Development of An Artificial Intelligence-Based Digital Platform: Enhancing Intercultural Communication Among University Students

Authors

  • Muhammad Abiyyu De Rossi Universitas Negeri Medan
  • Mhd Agri Amri Universitas Negeri Medan
  • Rita Hartati Universitas Negeri Medan
  • Nadia Kumari Universitas Negeri Medan
  • Juniar Elfrida Sihotang Universitas Negeri Medan
  • Azzahrah Andrianti Universitas Negeri Medan

DOI:

https://doi.org/10.33096/tamaddun.v25i1.1365

Keywords:

Artificial Intelligence, intercultural communication, sociocultural, digital literacy, university students, phenomenology

Abstract

Artificial Intelligence (AI) is increasingly used to support communication and learning in culturally diverse higher-education environments. This study examined the potential of an AI-based digital platform to enhance university students’ intercultural communication competence and explored their perceptions of the platform. A quantitative pre-experimental design employing a one-group pre-test–post-test model was used with 50 undergraduate students from diverse cultural, linguistic, and regional backgrounds. Intercultural communication competence was measured before and after the AI-supported learning intervention across seven dimensions: cultural awareness, cultural empathy, respect for cultural diversity, cross-cultural communication confidence, communication adaptability, appropriate language use across cultures, and conflict management in intercultural contexts. A post-intervention questionnaire was also administered to assess students’ perceptions of the platform. Descriptive analysis showed that the overall mean intercultural communication competence score increased from 3.13 in the pre-test to 4.44 in the post-test. Post-test scores improved across all seven dimensions, with respect for cultural diversity obtaining the highest mean score (M = 4.58), while conflict management recorded the lowest post-test mean (M = 4.33). Students also reported highly positive perceptions of the platform, with an overall mean of 4.58. The findings indicate that AI-supported learning may facilitate cultural awareness, communication adaptability, culturally appropriate language use, confidence, and intercultural reflection. The study highlights the pedagogical potential of AI as a reflective communication-support tool while emphasizing that human judgment, cultural sensitivity, and critical AI literacy should remain central to intercultural learning.

References

Alharbi, W. (2024). Impact of ChatGPT on ESL students' academic writing skills: A mixed methods intervention study. Smart Learning Environments, 11, Article 12. https://doi.org/10.1186/s40561-024-00295-9

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (pp. 610–623). Association for Computing Machinery. https://doi.org/10.1145/3442188.3445922

Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide. SAGE Publications.

Byram, M. (1997). Teaching and assessing intercultural communicative competence. Multilingual Matters. https://books.google.com/books?id=0vfq8JJWhTsC

Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20, Article 38. https://doi.org/10.1186/s41239-023-00408-3

Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20, Article 43. https://doi.org/10.1186/s41239-023-00411-8

Chen, G. M., & Starosta, W. J. (1996). Intercultural communication competence: A synthesis. Annals of the International Communication Association, 19(1), 353–383.

Chen, G. M., & Starosta, W. J. (2000). The development and validation of the Intercultural Sensitivity Scale. Human Communication, 3, 1–15.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Deardorff, D. K. (2006). Identification and assessment of intercultural competence as a student outcome of internationalization. Journal of Studies in International Education, 10(3), 241–266. https://doi.org/10.1177/1028315306287002

Deardorff, D. K. (2009). The SAGE Handbook of Intercultural Competence. Sage.

Dwivedi, Y. K., Kshetri, N., Hughes, L., et al. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642

Farrell, O., & Brunton, J. (2024). A balancing act: Exploring student perspectives on generative artificial intelligence and academic writing. Computers and Education: Artificial Intelligence, 6, 100214 https://doi.org/10.1016/j.caeai.2024.100214

Grassini, S. (2023). Shaping the future of education: Exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13(7), 692. https://doi.org/10.3390/educsci13070692

Hancock, J. T., Naaman, M., & Levy, K. (2020). AI-mediated communication: Definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication, 25(1), 89–100. https://doi.org/10.1093/jcmc/zmz022

Hohenstein, J., Kizilcec, R. F., DiFranzo, D., Aghajari, Z., Mieczkowski, H., Levy, K., Naaman, M., Hancock, J., & Jung, M. F. (2023). Artificial intelligence in communication impacts language and social relationships. Scientific Reports, 13, Article 5487. https://doi.org/10.1038/s41598-023-30938-9

Hu, Y. (2025). Generative AI, communication, and stereotypes: Learning critical AI literacy through experience, analysis, and reflection. Communication Teacher, 39(1), 6–12. https://doi.org/10.1080/17404622.2024.2397065

Johnston, H., Wells, R. F., Shanks, E. M., Boey, T., & Parsons, B. N. (2024). Student perspectives on the use of generative artificial intelligence technologies in higher education. International Journal for Educational Integrity, 20, Article 2. https://doi.org/10.1007/s40979-024-00149-4

Joshi, P., Santy, S., Budhiraja, A., Bali, K., & Choudhury, M. (2020). The state and fate of linguistic diversity and inclusion in the NLP world. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 6282–6293). Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.acl-main.560

Kasneci, E., Sessler, K., Küchemann, S., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54(2), 537–550. https://doi.org/10.1177/00336882231162868

Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–16). Association for Computing Machinery. https://doi.org/10.1145/3313831.3376727

Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://doi.org/10.54675/EWZM9535

Molenaar, I. (2022). Towards hybrid human–AI learning technologies. European Journal of Education, 57(4), 632–645. https://doi.org/10.1111/ejed.12527

Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, Article 100041. https://doi.org/10.1016/j.caeai.2021.100041

O’Dowd, R. (2021). Virtual exchange: Moving forward into the next decade. Computer Assisted Language Learning, 34(3), 209–224. https://doi.org/10.1080/09588221.2021.1902201

Passantino, F. (2024). AI-powered communication for intercultural education. Intercultural Education, 35(1), 104–110. https://doi.org/10.1080/14675986.2024.2307701

Qin, X. (2024). Evaluating intercultural learning materials from the RICH-Ed project through a non-essentialist perspective: Chinese university students' and instructors' perceptions. Asia-Pacific Journal of Teacher Education, 53(1), 17–49. https://doi.org/10.1080/1359866X.2024.2411598

Song, C., & Song, Y. (2023). Enhancing academic writing skills and motivation: Assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in Psychology, 14, Article 1260843. https://doi.org/10.3389/fpsyg.2023.1260843

Spitzberg, B. H. (2000). A model of intercultural communication competence. In Intercultural Communication: A Reader (9th ed., pp. 375–387). Wadsworth. https://doi.org/10.1080/23808985.1996.11678935

Spitzberg, B. H., & Cupach, W. R. (1984). Interpersonal Communication Competence. Sage.

Tao, Y., Viberg, O., Baker, R. S., & Kizilcec, R. F. (2024). Cultural bias and cultural alignment of large language models. PNAS Nexus, 3(9), pgae346. https://doi.org/10.1093/pnasnexus/pgae346

Ting-Toomey, S., & Kurogi, A. (1998). Facework competence in intercultural conflict: An updated face-negotiation theory. International Journal of Intercultural Relations, 22(2), 187–225. https://doi.org/10.1016/S0147-1767(98)00004-2

Waltzer, T., Pilegard, C., & Heyman, G. D. (2024). Can you spot the bot? Identifying AI-generated writing in college essays. International Journal for Educational Integrity, 20, Article 11.

Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: A systematic review. Smart Learning Environments, 11, Article 28. https://doi.org/10.1186/s40561-024-00316-7

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Published

2026-09-16

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Section

Research

How to Cite

Development of An Artificial Intelligence-Based Digital Platform: Enhancing Intercultural Communication Among University Students. (2026). Tamaddun, 25(1), 202-216. https://doi.org/10.33096/tamaddun.v25i1.1365