AI for Education (Intermediate)
Master advanced AI integration in education with practical prompt engineering methods for course design and assignments.
Master advanced AI integration in education with practical prompt engineering methods for course design and assignments.
This intermediate-level course builds on basic AI education concepts, focusing on refined prompt engineering methods for educational contexts. Students learn practical techniques for collaborating with AI assistants like GPT in various educational settings. The course provides tested methods for generating useful, relevant, and ethical AI outputs, with real-time demonstrations across different learning environments from secondary to college levels.
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What you'll learn
Master advanced prompt engineering techniques for educational contexts
Develop scalable AI-enhanced assignments for multiple education levels
Learn ethical implementation of AI in educational settings
Create effective course designs using AI assistance
Understand how to guide students in ethical AI usage
Implement AI-assisted peer review and editing processes
Skills you'll gain
This course includes:
60 Minutes PreRecorded video
Access on Mobile, Tablet, Desktop
FullTime access
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There are 2 modules in this course
This course provides educators with advanced techniques for integrating AI in educational settings. The curriculum focuses on practical applications of prompt engineering for course design and assessment. Students learn to create scalable assignments across different educational levels, from middle school to college. The course emphasizes ethical AI implementation and effective collaboration strategies with AI assistants for both teachers and students.
Course Introduction
Module 1 · 58 Minutes to complete
AI for Education - Intermediate
Module 2 · 4 Hours to complete
Fee Structure
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Instructor
Innovator in English and Generative AI at Kennesaw State University
Dr. Jeanne Beatrix Law is a Professor of English at Kennesaw State University, specializing in multimodal languaging, digital historiography, and the integration of generative AI technologies for writers. She is a co-author of The Writer’s Loop: A Guide to College Writing and has contributed to various academic publications on information literacy and AI applications in education. As the lead researcher for the nationally recognized #ATLStudentMovement oral history project, she has developed multiple Coursera courses focused on ethical generative AI use. Dr. Law serves as a faculty mentor for the AAC&U’s AI Pedagogy Institute and has presented extensively on the ethical implications of generative AI in educational settings. Her commitment to fostering digital literacy among students is evident in her innovative teaching methods and collaborative projects that emphasize the importance of compassionate pedagogy in today’s AI-driven landscape.
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