Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Generative AI detection in higher education assessments
35
Zitationen
1
Autoren
2024
Jahr
Abstract
Abstract This chapter presents a critical analysis of generative AI (GenAI) detection tools in higher education assessments. The rapid advancement and widespread adoption of GenAI, particularly in education, necessitates a reevaluation of traditional academic integrity mechanisms. I explore the effectiveness, vulnerabilities, and ethical implications of AI detection tools in the context of preserving academic integrity. My analysis synthesizes insights from various case studies, newspaper articles, and student testimonies to scrutinize the practical and philosophical challenges associated with AI detection. I argue that reliance on detection mechanisms is misaligned with the educational landscape, where AI plays an increasing role. I advocate for a strategic shift toward robust assessment methods and educational policies that embrace GenAI usage while ensuring academic integrity and authenticity in assessments.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.513 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.407 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.882 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.571 Zit.