FunChinese App: Platform Development and Application Based on Generative Artificial Intelligence Technology

Chen Jiajing(College of International Education,Wenzhou University)
Dong Tingting(College of International Education,Wenzhou University)
Song Zhanmei(College of International Education,Wenzhou University)

Abstract

With the continued advancement of the Belt and Road Initiative, overseas Chinese-funded enterprises commonly face challenges such as insufficient Chinese communication skills, lack of intercultural competence, and inadequate knowledge of Chinese professional terminology. To address this predicament, there is an urgent need to establish a digital platform through the “Internet Plus” model and build a remote education system integrating “Chinese language + professional skills.” However, existing Chinese learning applications often suffer from content homogenization, weak cultural dissemination, and insufficient relevance to professional fields. In response to this, the present study aims to design a Chinese language learning app that focuses on enhancing language proficiency, promoting Chinese culture, and targeting professional knowledge. Based on mobile learning theory, constructivist learning theory, and autonomous learning theory, and guided by principles of practicality and personalization, the app integrates gamified incentive mechanisms and AI-driven interactive features. It constructs a three-dimensional model of “level-based learning + cultural immersion + real-time PK (competition),” achieving a deep integration of linguistic knowledge, intercultural communication skills, and industry-specific expertise.

Keywords

Mobile learning software; APP; “Chinese + Professional Skills”

References

Wu Y, Liang Y, Guo J,et al.,2021. The status and prospects of global Chinese‑teaching resources. Journal of Yunnan Normal University (Teaching Chinese as a Foreign Language & Research Edition), 19(5):1–6.

Guo J, Wu Y, Gu L,et al.,2021. On the construction status and prospects of digital resources for international Chinese education. International Chinese Teaching Research, (4):86–96.

Cheng J, & Lu Y.,2020. An inquiry into the current status of apps for learning Chinese as a foreign language. Journal of East China University of Technology (Social Sciences Edition), 39(4):384–389.

Sheng S,2017. Investigation and application analysis of Chinese‑learning apps (Master thesis). Shandong: Shandong University.

Jordan M I, Mitchell T M.,2015. Machine learning: Trends, perspectives, and prospects. Science, 349(6245):255–260.

Jurafsky D, Martin J H.,2008. Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition. Prentice Hall.

LeCun Y, Bengio Y, Hinton G.,2025. Deep learning. Nature, 521(7553):436–444.

Shen J, et al.,2017. Natural TTS synthesis by conditioning WaveNet on mel spectrogram predictions. arXiv preprint arXiv:1712.05884.

Li T.,2021. Application of TTS technology in online teaching of Chinese as a foreign language. In Proceedings of the 2021 3rd International Conference on Internet Technology and Educational Informatization (ITEI) (pp. 38–41).

Rombach R, et al.,2021. High‑resolution image synthesis with latent diffusion models. arXiv preprint arXiv:2112.10752.

Liu R, et al.,2024. The application of scaffolding instruction and AI‑driven diffusion models in children’s aesthetic education: A case study on teaching traditional Chinese painting of the twenty‑four solar terms. Education and Information Technologies.

Radianti J, et al.,2020. A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda. Computers & Education, 147, 103778.

Klašnja‑Milićević A, et al.,2011. E‑learning personalization based on hybrid recommendation strategy and learning style identification. Computers & Education, 56(3):885–899.

Brown T B, et al.,2020. Language models are few‑shot learners. arXiv preprint arXiv:2005.14165.

Vaswani A, et al.,2017. Attention is all you need. In Advances in Neural Information Processing Systems (Vol. 30, pp. 6000–6010).

DOI: http://dx.doi.org/10.12345/ret.v8i2.33857