Enhanced text clustering and sentiment analysis framework for online education: a BIF-DCN approach in computer education.

ABSTRACT: Understanding students' emotional responses to course content and assignments is crucial for developing effective teaching strategies and improving online learning resources. To address this need, we propose a novel deep learning-based framework called BERT and BTF-IDF Integrated Framework with Deep Clustering Network (BIF-DCN), designed to accurately analyze student sentiment on educational platforms. The framework combines three key components: Bidirectional Encoder Representations from Transformers (BERT) for initial text feature extraction, Bi-level Term Frequency-Inverse Document Frequency (BTF-IDF) for enhanced feature representation, and an Improved Deep Embedded Clustering (IDEC) model for sentiment classification. BERT captures rich semantic features from student comments, which a

SUBMITTER: Zhang Q 

PROVIDER: S-EPMC12453793 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature