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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Use of AI in Teaching English Literature

Authors: Vidhate, Vishvajeet Haridas;

Use of AI in Teaching English Literature

Abstract

The use of English literature in teaching the English language has long been recognized as an effective pedagogical approach to developing linguistic competence, cultural awareness, and critical thinking skills among learners. This paper explores how literary texts—such as poetry, drama, and fiction—can be utilized to enhance language proficiency while fostering an appreciation of cultural and aesthetic values. By integrating literature into language instruction, teachers can create engaging, context-rich learning experiences that promote vocabulary development, grammar understanding, and communicative competence. The study also discusses various methods and approaches, including stylistic analysis, reader-response theory, and task-based learning, which help bridge the gap between language learning and literary appreciation. Findings suggest that when literature is used appropriately, it not only strengthens students’ language skills but also encourages empathy, creativity, and intercultural understanding. Therefore, incorporating literature into English teaching is both a linguistic and humanistic strategy that enriches the overall educational experience.

Keywords

English literature, Language teaching, Literature in language education, Teaching methodology, Language skills development, Literary texts, Cultural awareness, Communicative competence.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green