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Use of Artificial Intelligence in Teaching English Literature

Authors: Badale, Jagannath Dnyanoba; Shinde, Abhay;

Use of Artificial Intelligence in Teaching English Literature

Abstract

The present Article discusses the use of Artificial Intelligence (AI) in teaching English literature and its advantages as well as limitations. In today’s digital age, technology is increasingly shaping teaching methodologies. Particularly in the teaching of English literature, AI has emerged as an effective tool. Literature education is not limited to reading and writing; it involves studying language, analysing themes, understanding symbolism, and fostering creative thinking. AI-based tools guide both teachers and students through this process, making learning more effective and creative. The use of artificial intelligence in literature teaching proves to be highly beneficial for innovation and efficiency in academic practice. Through AI-powered tools, students can easily grasp the meaning, themes, symbolism, and perspective of authors. It also helps in preparing summaries, questions, and theme-based discussions after classroom reading. Thus, the application of AI in teaching English literature is proving to be advantageous. However, like any advanced technology, along with its benefits, AI also brings certain challenges. This Article attempts to analyse both dimensions in detail.

Keywords

Artificial Intelligence (AI), English Literature Teaching, Digital Pedagogy, Personalized Learning, Literary Analysis, Future Prospects of AI in Education.

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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