Students’ Perceptions of an AI-Based English e-Module for Digital Content Creation: An Explanatory Sequential Mixed-Methods Study - Alfaridhi, Dio Fahmi; Prayudha, Prayudha; Ali, Raden Muhammad; Masduki, Anang (JOLLT Journal of Languages and Language Teaching, 2026)
The integration of AI in EFL is increasingly vital to meet the demands of digital content creation, where English serves as a global medium for audience engagement. This study aims to investigate how students view the usefulness of an AI-based English e-module in improving their abilities and involvement in the production of digital content. An explanatory sequential mixed-method was used in this study. The data were gathered from 44 students of communication science study program at Universitas Ahmad Dahlan. Quantitative data were collected via a structured questionnaire grounded in the Technology Acceptance Model (TAM) and qualitative data were gathered through structured interviews with six purposively chosen participants. The quantitative data were analyzed using descriptive statistics, while qualitative data were analyzed using thematic analyses. Results revealed strong positive perceptions: the AI feature usefulness item recorded M = 3.98, the comparative effectiveness over conventional methods item yielded M = 3.89, and overall satisfaction achieved M = 3.91. Thematic analysis confirmed the value of real-time chatbot feedback and automated corrections in enhancing scriptwriting and confidence, though device incompatibilities and navigation issues emerged as barriers. These results suggest that in order to acquire real digital communication abilities, educators should incorporate AI-driven e-modules into task-based EFL curricula. Additionally, system design should give priority to multilingual support and cross-device optimization in order to guarantee equitable access.