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Jakob, Juvrianto Chrissunday
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Cultural Intelligence in AI-Driven Online Learning: Examining Bias and Inclusivity in Virtual Classrooms Juvrianto Chrissunday Jakob; Maslan Abdin; Mohammed H. Alaqad; Sivaraja S; Andi Asrifan
Jo-ELT (Journal of English Language Teaching) Fakultas Pendidikan Bahasa & Seni Prodi Pendidikan Bahasa Inggris IKIP Vol. 13 No. 1 (2026): June
Publisher : Faculty of Culture, Management, and Business Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jo-elt.v13i1.20009

Abstract

The integration of artificial intelligence (AI) into online education has transformed teaching and learning practices through personalization, automation, and adaptive learning support. However, the increasing use of AI-driven educational systems raises concerns regarding their ability to accommodate culturally diverse learners. While previous studies have primarily focused on the effectiveness of AI in improving engagement and learning outcomes, limited attention has been given to the role of cultural intelligence (CQ) in AI-mediated learning environments. This study examines how AI-integrated online learning platforms support or constrain cultural inclusivity among diverse student populations. The study employed an explanatory sequential mixed-methods design involving 230 participants, including students, instructors, and AI developers. Quantitative data were collected through surveys and analyzed using descriptive statistics, ANOVA, and regression analysis, while qualitative data from semi-structured interviews and focus groups were analyzed through thematic analysis. The findings indicate that although AI technologies improve accessibility and learning efficiency, many AI-driven systems still reflect dominant Western-oriented educational norms and communication styles. Non-Western learners and multilingual students reported lower engagement levels, particularly when AI-generated feedback and content recommendations lacked cultural representation and contextual sensitivity. The study also found that learners with higher levels of cultural intelligence demonstrated stronger adaptability to AI-mediated learning environments. This study contributes to the growing discussion on AI in education by positioning cultural intelligence as an important consideration in the design and implementation of AI-supported learning systems. The findings highlight the need for culturally responsive AI frameworks and emphasize the continuing importance of human–AI collaboration in creating equitable and inclusive online learning environments.
Co-Authors Abdin, Maslan Ahmad Nusi Ahmad Nusi Ana Sari, Hindri Febri Andrie Ch. Salhuteru Anthoneta Maitimu Arthur Imanuel Sinay Asrifan, Andi Betaubun, Renny James Fataruba, Muhammad Zulham Frans, Pieter L Haikuty, Mathias Theofilus hamkah, hamkah Haris, Wardi Haryanto Atmowardoyo Hasana Bolkia Kaliky Hizkia Nussy Huwae, David Daniel Marthin Jacob Johanis Lelapary Jakob, Fidela Evania Jessy Juniu Hahury Latar, Sjafrudin Leatemia, Meiti Lohy, Mastura Maelissa, Nelda Mahu, Muhamad Sidik Maslan Abdin Mastura Lohy Matitaputty, Apri Adam Meyke Marantika Meyke Marantika Mohammed H. Alaqad Mouren Wuarlela Nihla Afdaliah Nikijuluw, Reynold P. J. Vigeleyn Nikijuluw, Reynold Pieter Jordan Vigeleyn NIKOLAUS PASSASUNG PASSASUNG, NIKOLAUS Penina T. Istia Persulessy, Sylvia Irene Pertiwi, Sri Ananda Rahantan, Abdu Rahman Ralph Javier Renny James Betaubun Rudi Serang Salawaney, Valy Silas Saptenno, Sammy Selviana Walsen Singadji, Andarias Sivaraja S Sjafrudin Latar Sukardi Weda Syafna Maruapey Talakua, Elisabeth Vera Theresia Caroline Siahaya Walalayo, Rosmawati Wiliam Matalatua Yelliza Yelliza