Reshaping Language and Cognition in Education through AI

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Bibliographic Details
Title: Reshaping Language and Cognition in Education through AI
Language: English
Authors: Lalu Nurul Yaqin, Yabit bin Alas, Akhmad Habibi
Source: IGI Global. 2026.
Availability: IGI Global. 701 East Chocolate Avenue Suite 200, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; e-mail: cust@igi-global.com; Web site: http://www.igi-global.com/
Peer Reviewed: Y
Page Count: 406
Publication Date: 2026
Intended Audience: Policymakers; Researchers; Practitioners; Students
Document Type: Book
Collected Works - General
Descriptors: Artificial Intelligence, Technology Uses in Education, Language Acquisition, Cognitive Processes, Cognitive Development, Critical Thinking, Technology Integration
DOI: 10.4018/979-8-3373-4397-6
ISBN: 979-83-373-4397-6
Abstract: Artificial intelligence (AI) is rapidly transforming education by reshaping how language is taught and understood, while also influencing the development of human cognition. AI-powered tools offer personalized and responsive approaches that can enhance critical thinking and communication skills. As these technologies become more integrated into classrooms and learning environments, they are redefining traditional educational practices and cognitive processes, challenging educators to reconsider how knowledge is constructed and assessed. Exploring the role of AI in reshaping language and cognition is essential for leveraging its benefits responsibly while preserving the human-centered goals of education. "Reshaping Language and Cognition in Education Through AI" explores how AI fundamentally transforms how educators teach and engage with language, cognition, and education. It examines AI's role as a transformative force in linguistic and educational domains. Covering topics such as AI, language education, and cognitive education, this book is an excellent resource for educators, curriculum developers, policy makers, education developers, researchers, graduate students, and more.
Abstractor: As Provided
Entry Date: 2026
Accession Number: ED680304
Database: ERIC
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