Speaker
Description
Online extensive reading (OER) provides valuable opportunities for incidental vocabulary learning, yet learners often struggle with unfamiliar words without interrupting reading. Generative AI offers an alternative to traditional dictionary consultation by providing contextualized vocabulary support, but little is known about learners’ acceptance of this approach in OER. Guided by the Technology Acceptance Model (Davis, 1989), this work-in-progress study investigates adult EFL learners’ perceptions of AI-assisted vocabulary support compared with dictionary use during OER. Specifically, it examines learners’ perceived usefulness and ease of use of AI support, as well as factors such as perceived speed, accuracy, and convenience that influence their preferences. Using a mixed-methods design, approximately 50 adult EFL learners at a Vietnamese language center will complete a questionnaire adapted from TAM, supplemented by open-ended responses. Quantitative data will be analyzed using paired comparisons and correlation analysis, while qualitative responses will undergo thematic analysis. Findings are expected to inform AI integration into extensive reading and extend research on technology acceptance in AI-supported vocabulary learning.
Keywords: online extensive reading; generative AI; vocabulary learning; Technology Acceptance Model; adult EFL learners.
