Tag: ai
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New open access chapter: Corruption in the post-plagiarism era: weaponizing reputation and morality in the name of integrity in higher education
Sarah Elaine Eaton reflects on her admiration for Philip Altbach, Hans de Wit, and Elena Denisova-Schmidt, culminating in her contribution to the newly published “Handbook on Corruption in Higher Education.” Eaton’s chapter discusses corruption in the post-plagiarism era, exploring the manipulation of reputation and morality in higher education, emphasizing integrity.
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New Open Access Chapter: “Pedagogical Ethics: Navigating Learning in a Generative AI-Augmented Environment in a Post-Plagiarism Era”
The chapter “Pedagogical Ethics: Navigating Learning in a Generative AI-Augmented Environment in a Post-Plagiarism Era,” co-authored by Sarah Elaine Eaton and Mohammad Keyhani, discusses the implications of generative AI in education, focusing on academic integrity and pedagogical ethics. It emphasizes learner agency and offers guidance for educators, available as open access.
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Postplagiarism: Understanding the Difference Between Referencing and Giving Attribution
In the talks I give on postplagiarism, I distinguish between attribution and referencing amid evolving academic practices influenced by artificial intelligence. Attribution transcends mere technical referencing. The discourse urges an exploration of attribution as an ethical commitment in the postplagiarism era.
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Postplagiarism Reflection: On Control & Responsibility
In our digital age of remixing, re-using, sharing, and collaborative creation, we’re challenged to rethink ownership. Postplagiarism invites us to embrace a profound paradox: We can relinquish control (in part or in whole) to an AI app to either generate work on our behalf or provide a starting point that we then build upon. But,…
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Teaching Fact-Checking Through Deliberate Errors: An Essential AI Literacy Skill
This teaching resource presents a method for enhancing AI literacy by engaging students in fact-checking AI-generated content with intentional inaccuracies. It emphasizes systematic verification processes, critical evaluation of sources, and understanding AI error patterns, equipping students with essential skills to discern accurate information in a postplagiarism landscape.
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Upcoming Talk: From Plagiarism to Postplagiarism: Navigating the GenAI Revolution in Higher Education
Join us on January 29, 2025, for the inaugural postplagiarism talk titled “From Plagiarism to Postplagiarism: Navigating the GenAI Revolution in Higher Education,” led by Dr. Sarah Elaine Eaton. This hybrid event will address integrating Generative AI in academia while maintaining integrity and fostering original scholarship. Register to participate!
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Understanding Postplagiarism: Ethics in the Digital Age
Postplagiarism is defined as a new era where advanced technologies, such as AI and brain-computer interfaces, change intellectual engagement. It emphasizes the importance of attribution and accountability, contrary to absolute relativism or merely relying on technology. Critical thinking and digital literacy are crucial in teaching ethical interactions with these tools.
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University Rankings Overlook Academic Retractions: A Postplagiarism Perspective
University rankings often emphasize metrics like publication counts but fail to consider critical issues like academic retractions due to misconduct. Recent studies highlight the impact of retractions on research quality and integrity, suggesting that ranking systems need to incorporate these factors to reflect authentic academic reputation accurately and ensure fairness among institutions.
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Redefining Plagiarism in the Age of AI
The online presentation “Redefining Plagiarism” discussed the evolving concept of plagiarism in light of technological advancements, particularly Generative AI. As AI blurs the lines of originality and intellectual ownership, definitions of plagiarism must adapt. It emphasizes the need for quality-focused evaluation and maintains the importance of human accountability in creative work.
