A practical guide for teachers and students navigating the complicated intersection of artificial intelligence, education, and justice
Artificial intelligence is rapidly integrating into today’s classrooms, but unlike other new technologies, AI has the potential to harm, making it difficult to take advantage of its benefits. In Critical AI in K–12 Classrooms, Stephanie Smith Budhai and Marie K. Heath draw attention to the biases embedded within AI algorithms, such as those powering OpenAI’s ChatGPT and DALL-E, to guide students and teachers in developing strategies to best incorporate AI—or not—into equitable learning.
AI’s reliance on existing data and knowledge systems means Black, queer, those with disabilities, and other marginalized students are at greater risk of being harmed by built-in limitations and bias. Budhai and Heath show how to circumvent if not actively resist such harms as machine learning, NLPs, LLMS, and GenAI enter the classroom, with practical examples rooted in culturally sustaining, abolitionist, and fugitive pedagogies across disciplines. Their practical guide creatively answers the concerns of educators committed to forward-thinking yet fair instruction and the needs of students eager to use AI for just ends.
Critical AI in K–12 Classrooms meets the challenges of a key STEM technology with an eye toward cultivating a more just world. Balancing responsible learning with the joy of discovery, Budhai and Heath build a framework for AI instruction that all educators can confidently use.
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Stephanie Smith Budhai is an associate professor in the Educational Technology program at the University of Delaware and is the recipient of an Excellence in Teacher Education Award from the International Society for Technology in Education (ISTE). She is a council chair for the Society for Information Technology and Teacher Education (SITE) and has published over eighty practitioner articles for Tech & Learning and eight books to support teaching, learning, and technology in education. She holds K–12 teaching certifications in technology education, instructional technology, elementary education, and special education. Marie K. Heath is an associate professor of Learning Design and Technology and a faculty fellow at the Center for Leadership and Social Justice Education at Loyola University Maryland. She is coeditor of the social studies education section of Contemporary Issues in Technology and Teacher Education (CITE), and cofounder of the Civics of Technology project. She is a former high school social studies teacher in Baltimore County Public Schools.
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Paperback. Condizione: new. Paperback. A practical guide for teachers and students navigating the complicated intersection of artificial intelligence, education, and justice Artificial intelligence is rapidly integrating into today s classrooms, but unlike other new technologies, AI has the potential to harm, making it difficult to take advantage of its benefits. In Critical AI in K-2 Classrooms, Stephanie Smith Budhai and Marie K. Heath draw attention to the biases embedded within AI algorithms, such as those powering OpenAI's ChatGPT and DALL-E, to guide students and teachers in developing strategies to best incorporate AI-or not-into equitable learning. AI's reliance on existing data and knowledge systems means Black, queer, those with disabilities, and other marginalized students are at greater risk of being harmed by built-in limitations and bias. Smith Budhai and Heath show how to circumvent if not actively resist such harms as machine learning, NLPs, LLMS, and GenAI enter the classroom, with practical examples rooted in culturally sustaining, abolitionist, and fugitive pedagogies across disciplines. Their practical guide creatively answers the concerns of educators committed to forward-thinking yet fair instruction and the needs of students eager to use AI for just ends. Critical AI in K 2 Classrooms meets the challenges of a key STEM technology with an eye toward cultivating a more just world. Balancing responsible learning with the joy of discovery, Smith Budhai and Heath build a framework for AI instruction that all educators can confidently use. A roadmap for classroom AI that confronts hidden biases inherent in systems including ChatGPT and DALL-E. It equips educators and students with practical strategies to counter harm and uplift marginalized voices, drawing on critical, culturally informed, abolitionist, and fugitive pedagogies for equitable instruction. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9798895570180
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Paperback. Condizione: New. A practical guide for teachers and students navigating the complicated intersection of artificial intelligence, education, and justice Artificial intelligence is rapidly integrating into today' s classrooms, but unlike other new technologies, AI has the potential to harm, making it difficult to take advantage of its benefits. In Critical AI in K-2 Classrooms, Stephanie Smith Budhai and Marie K. Heath draw attention to the biases embedded within AI algorithms, such as those powering OpenAI's ChatGPT and DALL-E, to guide students and teachers in developing strategies to best incorporate AI-or not-into equitable learning. AI's reliance on existing data and knowledge systems means Black, queer, those with disabilities, and other marginalized students are at greater risk of being harmed by built-in limitations and bias. Smith Budhai and Heath show how to circumvent if not actively resist such harms as machine learning, NLPs, LLMS, and GenAI enter the classroom, with practical examples rooted in culturally sustaining, abolitionist, and fugitive pedagogies across disciplines. Their practical guide creatively answers the concerns of educators committed to forward-thinking yet fair instruction and the needs of students eager to use AI for just ends. Critical AI in K- 2 Classrooms meets the challenges of a key STEM technology with an eye toward cultivating a more just world. Balancing responsible learning with the joy of discovery, Smith Budhai and Heath build a framework for AI instruction that all educators can confidently use. Codice articolo LU-9798895570180
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Paperback. Condizione: New. A practical guide for teachers and students navigating the complicated intersection of artificial intelligence, education, and justice Artificial intelligence is rapidly integrating into today' s classrooms, but unlike other new technologies, AI has the potential to harm, making it difficult to take advantage of its benefits. In Critical AI in K-2 Classrooms, Stephanie Smith Budhai and Marie K. Heath draw attention to the biases embedded within AI algorithms, such as those powering OpenAI's ChatGPT and DALL-E, to guide students and teachers in developing strategies to best incorporate AI-or not-into equitable learning. AI's reliance on existing data and knowledge systems means Black, queer, those with disabilities, and other marginalized students are at greater risk of being harmed by built-in limitations and bias. Smith Budhai and Heath show how to circumvent if not actively resist such harms as machine learning, NLPs, LLMS, and GenAI enter the classroom, with practical examples rooted in culturally sustaining, abolitionist, and fugitive pedagogies across disciplines. Their practical guide creatively answers the concerns of educators committed to forward-thinking yet fair instruction and the needs of students eager to use AI for just ends. Critical AI in K- 2 Classrooms meets the challenges of a key STEM technology with an eye toward cultivating a more just world. Balancing responsible learning with the joy of discovery, Smith Budhai and Heath build a framework for AI instruction that all educators can confidently use. Codice articolo LU-9798895570180
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