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<p>English literature teaching can improve students’ literary literacy and English proficiency. In this paper, we preprocess the English literature teaching data in colleges and universities from the two modalities of visual information and auditory information, extract the features of auditory modality, text modality, and video modality of the classroom respectively, and represent the features using bidirectional long-time memory neural network. A multilayer attention network mechanism is introduced to complete multimodal fusion in English literature teaching and label multimodal features after the extraction is done. On this basis, a student-centered innovative teaching path for English literature in colleges and universities is constructed, and teaching practice and multimodal discourse analysis are carried out to explore its teaching effect. The results show that the length of time used for facial smiles in inefficient classrooms (780.52/s) is significantly more than that in inefficient classrooms (150.22/s), and the length of time used for eye interactions (832.63/s) is significantly more than that in inefficient classrooms (720.44/s), and the length of time used for animations (450.42/s) is significantly more than that in inefficient classrooms (128.88/s), and efficient classrooms are more emphasized on student interactions. Students’ reading and writing abilities were significantly different from those before the practice (P&lt;0.05). This study suggests that promoting innovation in teaching English literature in colleges and universities can have a positive practical significance.</p>
</abstract>

English literature teaching can improve students’ literary literacy and English proficiency. In this paper, we preprocess the English literature teaching data in colleges and universities from the two modalities of visual information and auditory information, extract the features of auditory modality, text modality, and video modality of the classroom respectively, and represent the features using bidirectional long-time memory neural network. A multilayer attention network mechanism is introduced to complete multimodal fusion in English literature teaching and label multimodal features after the extraction is done. On this basis, a student-centered innovative teaching path for English literature in colleges and universities is constructed, and teaching practice and multimodal discourse analysis are carried out to explore its teaching effect. The results show that the length of time used for facial smiles in inefficient classrooms (780.52/s) is significantly more than that in inefficient classrooms (150.22/s), and the length of time used for eye interactions (832.63/s) is significantly more than that in inefficient classrooms (720.44/s), and the length of time used for animations (450.42/s) is significantly more than that in inefficient classrooms (128.88/s), and efficient classrooms are more emphasized on student interactions. Students’ reading and writing abilities were significantly different from those before the practice (P<0.05). This study suggests that promoting innovation in teaching English literature in colleges and universities can have a positive practical significance.

Research on Innovative Teaching Path of English Literature in Colleges and Universities Based on Multimodal Discourse Analysis

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

English literature teaching can improve students’ literary literacy and English proficiency. In this paper, we preprocess the English literature teaching data...

Research on Innovative Teaching Path of English Literature in Colleges and Universities Based on Multimodal Discourse Analysis

Online veröffentlicht: 31. Jan. 2024

Seitenbereich: -

Eingereicht: 22. Dez. 2023

Akzeptiert: 27. Dez. 2023

DOI: https://doi.org/10.2478/amns-2024-0265

Schlüsselwörter
Feature extraction, Long-term memory neural, Multilayer attention, Multimodal discourse, English literature

© 2024 Yan Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on Innovative Teaching Path of English Literature in Colleges and Universities Based on Multimodal Discourse Analysis

Online veröffentlicht: 31. Jan. 2024

Seitenbereich: -

Eingereicht: 22. Dez. 2023

Akzeptiert: 27. Dez. 2023

DOI: https://doi.org/10.2478/amns-2024-0265

SchlüsselwörterFeature extraction, Long-term memory neural, Multilayer attention, Multimodal discourse, English literature

© 2024 Yan Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Feature extraction, Long-term memory neural, Multilayer attention, Multimodal discourse, English literature