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Teaching Literature (in the Age of Generative Machines): An Exploration of the Not-so-New Relationalities of Readers and Literary Texts in Schools
- Source :
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ProQuest LLC . 2024Ph.D. Dissertation, Columbia University. - Publication Year :
- 2024
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Abstract
- ChatGPT and generative AI technologies have infiltrated our learning spaces, and, as a result, schools may be changed forever. While some educators may seek to ban the use of chatbots, motivated by a fear of the rampant plagiarism the technology might invite, I, however, write this dissertation with the intent of finding uses for AI as a participant in the teaching and learning of literature in the secondary and post-secondary English classroom. In this dissertation, I examine a series of problems, issues, and ideas raised by AI, situated in specific relationalities among readers and literary texts (students, teachers, and myself functioning as my main sites of inquiry) by engaging in literature-based experiments. Through reflecting on my experiences and experimenting alongside teachers, students, and AI, I have found that the problems and opportunities introduced by AI are not-so-new: they're a re-presentation of the familiar, repackaged and amplified. Though this dissertation has not lent itself to the discovery of a singular conclusion, I have found, rather, grounds for further experimentation and provocation. As I conclude this dissertation, I attempt to identify some ways that teachers of English can utilize AI not as a tool for providing knowledge and information for students, but to rather utilize it as a thought-provoking companion for the teaching of literature. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
Details
- Language :
- English
- ISBN :
- 979-83-8280-982-3
- ISBNs :
- 979-83-8280-982-3
- Database :
- ERIC
- Journal :
- ProQuest LLC
- Publication Type :
- Dissertation/ Thesis
- Accession number :
- ED657168
- Document Type :
- Dissertations/Theses - Doctoral Dissertations