Trickle or Torrent? A Novel Algorithmic Approach to Reclaim Successful Academic Writing in the Face of Artificial Intelligence
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| Title: | Trickle or Torrent? A Novel Algorithmic Approach to Reclaim Successful Academic Writing in the Face of Artificial Intelligence |
|---|---|
| Language: | English |
| Authors: | Donna Poade, Russell M. Crawford (ORCID |
| Source: | Brock Education: A Journal of Educational Research and Practice. 2024 33(1). |
| Availability: | Brock University Faculty of Education. 500 Glenridge Avenue, Saint Catharines, ON, L2S 3A1 Canada. Tel: 905-688-5550 ext. 3733; e-mail: brocked@brocku.ca; Web site: http://brocked.ed.brocku.ca |
| Peer Reviewed: | Y |
| Page Count: | 14 |
| Publication Date: | 2024 |
| Document Type: | Journal Articles Reports - Descriptive |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Academic Language, Artificial Intelligence, Algorithms, Personal Autonomy, Writing Attitudes, Well Being, Writing Strategies, Higher Education |
| ISSN: | 1183-1189 |
| Abstract: | 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. |
| Abstractor: | As Provided |
| Entry Date: | 2024 |
| Accession Number: | EJ1417078 |
| Database: | ERIC |
| Abstract: | 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. |
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| ISSN: | 1183-1189 |
