AI-Supported Vocabulary Learning in Saudi EFL Higher Education: A Bloom’s Taxonomy–Based Application

Abstract

This study investigates the effectiveness of an AI-based vocabulary learning app, designed by the research supervisor and grounded in Bloom’s Taxonomy, in enhancing English as a Foreign Language (EFL) vocabulary acquisition among Saudi university students. Vocabulary development remains a major challenge for EFL learners, and adaptive, personalized technologies may help address individual learning needs. A quasi-experimental design is employed, comparing an experimental group using the AI-based app with a control group receiving traditional instruction. Vocabulary proficiency is measured through pretests and posttests to evaluate the impact of the intervention and identify differences between the two groups. The AI app applies a scaffolded approach aligned with Bloom’s cognitive levels, progressing from basic recall to higher order thinking skills to support comprehensive vocabulary mastery. Data collection includes quantitative test scores and a feedback survey to capture students’ perceptions of usability and effectiveness. Statistical analyses assess differences in vocabulary gains, while thematic analysis examines learners’ experiences. The study aims to contribute to EFL pedagogy by demonstrating the role of AI-driven tools in supporting vocabulary acquisition, learner engagement, and personalized learning.