The AI Assist : Strategies for Integrating AI Into the Very Human Act of Teaching

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Title: The AI Assist : Strategies for Integrating AI Into the Very Human Act of Teaching
Description: In The AI Assist, Nathan Lang-Raad presents a groundbreaking guide for teachers who are navigating the frontier of artificial intelligence in education.“We must recognize the value of human connection in teaching, ensuring that AI tools serve as supplements to—not replacements for—human teachers. This approach will help maintain a balance where AI enriches human interaction, creativity, and empathy in the classroom.'Teachers need to not only keep up with technology but also harness its potential to create more engaging, personalized, and effective learning experiences for their students.Inside, you'll discover• How to use the innovative HAIL model (Humanize, Augment, Integrate, Leverage) as a guide to seamlessly incorporate AI into your teaching practice.• More than 40 practical AI tools and templates, ready for classroom implementation.• Strategies for maintaining the irreplaceable human touch in an AI-enhanced environment.• Real-world examples of AI integration across various subjects and grade levels.• Essential processes to evaluate the effectiveness of your AI integration and assess student progress.Whether you're already using AI tools or are just starting to explore their potential benefits, Lang-Raad provides the insights and practical knowledge you need to confidently integrate this technology into your teaching practice.Embrace the future of education. Let The AI Assist be your guide in creating a classroom where technology and a very human connection work in harmony to unlock every student's potential.This book is a copublication of ASCD and ISTE.
Authors: Nathan Lang-Raad
Resource Type: eBook.
Subjects: Educational planning, Artificial intelligence--Educational applications
Categories: EDUCATION / Teaching / Methods & Strategies, EDUCATION / Computers & Technology
Database: eBook Collection (EBSCOhost)
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  – Type: ebook-epub
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  Availability: 0
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PubType: eBook
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  Data: In The AI Assist, Nathan Lang-Raad presents a groundbreaking guide for teachers who are navigating the frontier of artificial intelligence in education.“We must recognize the value of human connection in teaching, ensuring that AI tools serve as supplements to—not replacements for—human teachers. This approach will help maintain a balance where AI enriches human interaction, creativity, and empathy in the classroom.'Teachers need to not only keep up with technology but also harness its potential to create more engaging, personalized, and effective learning experiences for their students.Inside, you'll discover• How to use the innovative HAIL model (Humanize, Augment, Integrate, Leverage) as a guide to seamlessly incorporate AI into your teaching practice.• More than 40 practical AI tools and templates, ready for classroom implementation.• Strategies for maintaining the irreplaceable human touch in an AI-enhanced environment.• Real-world examples of AI integration across various subjects and grade levels.• Essential processes to evaluate the effectiveness of your AI integration and assess student progress.Whether you're already using AI tools or are just starting to explore their potential benefits, Lang-Raad provides the insights and practical knowledge you need to confidently integrate this technology into your teaching practice.Embrace the future of education. Let The AI Assist be your guide in creating a classroom where technology and a very human connection work in harmony to unlock every student's potential.This book is a copublication of ASCD and ISTE.
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      – Code: 371.33463
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
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      – SubjectFull: Educational planning
        Type: general
      – SubjectFull: Artificial intelligence--Educational applications
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      – TitleFull: The AI Assist : Strategies for Integrating AI Into the Very Human Act of Teaching
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2025
            – D: 25
              M: 11
              Type: profile
              Y: 2024
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