Generative AI in Creative Writing Pedagogy: Opportunities, Authorship Dilemmas, and Ethical Boundaries in Higher Education
DOI:
https://doi.org/10.21590/ijtmh20230904024Keywords:
Generative AI; Creative writing pedagogy; Authorship; Academic integrity; Higher education; Large language models; Assessment design; AI ethicsAbstract
Large language models capable of fluent narrative, poetry, and dialogue have entered the creative writing classroom faster than institutions have been able to reason about them. Responses so far cluster at two unsatisfying poles: prohibition, which is unenforceable and pedagogically evasive, and uncritical adoption, which risks hollowing out the very capacities creative writing programmes exist to develop. This paper charts a middle path. We first distinguish the pedagogical functions of creative writing instruction — craft acquisition, voice development, critical reading, revision discipline, and creative confidence — and analyse how generative AI interacts with each, showing that its effects are function-specific rather than uniformly beneficial or harmful. We then map legitimate instructional use cases (ideation partner, style laboratory, revision interlocutor, pastiche and parody object, workshop simulator) against their characteristic risks, including voice displacement, authorship ambiguity, homogenisation of style, and assessment distortion, and propose safeguards for each in a structured framework. Finally, we articulate boundary conditions — uses that should remain out of bounds in credit-bearing creative work — and a disclosure-based assessment architecture that makes process, not artefact, the primary object of evaluation. The paper offers writing programmes a principled basis for policy that is enforceable, teachable, and honest about both the promise and the cost of writing with machines.
References
1. C. H. Neetha and M. P. Kantipudi, “Adaptive Edge-Based Bilinear Interpolation for Smart Healthcare,” in IET Conference Proceedings CP824, vol. 2022, no. 26, Stevenage, U.K.: The Institution of Engineering and Technology (IET), 2022, pp. 7–13.
2. R. Aluvalu, R. Venkatachalam, V. Uma Maheswari, R. J. Anandhi, M. V. V. Kantipudi, and S. Prashanth Mallellu, “IWHO-Based Cluster Head Selection for Vehicle-to-Vehicle Communication in Intelligent Transport System,” International Journal of Transport Development and Integration, vol. 8, no. 2, pp. 154–166, 2024
3. S. Velamuri, S. K. Sudabattula, M. V. V. Prasad Kantipudi, and N. Prabaharan, “Q-Learning Based Commercial Electric Vehicles Scheduling in a Renewable Energy Dominant Distribution Systems,” Electric Power Components and Systems, pp. 1–14, 2023
4. Singh, M., Rallabandi, B., Gattupalli, K. K., & Sai Medarametla, M. (2025). Autonomous private 5G field area networks: Achieving secure, scalable, and self-healing smart grid communications. In 2025 2nd International Conference on Recent Trends in Electrical, Electronics and Computing Technologies (ICRTEECT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICRTEECT67512.2025.11448712
5. Desai, A. B., Rallabandi, B., Gattupalli, K. K., & Medarametla, M. S. (2025). Agentic AI for rural connectivity and spectrum-aware networks to power smart agriculture ecosystems. In 2025 2nd International Conference on Recent Trends in Electrical, Electronics and Computing Technologies (ICRTEECT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICRTEECT67512.2025.11448879
6. Goyal, S., Rallabandi, B., Gattupalli, K. K., & Medarametla, M. S. (2025). Digital twin-enabled context-aware networks: Enhancing smart grid resilience through predictive intelligence. In 2025 2nd International Conference on Recent Trends in Electrical, Electronics and Computing Technologies (ICRTEECT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICRTEECT67512.2025.11448880
7. Tripathi, N., Gattupalli, K. K., Rallabandi, B., & Medarametla, M. S. (2025). AI-native Cloud-RAN orchestration for enterprise private 5G using digital twin models. In 2025 1st IEEE Uttar Pradesh Section Women in Engineering International Conference on Electrical Electronics and Computer Engineering (UPWIECON) (pp. 851–857). IEEE. https://doi.org/10.1109/UPWIECON67212.2025.11390348
8. Goyal, S., Gattupalli, K. K., Rallabandi, B., & Medarametla, M. S. (2025). Integrating terrestrial and non-terrestrial networks for reliable rural coverage in agriculture and smart grids. In 2025 1st IEEE Uttar Pradesh Section Women in Engineering International Conference on Electrical Electronics and Computer Engineering (UPWIECON) (pp. 846–850). IEEE. https://doi.org/10.1109/UPWIECON67212.2025.11390331
9. N. Pachauri, V. Suresh, M. V. V. Prasad Kantipudi, R. Alkanhel, and H. A. Abdallah, “Multi-Drug Scheduling for Chemotherapy Using Fractional Order Internal Model Controller,” Mathematics, vol. 11, no. 8, Art. no. 1779, 2023,
10. M. V. V. Prasad Kantipudi, S. Vemuri, N. S. Pradeep Kumar, S. Sreenath Kashyap, and S. Eslamian, “Proposing Model for Water Quality Analysis Based on Hyperspectral Remote Sensor Data,” in Handbook of Hydroinformatics, Elsevier, 2023, pp. 317–324.
11. Rana, M., Srinivas, S., Jamili, L. K., Jaiswal, I. A., Nakka, S., & Kasetti, S. (2025, May). Real-Time Monitoring and Prediction of Blood Sugar Levels in Diabetic Patients with Functional Models. In 2025 International Conference on Engineering, Technology & Management (ICETM) (pp. 1-6). IEEE.
12. Jaiswal, I. A. (2023). Intelligent Cybersecurity Framework for Large-Scale RESTful Service Architectures. International Journal of Research Radicals in Multidisciplinary Fields, ISSN: 2960-043X, 2 (1), 178–184. Retrieved from https://www. researchradicals. com/index. php/rr/article/view, 252.
13. Jaiswal, I. A. (2023). Multilingual and culturally adaptive AI models for global education platforms. International Journal for Research in Education (IJRE), 12(9), 17–27. https://doi.org/10.63345/ijre.v12.i9.1
14. M. S. Prashanth, R. Aluvalu, and M. V. V. Kantipudi, “Enhancing Health Product Traceability on the Blockchain: A Novel Approach for Supply Chain Management Inspection to AI,” EAI Endorsed Transactions on Pervasive Health & Technology, vol. 10, no. 1, 2024.
15. H. K. Jani, M. V. V. Prasad Kantipudi, G. Nagababu, D. Prajapati, and S. S. Kachhwaha, “Simultaneity of Wind and Solar Energy: A Spatio-Temporal Analysis to Delineate the Plausible Regions to Harness,” Sustainable Energy Technologies and Assessments, vol. 53, Art. no. 102665, 2022
16. Jaiswal, I. A. (2022). Natural language processing for security policy and log analysis. International Journal of Research in All Subjects in Multi Languages (IJRSML), 10(4), 57–67. https://doi.org/10.63345/ijrsml.v10.i4.1
17. Khan, S. (2019). Sales force security compliance: An in-depth study of GDPR, HIPAA, and PCI-DSS enforcement in cloud-based CRM systems and their implications for global enterprises. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 8(9), 2211–2219. https://doi.org/10.15662/IJAREEIE.2019.0809010
18. S. Choudhary, C. H. Kandikattu, S. Kumar, M. V. V. P. Kantipudi, and M. Kumar, “Enhancing cybersecurity through combined convolutional neural network-gated recurrent unit approach for distributed denial of service attack detection,” in Proceedings of the 2024 1st International Conference on Innovative Engineering Sciences and Technological Research (ICIESTR), pp. 1–6, 2024.
19. S. Rani, D. Ghai, and S. Kumar, “Reconstruction of wire frame model of complex images using syntactic pattern recognition,” in IET Conference Proceedings CP791, vol. 2021, no. 11, pp. 8–13, 2021.
20. Swathi, S. Kumar, S. Rani, A. Jain, and R. K. M. V. N. M., “Emotion classification using feature extraction of facial expression,” in Proceedings of the 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), pp. 283–288, 2022.
21. S. Choudhary, S. Kumar, S. Gowroju, M. Gulhane, and R. Sri Lakshmi, Eds., Genomics at the Nexus of AI, Computer Vision, and Machine Learning. Hoboken, NJ, USA: John Wiley & Sons, 2024.
22. S. Kumar, S. Choudhary, S. Gowroju, and A. Bhola, “Convolutional neural network approach for multimodal biometric recognition system for banking sector on fusion of face and finger,” in Multimodal Biometric and Machine Learning Technologies: Applications for Computer Vision, pp. 251–267, 2023.
23. S. Choudhary, S. Kumar, M. Gulhane, and M. Kumar, “Secured automated certificate creation based on multimodal biometric verification,” in Multimodal Biometric and Machine Learning Technologies: Applications for Computer Vision, pp. 269–281, 2023.
24. Jaiswal, I. A. (2024). AI-powered observability and incident prediction in distributed enterprise platforms. Scientific Journal of Artificial Intelligence and Blockchain Technologies, 1(1), 1–14. https://doi.org/10.63345/sjaibt.v1.i1.201
25. S. Choudhary, C. H. Kandikattu, S. Kumar, M. V. V. P. Kantipudi, and M. Kumar, “Enhancing cybersecurity through combined convolutional neural network-gated recurrent unit approach for distributed denial of service attack detection,” in Proceedings of the 2024 1st International Conference on Innovative Engineering Sciences and Technological Research (ICIESTR), pp. 1–6, 2024.
26. Jaiswal, I. A. (2023). High-Performance AI-Augmented Content Management Systems for Distributed Clouds. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 2 (2), 90–97. Retrieved from https://ijmirm. com/index. php/ijmirm/article/view, 243.
27. Khan, S. (2018). The role of zero-trust models in database security: Eliminating implicit trust and enforcing continuous verification in enterprise data access systems. International Journal of Research in Electronics and Computer Engineering, 6(1), 1622–1628.
28. Jaiswal, I. A. (2024). Self-healing REST services using artificial intelligence in multi-cloud environments. Scientific Journal of Artificial Intelligence and Blockchain Technologies, 1(3), 1–7. https://doi.org/10.63345/sjaibt.v1.i3.201
29. V. Saini, A. Jain, Anurag, and M. V. V. Prasad Kantipudi, “An Efficient Approach for Improving the Performance of Autonomous Vehicle Using Advanced Computer Vision,” in International Conference on Soft Computing and Pattern Recognition, Cham, Switzerland: Springer Nature Switzerland, 2023, pp. 164–174.
30. Khan, S. (2017). The role of privacy-preserving techniques in database security: Secure multi-party computation, differential privacy, and homomorphic encryption. The Research Journal, 3(4), 29–35.
31. Khan, S. (2016). A study of data provenance and integrity in database security: Ensuring authenticity, non-repudiation, and accountability in data lifecycle management. International Journal of Research in Electronics and Computer Engineering, 4(3), 180–186.
32. Rallabandi, B. R. (2020). MEC-native 5G systems: Orchestration algorithms for ultra-low latency cloud-edge integration. International Journal of Intelligent Systems and Applications in Engineering, 8(4), 398–408. https://ijisae.org/index.php/IJISAE/article/view/7889
33. Rallabandi, B. R. (2018). Joint deployment and operational energy optimization in heterogeneous cellular networks under traffic variability. International Journal of Communication Networks and Information Security, 10(3), 638–647. https://ijcnis.org/index.php/ijcnis/article/view/8604
34. Cherladine, K., Rallabandi, B. R., Goel, A., Kaushik, K., Dhillon, A., & Soni, M. (2025). Generative adversarial defense models for simulated cyberattack scenarios in virtual networks. In 2025 International Conference on Digital Innovations for Sustainable Solutions (ICDISS) (pp. 1–6). IEEE. https://doi.org/10.1109/ICDISS68238.2025.11320686
