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A Hybrid Fuzzy Logic and Deep Learning Model for Corpus-Based German Language Learning with NLP

Sparad:
I publikationen:Informatica vol. 49, no. 21 (May 2025), p. 1-15
Huvudupphov: Wang, Bo
Utgiven:
Slovenian Society Informatika / Slovensko drustvo Informatika
Ämnen:
Language acquisition
Comprehension
Deep learning
Fuzzy logic
Artificial neural networks
Language instruction
Neural networks
Syntactic analysis
Machine learning
Teaching methods
Pattern recognition
Accuracy
Vocabulary learning
Sentiment analysis
Learning outcomes
Decision making
Natural language processing
Effectiveness
Students
German language
Language proficiency
Experiments
Reading comprehension
Learning
Student participation
Teaching
Logic
Vocabulary
Uncertainty
Satisfaction
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Abstrakt:This study proposes and implements a German learning system based on a hybrid fuzzy-neural model, aiming to enhance the language acquisition efficiency of German learners by integrating the strengths of fuzzy logic in handling uncertainty with those of deep neural networks for complex pattern recognition. Through detailed computational experiments, the hybrid model achieved significant improvements over traditional and baseline methods, with key results including vocabulary acquisition accuracy of 90.5% ± 1.2%, syntactic analysis accuracy of 88.7% ± 1.6%, sentiment analysis accuracy of 92.1% ± 1.3%, and a reading comprehension BLEU score of 42.3 ± 1.5%. Students in the experimental group showed substantial gains from pre-test (75.8 ± 5.2) to post-test (88.3 ± 4.1), achieving an average improvement of 12.5 points compared to the control group's 5.9-point increase. Additionally, the experimental group rated the teaching content as rich and diverse (4.7/5), found the teaching methods interesting and effective (4.5/5), felt it helped improve their language skills (4.8/5), and considered it easy to learn independently (4.6/5), with overall satisfaction at 4.7/5. These findings highlight the hybrid fuzzy-neural model's effectiveness in enhancing both learning outcomes and student engagement in German language education.
ISSN:0350-5596
1854-3871
DOI:10.31449/inf.v49i21.7423
Källa:Advanced Technologies & Aerospace Database