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Demystifying Artificial Intelligence Biases through the Design of Effective Prompts in Teacher Education
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| dc.contributor.author | Arrar, Salah | |
| dc.contributor.author | Seghiour, Abdellatif | |
| dc.date.accessioned | 2025-05-20T10:12:30Z | |
| dc.date.available | 2025-05-20T10:12:30Z | |
| dc.date.issued | 2024-10-25 | |
| dc.identifier.issn | issn | |
| dc.identifier.uri | http://depot.umc.edu.dz/handle/123456789/14638 | |
| dc.description.abstract | This contribution takes a pragmatic approach to highlight a range of techniques and strategies aimed at developing critical skills among French language teachers, enabling them to analyze AI-generated results with an awareness of inherent biases and potential pitfalls. We emphasize educational and pedagogical approaches grounded in the art of prompt engineering, viewed as a powerful tool to mitigate the impact of bias on research outcomes. | fr_FR |
| dc.language.iso | en | fr_FR |
| dc.publisher | Université Frères Mentouri - Constantine 1 | fr_FR |
| dc.title | Demystifying Artificial Intelligence Biases through the Design of Effective Prompts in Teacher Education | fr_FR |
| dc.type | Presentation | fr_FR |
