Developing A Collaborative Learning-Based English for Artificial Intelligence Textbook for ESP Instruction

Non-native English speakers often face challenges in navigating the complex and specialized language used in AI literature. This study reports on the development of a textbook titled English for Artificial Intelligence, designed to address these challenges through a collaborative learning approach. This book is designed to bridge the gap by providing targeted language instruction tailored to the needs of AI professionals. Employing a Research and Development (R&D) methodology, the study followed the ADDIE model. Data were collected through simple random sampling involving 76 Informatics students, 2 ESP lecturers, a content and a layout expert during the needs analysis phase. The textbook primarily focuses on reading comprehension with supplementary activities in writing and speaking on the exercises. The validation stage, involving 20 students, ESP lectures, and subject matter experts, evaluated the textbook. Results showed that this textbook is Very Feasible to use for ESP teaching and learning. The feasibility aspects can also be seen from the scores given by students and experts, with 4.69 and 4.68 on average, respectively. The feasibility aspects cover content feasibility, presentation feasibility, language use, and graphic feasibility. The acceptance level for this book is 88% and 84% by the experts and students, respectively. These findings confirm that the textbook is both pedagogically sound and contextually appropriate, offering a practical solution for improving English proficiency among AI learners and contributing to more inclusive participation in the global AI discourse.

Authors

Publication Details

Journal
Metathesis Journal of English Language Literature and Teaching
Published
2025-08-11
DOI
https://doi.org/10.31002/metathesis.v9i1.2681
Primary Topic
Technology-Enhanced Education Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Developing A Collaborative Learning-Based English for Artificial Intelligence Textbook for ESP Instruction

Sri Waluyo, Fatimah Nur Arifah, Kanafi
Metathesis Journal of English Language Literature and Teaching
Technology-Enhanced Education Studies
article

Developing A Collaborative Learning-Based English for Artificial Intelligence Textbook for ESP Instruction

Sri Waluyo, Fatimah Nur Arifah, Kanafi
article en

Abstract

Non-native English speakers often face challenges in navigating the complex and specialized language used in AI literature. This study reports on the development of a textbook titled English for Artificial Intelligence, designed to address these challenges through a collaborative learning approach. This book is designed to bridge the gap by providing targeted language instruction tailored to the needs of AI professionals. Employing a Research and Development (R&D) methodology, the study followed the ADDIE model. Data were collected through simple random sampling involving 76 Informatics students, 2 ESP lecturers, a content and a layout expert during the needs analysis phase. The textbook primarily focuses on reading comprehension with supplementary activities in writing and speaking on the exercises. The validation stage, involving 20 students, ESP lectures, and subject matter experts, evaluated the textbook. Results showed that this textbook is Very Feasible to use for ESP teaching and learning. The feasibility aspects can also be seen from the scores given by students and experts, with 4.69 and 4.68 on average, respectively. The feasibility aspects cover content feasibility, presentation feasibility, language use, and graphic feasibility. The acceptance level for this book is 88% and 84% by the experts and students, respectively. These findings confirm that the textbook is both pedagogically sound and contextually appropriate, offering a practical solution for improving English proficiency among AI learners and contributing to more inclusive participation in the global AI discourse.

Metathesis Journal of English Language Literature and TeachingVol. 9(1)
Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi
Quality Education
Openalex Percentile: Top 77%
Technology-Enhanced Education Studies
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