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Uses of Artificial Intelligence in STEM Education
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Uses of Artificial Intelligence in STEM Education

Book Details

Format Hardback or Cased Book
ISBN-10 0198882076
ISBN-13 9780198882077
Publisher Oxford University Press
Imprint Oxford University Press
Country of Manufacture GB
Country of Publication GB
Publication Date Oct 24th, 2024
Print length 624 Pages
Weight 1,166 grams
Dimensions 16.20 x 24.20 x 3.90 cms
Ksh 24,050.00
Werezi Extended Catalogue 0 in stock

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As technology rapidly evolves, AI tools such as automated scoring and intelligent tutors are revolutionizing how we teach STEM subjects. The book discusses the benefits, challenges, and ethical implications. It's a comprehensive guide that showcases the future of education in an AI-driven world.
In the age of rapid technological advancements, the integration of Artificial Intelligence (AI), machine learning (ML), and large language models (LLMs) in Science, Technology, Engineering, and Mathematics (STEM) education has emerged as a transformative force, reshaping pedagogical approaches and assessment methodologies. Uses of AI in STEM Education, comprising 25 chapters, delves deep into the multifaceted realm of AI-driven STEM education. It begins by exploring the challenges and opportunities of AI-based STEM education, emphasizing the intricate balance between human tasks and technological tools. As the chapters unfold, readers learn about innovative AI applications, from automated scoring systems in biology, chemistry, physics, mathematics, and engineering to intelligent tutors and adaptive learning. The book also touches upon the nuances of AI in supporting diverse learners, including students with learning disabilities, and the ethical considerations surrounding AI''s growing influence in educational settings. It showcases the transformative potential of AI in reshaping STEM education, emphasizing the need for adaptive pedagogical strategies that cater to diverse learning needs in an AI-centric world. The chapters further delve into the practical applications of AI, from scoring teacher observations and analyzing classroom videos using neural networks to the broader implications of AI for STEM assessment practices. Concluding with reflections on the new paradigm of AI-based STEM education, this book serves as a comprehensive guide for educators, researchers, and policymakers, offering insights into the future of STEM education in an AI-driven world.

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