Developing an AI-Based Learning System for L2 Learners’ Authentic and Ubiquitous Learning in English Language

Fenglin Jia, Daner Sun (), Qing Ma and Chee-Kit Looi
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Fenglin Jia: Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong SAR 999077, China
Daner Sun: Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong SAR 999077, China
Qing Ma: Department of Linguistics and Modern Language Studies, The Education University of Hong Kong, Hong Kong SAR 999077, China
Chee-Kit Looi: National Institute of Education, Nanyang Technological University, Singapore 637616, Singapore

Sustainability, 2022, vol. 14, issue 23, 1-18

Abstract: Motivated by the rapid development and application of artificial intelligence (AI) technologies in education and the needs of language learners during the COVID-19 pandemic, an AI-enabled English language learning (AIELL) system featuring authentic and ubiquitous learning for the acquisition of vocabulary and grammar in English as a second language (L2) was developed. The aim of this study was to present the developmental process and methods used to design, develop, evaluate, and validate the AIELL system and to distil key design features for English learning in authentic contexts. There were 20 participants in the tests, with three interviewees in the study. Mixed research methods were employed to analyse the data, including a demonstration test, a usability test, and an interview. The quantitative and qualitative data collected and analysed affirmed the validity and usability of the design and helped identify areas for further improvements to the desired features. This study informs the integration of AI into facilitating language teaching and learning guided by the mobile learning principle.

Keywords: artificial intelligence; mobile learning; authentic and ubiquitous learning; system development; English as L2 learner (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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