ISBN: 9786206735151 - autonomy versus algorithm: a replication study of student perspectives: the hidden moral tradeoffs behind everyday ai use (4 Ergebnisse)

Taschenbuch. Zustand: Neu. Autonomy Versus Algorithm: A Replication Study of Student Perspectives | The Hidden Moral Tradeoffs Behind Everyday AI Use | Aminu Muhammad Auwal | Taschenbuch | Englisch | 2026 | GlobeEdit | EAN 9786206735151 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 52 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book examines how undergraduate students interpret ethical boundaries around generative AI use in higher education. Using a mixed methods replication design, the study surveys 200 undergraduates across multiple disciplines in three Nigerian universities to measure agreement with five AI ethics dimensions: beneficence, non maleficence, justice, autonomy, and explicability. Results show autonomy as the strongest priority, while explicability ranks lowest, suggesting students care more about preserving independent decision making than understanding how AI systems produce outputs. Regression analyses indicate technology proficiency predicts stronger endorsement of beneficence and autonomy, while gender predicts non maleficence and justice. Qualitative findings highlight practical concerns about misinformation, erosion of creativity and skill, privacy, bias, job displacement, and unequal access shaped by infrastructure and data costs, alongside views that responsibility lies primarily with users. The book concludes with implications for AI ethics guidance, awareness programs, and curriculum integration tailored to the Nigerian higher education context.…

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book examines how undergraduate students interpret ethical boundaries around generative AI use in higher education. Using a mixed methods replication design, the study surveys 200 undergraduates across multiple disciplines in three Nigerian universities to measure agreement with five AI ethics dimensions: beneficence, non maleficence, justice, autonomy, and explicability. Results show autonomy as the strongest priority, while explicability ranks lowest, suggesting students care more about preserving independent decision making than understanding how AI systems produce outputs. Regression analyses indicate technology proficiency predicts stronger endorsement of beneficence and autonomy, while gender predicts non maleficence and justice. Qualitative findings highlight practical concerns about misinformation, erosion of creativity and skill, privacy, bias, job displacement, and unequal access shaped by infrastructure and data costs, alongside views that responsibility lies primarily with users. The book concludes with implications for AI ethics guidance, awareness programs, and curriculum integration tailored to the Nigerian higher education context.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.…