Application and Evaluation of AI-Based Mobile Learning Platforms for Enhancing English Writing Proficiency.
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| Title: | Application and Evaluation of AI-Based Mobile Learning Platforms for Enhancing English Writing Proficiency. |
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| Authors: | Wang, Xiujuan1, Fang, Lanlan2 fanglanlan1982@163.com |
| Source: | International Journal of Interactive Mobile Technologies. 2026, Vol. 20 Issue 8, p50-64. 15p. |
| Subjects: | English language writing, Human-artificial intelligence interaction, Second language acquisition, Natural language processing, Design science, Mobile learning, Affective computing |
| Abstract: | In the context of globalization, English writing has become a core skill in second language acquisition (SLA), with increasing demand. The fragmented and contextualized advantages of mobile learning provide new possibilities for enhancing writing skills. However, existing AI writing support tools generally suffer from two major gaps: a lack of personalized interaction and insufficient support for deep skill development. To address these issues, this paper proposes a personalized writing support model driven by human-AI interaction (HII). The model integrates AI technologies such as natural language processing (NLP), affective computing, and context awareness to create an English writing learning platform tailored for mobile learning environments. This platform enables a full-process intelligent interaction involving "intent recognition, real-time feedback, dynamic adaptation, and cognitive guidance." A mixed research method was employed: the platform's iterative development and optimization were guided by Design Science Research (DSR), while a quasi-experimental study was conducted with 120 English as a foreign language (EFL) learners at different proficiency levels. The experiment included an experimental group and a control group, and evaluation was based on multiple data sources, including writing texts, interaction behaviors, and user perceptions. The empirical results indicate that the experimental group scored significantly higher than the control group in three core dimensions: logical coherence of writing content, linguistic accuracy, and textual coherence. Additionally, the HII module had a substantial positive effect on learning motivation, error correction efficiency, and metacognitive ability. The "technology-teaching-assessment" integrated theoretical framework constructed in this paper enriches the empirical research on HII in mobile learning environments and provides an interdisciplinary research model for the deep integration of AI educational technology and second language writing instruction. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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