Design and Evaluation of Computer Assisted Chinese Second Language Acquisition Teaching Model

Abstract In the context of accelerated globalization today, computer-assisted language learning (CALL), as an emerging teaching force, is gradually showing its importance in the field of teaching Chinese as a second language (L2), winning widespread attention and being adopted in practice. The CALL mode not only pushes the application of information technology in language learning to new heights, achieving integration and innovation, but also emphasizes the updating of teaching methods, optimization of teaching tools, and structure of high-quality teaching resources and learning environments. This article proposes an innovative Chinese language teaching system supported by CALL technology, which deeply integrates deep learning (DL) technology and can intelligently analyze students' learning behavior, interests, and ability status, thereby providing customized learning resource recommendations. The system further utilizes big data analysis technology and has the function of predicting learning outcomes, which can evaluate students' learning performance in advance and provide data support for teachers' teaching strategy adjustments and students' learning planning optimization. Experimental results have shown that the system properly enhances the learning efficiency of Chinese second language learners, stimulates their learning interest, and comprehensively promotes the improvement of language abilities.