Generative AI detection in higher education assessments

Author:

Ardito Cesare Giulio1

Affiliation:

1. Department of Mathematics School of Natural Sciences Faculty of Science and Engineering University of Manchester Manchester UK

Abstract

AbstractThis 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.

Publisher

Wiley

Reference66 articles.

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2. Ardito C. G.(2023 May 1).Against AI detection: Detection does not work.Thoughts.https://cesaregardito.substack.com/p/against‐ai‐detection‐1‐detection

3. Ardito C. G. &ChatGPT. (2023 November 19).Prove output by language model.https://chat.openai.com/share/666370cd‐4333‐4b42‐88a1‐1760e7513c4a

4. Examining students’ perceptions of two graphing technologies and their impact on problem solving;Bostic J.;Journal of Computers in Mathematics and Science Teaching,2010

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