Trickle or torrent? A novel algorithmic approach to reclaim successful academic writing in the face of artificial intelligence.

Poade, Donna ORCID: https://orcid.org/0009-0001-7405-6790 and Crawford, Russell ORCID: https://orcid.org/0000-0002-4657-1576 (2024) Trickle or torrent? A novel algorithmic approach to reclaim successful academic writing in the face of artificial intelligence. Brock Education Journal, 33 (1). pp. 166-179. ISSN 2371-7750

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Abstract / Summary

The emergence of artificial intelligence (AI) in academia has prompted various debates on the uses, threats, and limitations of tools that can create text for numerous academic purposes. Critics argue that these advancements may provide opportunities for cheating and plagiarism and even replace the art of writing entirely. To reclaim the creativity and depth that academic writing holds, we propose both an innovative approach to safeguard the creativity and depth of academic writing and a scaffolded way to enhance success in terms of authenticity for the author and, by extension, meaning for the reader. This novel conceptual algorithmic trickle filter model aims to inform successful academic writing and embody the writer’s agency—a task too sophisticated for current AI tools. Our model provides a scaffolded decision-making process in a highly personal, flexible, and iterative individual writing development tool applied in a health-conscious way. We position this model as a step towards a pedagogic paradigm shift in reclaiming academic writing that, rather than competing with AI, doubles down on the personal self-evaluative aspects that academic writing offers both author and reader.

Item Type:	Article
Identification Number:	10.26522/brocked.v33i1.1127
ISSN:	2371-7750
Subjects:	Computing & Data Science Education
Department:	Cornwall Business School
Depositing User:	Donna Poade
Date Deposited:	26 Oct 2026 11:21
Last Modified:	26 Oct 2026 11:21
URI:	https://repository.falmouth.ac.uk/id/eprint/6612

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