Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Current evaluation and recommendations for the use of artificial intelligence tools in education
36
Zitationen
5
Autoren
2023
Jahr
Abstract
Abstract This paper discusses the integration of artificial intelligence (AI) tools in education, delineating their potential to transform pedagogical practices alongside the challenges they present. Generative AI models like ChatGPT, had a disruptive impact on teaching and learning, due to their ability to create text, images, and sound, revolutionizing educational content creation and modification. However, nowadays the educational community is polarized, with some embracing AI for its accessibility and efficiency thus advocating it as an indispensable tool, while others cautioning against risks to academic integrity and intellectual development. This document is designed to raise awareness about AI tools and provide some examples of how they can be used to improve education and learning. From an educator’s perspective, AI is an asset for curriculum development, course material preparation, instructional design and student assessment, while reducing bias and workload. For students, AI tools offer personalized learning experiences, timely feedback, and support in various academic activities. The Turkish Biochemical Society (TBS) Academy recommends educators to embrace and utilize AI tools to enhance educational processes, and engage in peer learning for better adaptation while maintaining a critical perspective on their utility and limitations. The transfer of AI knowledge and methods to the teaching experiences should complement and not replace the educator’s creativity and critical thinking. The paper advocates for an informed embrace of AI, AI fluency among educators and students, ethical application of AI in academic settings, and continuous engagement with the evolving AI technologies, ensuring that AI tools are used to augment critical thinking and contribute positively to education and society.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.312 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.169 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.564 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.466 Zit.