AI for Educators in Practice: Applying Intelligent Tools and Adaptive Platforms Across K–12 and Higher Education Classrooms
Language: English
Published by Independently published, 2026
- Softcover
- New

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- Title
- AI for Educators in Practice: Applying Intelligent Tools and Adaptive Platforms Across K–12 and Higher Education Classrooms
- Author
- Monroe, Keiko
- Publisher
- Independently published
- Publication year
- 2026
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798196607615
Artificial intelligence is no longer peripheral to education it is increasingly embedded in how institutions plan instruction, assess learners, and personalize academic pathways. Yet most available literature either oversimplifies the technology or targets developers rather than the professionals who deploy it daily. AI for Educators in Practice addresses that gap directly.
Written for experienced classroom practitioners, curriculum coordinators, instructional designers, and institutional decision-makers, this book provides a rigorous, field-grounded examination of how intelligent systems function within real educational environments. It does not assume a technical background in computer science, but it does assume professional familiarity with pedagogical frameworks, institutional structures, and the complex realities of modern teaching.
Across ten structured chapters, readers will examine the foundational architecture of AI systems relevant to education, explore how adaptive learning platforms personalize content delivery at scale, and evaluate the practical and ethical dimensions of deploying AI teaching assistants in live instructional settings. The book addresses student performance analytics with an emphasis on data interpretation, equity considerations, and institutional accountability. Generative AI applications including AI-powered lesson planning, automated feedback systems, and content generation tools are analyzed with critical depth, not promotional enthusiasm.
Each chapter integrates current research, documented case implementations from K–12 and higher education contexts, and frameworks educators can apply to their own institutional decisions. The book also addresses policy alignment, digital equity, faculty adoption challenges, and the evolving regulatory landscape surrounding educational data.
This is not an introductory survey. It is a practitioner-level reference for professionals who are already navigating EdTech ecosystems and need analytical frameworks, not simplified tutorials.
If you are an educator, administrator, or instructional strategist ready to engage with AI not as a novelty but as a professional instrument this book belongs in your institutional library. Secure your copy today and equip your practice with the depth this technological shift demands.
Written for experienced classroom practitioners, curriculum coordinators, instructional designers, and institutional decision-makers, this book provides a rigorous, field-grounded examination of how intelligent systems function within real educational environments. It does not assume a technical background in computer science, but it does assume professional familiarity with pedagogical frameworks, institutional structures, and the complex realities of modern teaching.
Across ten structured chapters, readers will examine the foundational architecture of AI systems relevant to education, explore how adaptive learning platforms personalize content delivery at scale, and evaluate the practical and ethical dimensions of deploying AI teaching assistants in live instructional settings. The book addresses student performance analytics with an emphasis on data interpretation, equity considerations, and institutional accountability. Generative AI applications including AI-powered lesson planning, automated feedback systems, and content generation tools are analyzed with critical depth, not promotional enthusiasm.
Each chapter integrates current research, documented case implementations from K–12 and higher education contexts, and frameworks educators can apply to their own institutional decisions. The book also addresses policy alignment, digital equity, faculty adoption challenges, and the evolving regulatory landscape surrounding educational data.
This is not an introductory survey. It is a practitioner-level reference for professionals who are already navigating EdTech ecosystems and need analytical frameworks, not simplified tutorials.
If you are an educator, administrator, or instructional strategist ready to engage with AI not as a novelty but as a professional instrument this book belongs in your institutional library. Secure your copy today and equip your practice with the depth this technological shift demands.
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California Books
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