Globalizing Language Learning with Multicultural Sensitivity: How Ubiquitous Learning Technologies Support Cross-Cultural Language Acquisition

Ishak Bagea (1), Jack Davis (2), Emilie Bernard (3)
(1) Universitas Muhammadiyah Kendari, Indonesia,
(2) Monash University, Australia,
(3) Monaco Law University, Monaco

Abstract

Background. As the world becomes increasingly interconnected, language acquisition extends beyond merely mastering grammar and vocabulary to include understanding cultural nuances. Ubiquitous learning technologies have transformed the way languages are taught, making learning more flexible, accessible, and personalized. However, there remains a need for these technologies to address not only linguistic proficiency but also multicultural sensitivity, enabling learners to navigate cross-cultural communication effectively in a globalized world.


Purpose. This study aims to explore how ubiquitous learning technologies can support language acquisition while fostering multicultural sensitivity. Specifically, it investigates the role of digital tools in bridging cultural gaps and enhancing learners’ ability to communicate across diverse cultural contexts.


Method. A mixed-methods approach was employed, combining surveys, interviews, and usage data from learners who used mobile apps and online platforms for language learning. The study focused on how these technologies facilitated cross-cultural understanding, linguistic competence, and the development of intercultural communication skills.


Results. The findings indicate that learners who used digital tools that incorporated cultural content and context-driven learning strategies showed significant improvements in both language proficiency and intercultural sensitivity. These learners demonstrated increased engagement and motivation, particularly in understanding cultural contexts and applying language in real-world scenarios.


Conclusion. Ubiquitous learning technologies, when designed with multicultural sensitivity, play a critical role in supporting cross-cultural language acquisition. This research highlights the importance of integrating cultural awareness into language learning platforms to promote global communication skills.

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References

A., A. G., & V., V. (2024). Sentiment analysis on a low-resource language dataset using multimodal representation learning and cross-lingual transfer learning. Applied Soft Computing, 157, 111553. https://doi.org/10.1016/j.asoc.2024.111553

Ahmad, P. N., Shah, A. M., Lee, K., Naqvi, R. A., & Muhammad, W. (2025). Optimizing slogan classification in ubiquitous learning environment: A hierarchical multilabel approach with fuzzy neural networks. Knowledge-Based Systems, 314, 113148. https://doi.org/10.1016/j.knosys.2025.113148

Alwakid, W. N., Dahri, N. A., Humayun, M., & Alwakid, G. N. (2025). Integrating AI chatbots for enhancing academic support in business education: A SEM-Based study toward sustainable learning. The International Journal of Management Education, 23(3), 101252. https://doi.org/10.1016/j.ijme.2025.101252

Austin, T., & Medina Riveros, R. A. (2025). Ethics for researching language and education: What the discourse of professional guidelines reveals. Research Methods in Applied Linguistics, 4(2), 100221. https://doi.org/10.1016/j.rmal.2025.100221

Benabbes, S., & AbdulHaleem Abu Taleb, H. (2024). The effect of storytelling on the development of language and social skills in French as a foreign language classrooms. Heliyon, 10(8), e29178. https://doi.org/10.1016/j.heliyon.2024.e29178

Benítez-Burraco, A., & Nikolsky, A. (2025). Language Evolution and Music Evolution. Dalam Reference Module in Social Sciences. Elsevier. https://doi.org/10.1016/B978-0-323-95504-1.00854-1

Bickhard, M. H. (2025). Persons: The emergence of Homo Socius. Dalam M. H. Bickhard (Ed.), The Whole Person (hlm. 261–442). Academic Press. https://doi.org/10.1016/B978-0-443-33050-6.00010-0

Boukhari, D. E., Dornaika, F., Chemsa, A., & Taleb-Ahmed, A. (2025). A comprehensive review of facial beauty prediction using deep learning techniques. Engineering Applications of Artificial Intelligence, 161, 112009. https://doi.org/10.1016/j.engappai.2025.112009

Brdar, M., & Brdar-Szabó, R. (2024). When medical eponyms become false friends, and how to deal with them. English for Specific Purposes, 73, 75–94. https://doi.org/10.1016/j.esp.2023.10.005

Carroll, P., Singh, B., & Mangina, E. (2024). Uncovering gender dimensions in energy policy using Natural Language Processing. Renewable and Sustainable Energy Reviews, 193, 114281. https://doi.org/10.1016/j.rser.2024.114281

Cintora, P., Quirós-Alcalá, L., Nzegwu, A. W., Upadhyaya, S., Woodbury, M., Geiger, S. D., Morello-Frosch, R., Dunlop, A. L., Bastain, T. M., Starling, A. P., Dabelea, D., Camargo, C. A., Lin, P.-I. D., Kelly, R. S., Ferrara, A., Croen, L. A., O’Connor, T. G., Park, J.-S., Reynolds, M., … Schantz, S. L. (2025). Association between prenatal exposures to per- and polyfluoroalkyl substances and early language development in the ECHO cohort. NeuroToxicology, 111, 103309. https://doi.org/10.1016/j.neuro.2025.103309

Gao, Y. (2025). Digital Divide in Spanish Education: Journal of Cases on Information Technology, 27(1). https://doi.org/10.4018/JCIT.387080

Gómez-Corona, C. (2025). Culture, Gender and Socioeconomical Perspectives Across Latin American Consumers. Dalam Reference Module in Food Science. Elsevier. https://doi.org/10.1016/B978-0-443-29139-5.00035-5

Hasnine, M. N. (2025). Multimedia annotations and modalities integration in vocabulary learning systems in pre-AI days: A review and appraisal. 29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2025), 270, 4263–4273. https://doi.org/10.1016/j.procs.2025.09.551

Hsu, T.-C., Wen, W.-N., Liao, C.-S., Tu, Y.-F., & Lee, M.-J. (2025). Virtual reality in P-12 education for improving presence, immersion, and 4C skills: A systematic review of empirical research. Thinking Skills and Creativity, 58, 101918. https://doi.org/10.1016/j.tsc.2025.101918

Ibrahim, S. T., Li, M., Patel, J., & Katapally, T. R. (2025). Utilizing natural language processing for precision prevention of mental health disorders among youth: A systematic review. Computers in Biology and Medicine, 188, 109859. https://doi.org/10.1016/j.compbiomed.2025.109859

Ireland, S., Bukulatjpi, D. Y., Bukulatjpi, E. D., Gundjarra?buy, R., Adair, R., Roe, Y., Moore, S., Kildea, S., & Maypilama, E. ?äwurrpa. (2024). Djäkamirr: Exploring principles used in piloting the training of First Nations doulas in a remote multilingual Northern Australian community setting. Women and Birth, 37(3), 101573. https://doi.org/10.1016/j.wombi.2023.12.007

Jiang, S., Numtong, K., & Wang, H. (2025). Machine Learning Analysis of China’s Digital Knowledge Transfer: International Journal of Customer Relationship Marketing and Management, 16(1). https://doi.org/10.4018/IJCRMM.390273

Kejriwal, J., & Be?uš, Š. (2025). Lexical, syntactic, semantic and acoustic entrainment in Slovak, Spanish, English, and Hungarian: A cross-linguistic comparison. Speech Communication, 171, 103240. https://doi.org/10.1016/j.specom.2025.103240

Lazi?, J., & Vujnovi?, S. (2025). Influence of the surprisal power adjustment on spoken word duration in emotional speech in Serbian. Computer Speech & Language, 94, 101803. https://doi.org/10.1016/j.csl.2025.101803

Li, H., & Yoon, S. J. (2024). Anchoring in the meso-level: Departmental preparation for the adoption of blended learning in tertiary education. System, 121, 103239. https://doi.org/10.1016/j.system.2024.103239

Luo, X., Li, Y., Huang, Q., & Zhan, J. (2024). A survey of automated negotiation: Human factor, learning, and application. Computer Science Review, 54, 100683. https://doi.org/10.1016/j.cosrev.2024.100683

Maras, K., Kriss, K., Cumming, T. M., & Hoenig, J. F. (2025). Engaging in a community of practice in visual arts: A systematic literature review. International Journal of Educational Research, 133, 102752. https://doi.org/10.1016/j.ijer.2025.102752

Moorhouse, B. L., & Kohnke, L. (2024). The effects of generative AI on initial language teacher education: The perceptions of teacher educators. System, 122, 103290. https://doi.org/10.1016/j.system.2024.103290

Mukhtar, A., Hadwiger, M., Wotawa, F., & Schweiger, G. (2025). Reproducibility of machine learning-based fault detection and diagnosis for HVAC systems in buildings: An empirical study. Energy and AI, 22, 100658. https://doi.org/10.1016/j.egyai.2025.100658

Wiboolyasarin, W., Wiboolyasarin, K., Tiranant, P., Jinowat, N., & Boonyakitanont, P. (2025). AI-driven chatbots in second language education: A systematic review of their efficacy and pedagogical implications. Ampersand, 14, 100224. https://doi.org/10.1016/j.amper.2025.100224

Wuttiphan, N., & Kwangmuang, P. (2025). Designing a ubiquitous learning environment to enhance pre-service Chinese language teachers’ critical writing skills: A developmental research approach. Teaching and Teacher Education, 155, 104921. https://doi.org/10.1016/j.tate.2024.104921

Xia, Z., Lyu, S., Chen, C.-H., & Liu, B. (2024). An interpretable English reading proficiency detection model in an online learning environment: A study based on eye movement. Learning and Individual Differences, 109, 102407. https://doi.org/10.1016/j.lindif.2023.102407

Xu, C., Gao, F., & Han, L. (2025). Enhancing user information disclosure intention in dynamic conversations of intelligent recommendation systems based on large language models: A perspective of user gratification and privacy calculus. International Journal of Human-Computer Studies, 200, 103511. https://doi.org/10.1016/j.ijhcs.2025.103511

Yong, L. (2024). Simulation of E-learning video recommendation based on virtual reality environment on English teaching platform. Entertainment Computing, 51, 100757. https://doi.org/10.1016/j.entcom.2024.100757

Yoon, S., & Kim, H. Y. (2025). Exploring factors influencing the adoption and usage of ChatGPT: Internet usage patterns in South Korea. Computers in Human Behavior Reports, 20, 100866. https://doi.org/10.1016/j.chbr.2025.100866

Yordudom, T., Boonkaew, S., Imjai, N., Moghadas, S., Khuadthong, B., & Aujirapongpan, S. (2025). Developing career intention of Gen Z hospitality students: The roles and matters of experiential learning, problem-solving skills, positive thinking skills and adaptability skills. Journal of Hospitality, Leisure, Sport & Tourism Education, 37, 100560. https://doi.org/10.1016/j.jhlste.2025.100560

Yu, H.-T., Lei, C., Ge, Y., Duan, Y., Liu, X., Lynden, S., Kim, K., Matono, A., & Jatowt, A. (2025). Estimating the plausibility of commonsense statements by novelly fusing large language model and graph neural network. Information Processing & Management, 62(4), 104146. https://doi.org/10.1016/j.ipm.2025.104146

Zhang, X., Chen, M., & Huang, Y. (2025). Who gets to use the street? Evaluate the utilization and inclusiveness using crowdsourced videos and vision-language models. Sustainable Cities and Society, 134, 106906. https://doi.org/10.1016/j.scs.2025.106906

Zhui, L., Yhap, N., Liping, L., Zhengjie, W., Zhonghao, X., Xiaoshu, Y., Hong, C., Xuexiu, L., & Wei, R. (2024). Impact of Large Language Models on Medical Education and Teaching Adaptations. JMIR Medical Informatics, 12. https://doi.org/10.2196/55933

Authors

Ishak Bagea
ishakbagea41@gmail.com (Primary Contact)
Jack Davis
Emilie Bernard
Bagea, I. ., Davis, J. ., & Bernard, E. (2026). Globalizing Language Learning with Multicultural Sensitivity: How Ubiquitous Learning Technologies Support Cross-Cultural Language Acquisition. International Journal of Language and Ubiquitous Learning, 4(2), 84–95. https://doi.org/10.70177/ijlul.v4i2.3394

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