatives of technological innovation and the United Nations' Sustainable Development Goals (SDGs)¹. While the demand for English proficiency continues to surge in non-Anglophone regions, fueled by globalization, academic mobility, and digital economies², traditional pedagogical approaches often fail to equip learners with the critical competencies needed for 21st-century communication³. Conventional EFL methodologies, which emphasize rote memorization and structu....

Protocol

This study was conducted in compliance with ethical guidelines for human subject's research. Informed consent was obtained from all participants prior to their involvement, ensuring they were fully informed of the study's purpose, survey-based procedures, voluntary nature, and their right to withdraw at any time without consequence. All methods adhered to ethical standards for human research, ensuring participant confidentiality, data anonymization, and protection throughout the study. The study involved non-invasive, survey-based data collection with minimal risk to participants.

1. Research design

Results

Descriptive statistics
A descriptive analysis provides important insights into patterns of variables, central locations, and their dispersion, enabling researchers to verify the health, normality, and theoretical congruence of the initial data. In this study, the mean values are used to measure the level of kurtosis, while the parameters of standard deviation are employed to assess the level of skewness. Additionally, the effects of skewness are also considered. This suggests that the 420 participant.......

Discussion

Summary of key findings
This study examined the interplay between Sustainable Development Goals (SDGs), generative AI (ChatGPT), and key educational outcomes: motivation, digital literacy, and creativity in EFL learning environments. The results confirmed all direct-effect hypotheses (H1-H5), demonstrating that SDG integration (β = 0.37) and ChatGPT use (β = 0.28) significantly enhance student motivation, which in turn fosters digital literacy (β = 0.45) and creativity (β = 0.32.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
ChatGPT Usage Scale	8-item scale adapted from Abbas et al. (2023).	Abbas et al. (2023).
Creativity Scale	12-item scale adapted from Govindasamy et al. (2022), measuring four sub-constructs: Originality, Flexibility, Fluency, and Elaboration.	Govindasamy et al. (2022)
Data Collection Instrument	Anonymous, self-administered paper-and-pencil questionnaire.	Not applicable / custom-designed
Data Storage System	Password-protected servers with encrypted digital systems.	Not applicable / institutional IT infrastructure
Digital Literacy Scale	29-item scale adapted from Rodríguez-de-Dios et al. (2018), covering six dimensions: Technological, Personal Security, Critical, Device Security, Information, and Communication Literacy.	Rodríguez-de-Dios et al. (2018)
Informed Consent Documents	Written information sheet and consent form.	Not applicable / custom-designed
Language Learning Engagement Scale	9-item scale adapted from Eerdemutu et al. (2023).	Eerdemutu et al. (2023)
Motivation Scale	5-item scale adapted from Obiosa (2023).	Obiosa (2023).
PLS-SEM Algorithm & Bootstrapping	SmartPLS 4 internal routines (PLS Algorithm and Bootstrapping with 5,000 subsamples).	https://www.smartpls.com/documentation/algorithms-and-techniques
Predictive Relevance Assessment	Blindfolding procedure in SmartPLS 4 to calculate Stone-Geisser’s Q² value.	https://www.smartpls.com/documentation/predictive-relevance-q2
SDG Integration Scale	36-item scale adapted from Atmaca et al. (2023), with subscales for Economy (13 items), Society (9 items), and Environment (14 items).	Atmaca et al. (2023)
Statistical Analysis Software	IBM SPSS Statistics, Version 28.	-
Structural Equation Modeling Software	SmartPLS, Version 4.	https://www.smartpls.com
Validity & Reliability Checks	SmartPLS 4 reporting functions for Composite Reliability, Average Variance Extracted (AVE), Fornell-Larcker Criterion, and HTMT ratios.	https://www.smartpls.com/documentation/reporting