Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Rethinking Pedagogy in the Age of AI: A Hegelian Exploration of Generative AI Tools and Student Learning
0
Zitationen
1
Autoren
2025
Jahr
Abstract
The integration of generative AI into education marks a significant shift in traditional pedagogy, raising fundamental questions about knowledge construction, critical thinking, and the evolving role of educators. While AI tools like ChatGPT and Gemini offer unprecedented access to information and personalized learning opportunities, they also introduce concerns regarding intellectual dependency, the erosion of critical reasoning, and ethical considerations. This research employs a Hegelian dialectical framework to analyze the tension between established pedagogical methods (thesis) and the rise of AI-generated knowledge (antithesis), ultimately leading to a reimagined synthesis of AI-augmented critical learning. Through this lens, the study examines how students interact with AI-generated content, emphasizing the necessity of human skepticism as a filter for refining and contextualizing information. Rather than replacing traditional learning, AI serves as a catalyst for deeper inquiry, challenging students to engage in comparative analysis, critical reflection, and independent meaning-making. The resulting pedagogical synthesis fosters an educational paradigm where AI and human judgment coexist, enhancing both accessibility and intellectual rigor. This approach ensures that education in the AI era prioritizes not only the acquisition of knowledge but also the cultivation of wisdom, ethical discernment, and creative problem-solving, equipping learners to navigate the complexities of the 21st century.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.707 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.613 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 8.159 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.875 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.