AI-Enabled Learning Engagement Analysis
Revolutionizing Education with AI
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Beschreibung
Artificial Intelligence (AI) is revolutionizing the education industry, particularly in understanding and enhancing student learning engagement in online learning. The book aims to get an in-depth exploration into a three-stage framework of AI-enabled learning engagement analysis, which provides effective tools and methodologies for education researchers and practitioners, facilitating intelligent transformation and optimization. It delves into intelligent recognition, including emotional and cognitive engagement, supported by detailed algorithmic introductions and case studies. The book further examines the relationship between engagement and outcomes, covering cognition, emotion, self-regulation, and social network characteristics. Furthermore, it presents adaptive interventions, offering a comprehensive guide to leveraging AI for personalized learning experiences and improved learning outcomes.
The book provides valuable insights and practical tools for enhancing teaching and learning outcomes. Whether you are an educator seeking to integrate AI into your teaching strategies or a researcher exploring the frontiers of educational technology, this book equips you with the knowledge and resources to navigate the evolving landscape of AI-enabled education.
This publication underscores the significance of practical applications, presenting a compendium of pioneering research methodologies and case studies that elucidate the integration of AI and data analytics within pedagogical contexts. Whether the objective is to refine comprehension of online learning engagement dynamics or to deploy AI-infused strategies in educational settings, this text serves as an invaluable resource for revolutionizing education with AI.
Chapter 2 is available for open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Artificial Intelligence (AI) is revolutionizing the education industry, particularly in understanding and enhancing student learning engagement in online learning. The book aims to get an in-depth exploration into a three-stage framework of AI-enabled learning engagement analysis, which provides effective tools and methodologies for education researchers and practitioners, facilitating intelligent transformation and optimization. It delves into intelligent recognition, including emotional and cognitive engagement, supported by detailed algorithmic introductions and case studies. The book further examines the relationship between engagement and outcomes, covering cognition, emotion, self-regulation, and social network characteristics. Furthermore, it presents adaptive interventions, offering a comprehensive guide to leveraging AI for personalized learning experiences and improved learning outcomes.
The book provides valuable insights and practical tools for enhancing teaching and learning outcomes. Whether you are an educator seeking to integrate AI into your teaching strategies or a researcher exploring the frontiers of educational technology, this book equips you with the knowledge and resources to navigate the evolving landscape of AI-enabled education.
This publication underscores the significance of practical applications, presenting a compendium of pioneering research methodologies and case studies that elucidate the integration of AI and data analytics within pedagogical contexts. Whether the objective is to refine comprehension of online learning engagement dynamics or to deploy AI-infused strategies in educational settings, this text serves as an invaluable resource for revolutionizing education with AI.
Chapter 2 is available for open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Provides a data-driven analysis approach for learning engagement that combines AI and empirical methods Offers a novel perspective to the research of learning engagement from computer science and educational psychology Presents an in-depth exploration of a three-stage framework of AI-enabled learning engagement analysis
Autor*in
Zhi Liu
Themen in »AI-Enabled Learning Engagement Analysis«
Online learning MOOC Asynchronous online discussion Learning engagement Bidirectional Encoder Representations Cognitive engagement Learning outcome Mechanisms of association Adaptive intervention