Fuzzy Sentiment Analysis for Improving German Learning in Corpus-Based Deep Learning Approaches

محفوظ في:
التفاصيل البيبلوغرافية
الحاوية / القاعدة:International Journal of Web-Based Learning and Teaching Technologies vol. 20, no. 1 (2025), p. 1-23
المؤلف الرئيسي: Dong, Qi
منشور في:
IGI Global
الموضوعات:
الوصول للمادة أونلاين:Citation/Abstract
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الوصف
مستخلص:This study aims to explore how to optimize corpus-based deep learning methods by introducing fuzzy sentiment analysis technology to improve the effectiveness and interactivity of German learning. By building an intelligent tutoring system that can perceive the emotional state of German learners, the effectiveness and interactivity of learning can be improved. Experimental results show that the fuzzy sentiment classifier has significant advantages in language skill improvement, user satisfaction, learning motivation, and sustained engagement. Fuzzy sentiment analysis technology can capture and process learners' emotional states more delicately, provide personalized feedback and support, and identify individual learning patterns and preferences based on long-term accumulated data, thereby recommending customized learning paths.
تدمد:1548-1093
1548-1107
DOI:10.4018/IJWLTT.383940
المصدر:Engineering Database