Voices of English major students in Literary Criticism course in the age of Artificial Intelligence
Authors
-
Weena Mae G. Ampo
weenamae.ampo@bisu.edu.ph
Bohol Island State University, Tagbilaran, Philippineshttps://orcid.org/0000-0002-1526-0257
DOI:
10.46223/HCMCOUJS.soci.en.16.5.3838.2026Keywords:
analytical thinking; artificial intelligence; interpretive skills; literary criticism; over-relianceAbstract
Artificial Intelligence (AI) has transformed students’ approach to learning; however, most of the literature focuses on education, with less attention given to student perceptions of AI in the humanities, particularly in literary criticism. This study investigates the experiences of ten 4th-year BSEd English majors from the College of Teacher Education to understand how AI impacts their engagement in analyzing literary works. This phenomenological study uses semi-structured interviews to determine how AI shapes students’ learning experiences, with a focus on its impact on creativity and analytical thinking. Participants were purposively selected based on their enrollment in the Literary Criticism course and prior use of AI for writing-related tasks. Key findings indicate the positive and negative impacts of AI on students. Generally, students perceive AI positively as it aids in identifying analytical patterns and forming clear assumptions about the texts. Students also emphasize the importance of verifying AI-generated information to ensure accuracy in their interpretations. However, a concerning trend emerges, as some students tend to over-rely on AI. This reliance may impact their confidence in constructing independent analysis, suggesting a risk to their critical and interpretive thinking. Hence, there is a need for educational interventions to guide students in using AI responsibly. The study primarily addresses the United Nations Sustainable Development Goal (UN SDG) 4 on Quality Education by promoting responsible technology integration. The importance of developing critical thinking, analytical skills, and autonomy in learning-core components of quality education essential in the humanities and literature studies.
Downloads
Download data is not yet available.References
Akuamoah-Boateng, K., Banguti, P., Starling, D. I., Mvukiyehe, J. P., Moses, B., Tuyishime, E., Samanta, D., Umuhire, O. F., & Bethea, A. (2019). 1383: Effect of implementing a fundamental critical care support course in emerging critical care systems. Lippincott Williams & Wilkins, 48(1), 668-668. https://doi.org/10.1097/01.ccm.0000645448.53777.6f
BaHammam, A. S., Alrajeh, S., & Al-Jahdali, H. (2023). Artificial intelligence applications in sleep medicine: Current trends and future perspectives. Nature and Science of Sleep, 15, 1-11.
Beghetto, R. A., Kaufman, J. C., & Hatcher, R. (2016). Applying creativity research to cooking. The Journal of Creative Behavior, 50, 71-77. https://doi.org/10.1002/jocb.124
Bevilacqua, M., Oketch, K., Qin, R., Stamey, W., Zhang, X., Gan, Y., Yang, K., & Abbasi, A. (2023). When automated assessment meets automated content generation: Examining text quality in the era of GPTs. https://doi.org/10.48550/arxiv.2309.14488
Binns, R. (2018). Algorithmic accountability and public reason. Philosophy & Technology, 31(4), 543-556. https://doi.org/10.1007/s13347-017-0263-5
Blue, E. V. (2012). Reading and interpretive response to literary text: Drawing upon sociocultural perspective. Taylor & Francis, 28(2), 164-178. https://doi.org/10.1080/10573569.2012.651077
Bulut, O., Beiting-Parrish, M., Casabianca, J. M., Slater, S. C., Jiao, H., Song, D., Ormerod, C. M., Fabiyi, D. G., Ivan, R., Walsh, C., Rios, O., Wilson, J. M., Yildirim‐Erbasli, S. N., Wongvorachan, T., Liu, J. X., Tan, B., & Morilova, P. (2024). The rise of artificial intelligence in educational measurement: Opportunities and ethical challenges. https://doi.org/10.48550/arxiv.2406.18900
Carr, N. (2016). The shallows: What the Internet is doing to our brains. https://doi.org/10.1080/01972243.2013.758481
Chen, L., & Zhao, Y. (2021). Impacts of AI in language learning: Student perspectives on efficiency and ease of use. Journal of Educational Technology & Society, 24(1), 34-47.
Choi, J. (2023). AI and cognitive offloading: Implications for creative tasks in the humanities. Journal of Educational Technology, 45(2), 134-148.
Davis, J. N. (1989). The act of reading in the foreign language: Pedagogical implications of Iser’s reader-response theory. Wiley, 73(4), 420-420. https://doi.org/10.2307/326877
Dong, Y. (2023). Revolutionizing academic English writing through AI-powered pedagogy: Practical exploration of teaching process and assessment. Journal of Higher Education Research, 4(2), 52-52. https://doi.org/10.32629/jher.v4i2.1188
Fraiwan, M., & Khasawneh, N. (2023). A review of ChatGPT applications in education, marketing, software engineering, and healthcare: Benefits, drawbacks, and research directions. https://doi.org/10.48550/arxiv.2305.00237
Franceschelli, G., & Musolesi, M. (2023). On the creativity of large language models. https://doi.org/10.48550/arXiv.2304.
Gill, S. S., & Kaur, R. (2023). ChatGPT: Vision and challenges. Elsevier, 3, 62-271. https://doi.org/10.1016/j.iotcps.2023.05.004
Glenn, W. J. (2007). Real writers as aware readers: Writing creatively as a means to develop reading skills. Wiley, 51(1), 10-20. https://doi.org/10.1598/jaal.51.1.2
Hammond, A. (2021). The dangers of AI in literary criticism: Losing touch with subjectivity. Literature Today, 32(1), 25-40.
Hou, X., Omar, N., & Wang, J. (2022). Interactive design psychology and artificial intelligence-based innovative exploration of Anglo-American traumatic narrative literature. Frontiers in Psychology, 12, Article 755039. https://doi.org/10.3389/fpsyg.2021.755039
Houtan, K. S. V., Gagné, T. O., Jenkins, C. N., & Joppa, L. (2020). Sentiment analysis of conservation studies captures successes of species reintroductions. Elsevier, 1, 100005-100005. https://doi.org/10.1016/j.patter.2020.100005
Jacob, S., Tate, T., & Warschauer, M. (2023). Emergent AI-assisted discourse: Case study of a second language writer authoring with ChatGPT. https://doi.org/10.48550/arxiv.2310.10903
Jockers, M. L. (2013). Macroanalysis: Digital methods and literary history. University of Illinois Press.
Ju, Q. (2023). Experimental evidence on negative impact of generative AI on scientific learning outcomes. https://doi.org/10.2139/ssrn.4567696
Júnior, E. M. D. S., & Dutra, M. L. (2021). A roadmap toward the automatic composition of systematic literature reviews. International Journal of Software and Methodologies, 1(2), 1-22. https://doi.org/10.47909/ijsmc.52
Kim, D., Joo, K., & Park, J. (2023). AI and academic integrity: Student perspectives on the ethical use of AI tools. Ethics and Education, 18(2), 147-160.
Knox, J. (2020). AI and education in the critical humanities. Learning, Media and Technology, 45(1), 1-17. https://doi.org/10.1080/17439884.2020.1694945
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. https://discovery.ucl.ac.uk/id/eprint/1475756
Marrone, R., Taddeo, V., & Hill, G. (2022). Creativity and artificial intelligence - A student perspective. Journal of Intelligence, 10(3), Article 65. https://doi.org/10.3390/jintelligence10030065
Mazzocchi, J. (2019). Sentiment analysis in narrative texts: Tracking emotional arcs and tone in literature. Digital Humanities Quarterly, 13(2).
Mello, R. F., Freitas, E. L. S. X., Pereira, F. D., Cabral, L., Tedesco, P., & Ramalho, G. (2023). Education in the age of Generative AI: Context and recent developments. https://doi.org/10.48550/arxiv.2309.12332
Mohammadkarimi, E. (2023). Teachers’ reflections on academic dishonesty in EFL students’ writings in the era of artificial intelligence. Journal of Applied Learning & Teaching, 6(2). https://doi.org/10.37074/jalt.2023.6.2.10
Mollick, E., & Mollick, L. (2023). Assigning AI: Seven approaches for students, with prompts. https://doi.org/10.2139/ssrn.4475995
Moretti, F. (2013). Digital scholarship in the humanities. Journal Alliance of Digital Humanities Organizations, 30(1), 152-154. https://doi.org/10.1093/llc/fqu010
Murdoch, W. J., Singh, C., Kumbier, K., Abbasi-Asl, R., & Yu, B. (2019). Definitions, methods, and applications in interpretable machine learning. National Academy of Sciences, 116(44), 22071-22080. https://doi.org/10.1073/pnas.1900654116
Murray, J. (2019). AI and the future of creativity: Implications for literary studies. Humanities and Technology Review, 28(4), 54-72.
Nguyen, T. A., Nguyen, P. H., Pham, H., Bui, T., Nguyen, T. M., & Luong, D. T. A. (2021). SP-GPT2: Semantics improvement in Vietnamese poetry generation. In Proceedings of the 20th IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 1576-1581). IEEE. https://doi.org/10.1109/icmla52953.2021.00252
Oxford Bibliographies. (2019). Literary and critical theory. https://www.oxfordbibliographies.com/display/document/obo-9780190221911/obo-9780190221911-0077.xml
Perez, R. C. L. (2024). AI in higher education: Faculty perspective towards artificial intelligence through UTAUT approach. Ho Chi Minh City Open University Journal of Science: Social Sciences, 14(4), 1-15. https://doi.org/10.46223/HCMCOUJS.soci.en.14.4.2851.2024
Piper, A. (2018). Enumerations: Data and literary study. University of Chicago Press.
Raj, A. V., Udayakumar, M. U., & Saravanan, M. D. (2023). Integrating artificial intelligence in English literature: Exploring applications, implications, and ethical considerations. International Journal of Advanced Research in Science, Communication and Technology, 3(1), 11-15. https://doi.org/10.48175/ijarsct-12003
Rockwell, G., & Sinclair, S. (2016). Hermeneutica: Computer-assisted interpretation in the humanities. https://doi.org/10.7551/mitpress/9522.001.0001
Schwartz, H. J. (1989). Literacy theory in the classroom: Computers in literature and writing. Elsevier BV, 7(1), 49-63. https://doi.org/10.1016/s8755-4615(89)80006-4
Silberman, M., & Holub, R C. (1984). Review of the book reception theory: A critical introduction. New German Critique, (33), 249-254. https://doi.org/10.2307/488364
Srinivasan, V., & Murthy, H. (2021). Improving reading and comprehension in K-12: Evidence from a large-scale AI technology intervention in India. Computers and Education: Artificial Intelligence, 2, Article 100019.
Swisher, C. N., & Shamir, L. (2023). A data science and machine learning approach to continuous analysis of Shakespeare’s plays. Journal of Data Mining & Digital Humanities, Article 10829. https://doi.org/10.46298/jdmdh.10829
Underwood, T. (2019). Distant horizons: Digital evidence and literary change. https://doi.org/10.7208/chicago/9780226612973.001.0001
Wagner, P., Niesen, T., & Sagerer, G. (2021). Artificial intelligence in education: Challenges and opportunities for teaching and learning. International Journal of Learning Analytics and Artificial Intelligence for Education, 3(1), 5-19.
Wang, T., Lund, B., Marengo, A., Pagano, A., Mannuru, N. R., Teel, Z. A., & Pange, J. (2023). Exploring the potential impact of Artificial Intelligence (AI) on international students in higher education: Generative AI, Chatbots, analytics, and international student success. Multidisciplinary Digital Publishing Institute, 13(11), 6716-6716. https://doi.org/10.3390/app13116716
Williams, T., & Black, J. (2022). Instructor support in AI adoption: Effects on student attitudes toward educational technology. British Journal of Educational Technology, 53(4), 967-982.
Williamson, B. (2020). Big data in education: The digital future of learning, policy and practice. https://doi.org/10.1007/s42438-019-00059-6
Woo, D. J., Susanto, H., & Guo, K. (2023). EFL students’ attitudes and contradictions in a machine-in-the-loop activity system. https://doi.org/10.48550/arXiv.2307.
Zaidi, S., & Ashraf, A. (2019). Love as a deteriorative stimulus in love in the time of cholera: A reader’s response analysis. Global Social Sciences Review, IV(IV), 460-467. https://doi.org/10.31703/gssr.2019(IV-IV).56
Zhou, W. (2023). Chat GPT integrated with voice assistant as learning oral chat-based constructive communication to improve communicative competence for EFL earners. https://doi.org/10.48550/arxiv.2311.00718
Downloads
Received: 08-11-2024Accepted: 17-12-2024Published: 05-03-2025Statistics Views
Abstract: 951 PDF: 154How to Cite
Ampo, W. M. G. (2025). Voices of English major students in Literary Criticism course in the age of Artificial Intelligence. HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - SOCIAL SCIENCES, 16(5), 63–78. https://doi.org/10.46223/HCMCOUJS.soci.en.16.5.3838.2026License
Copyright (c) 2026 Weena Mae G. Ampo

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
