Guangxiang Liu|Ron Darvin|Chaojun Ma
Exploring AI-mediated informal digital learning of English (AI-IDLE): a mixed-method investigation of Chinese EFL learners’ AI adoption and experiences
Chinese University of Hong Kong|University of British Columbia|City University of Hong Kong
recent advancements natural language processing large language models ushered language learning age artificial intelligence ai recognizing affordances generative ai tools paper aims examine degree l2 learners accepted leveraged large language model platforms eg chatgpt bing chat informal digital learning english idle purposes employing explanatory sequential mixedmethod design study draws technology acceptance model tam collects data via adapted tam questionnaire interview guide total 867 chinese efl english foreign language learners answered online survey 20 attended postsurvey interviews drawing validated structural model elucidates interfactor relationships perceived ease use perceived usefulness intention use actual use quantitative analysis provides statistical accounts efl learners adoption generative pretrained transformer gpt technologies qualitative findings derived interview data reveal three key themes 1 perceived usefulness chatbots idle emerges handson experimentation tools 2 intention use increases learners negotiate chatbot affordances constraints 3 actual use chatbots idle involves using tools tutors conversation partners connections quantitative qualitative findings enhance understanding efl learners negotiate affordances constraints highly capable ai technologies participate creative idle practices understanding practices study draws attention attitudes practices constitute ai literacies ultimately offering implications future classroom practices research