This edited volume remedies existing deficiencies in the literature on artificial intelligence and education in the context of work. The topics addressed by this book are:
• Supporting formal and informal learning through AI
• Human-machine collaboration for learning at the workplace, including the potential of human-AI interaction in professional and vocational education contexts, design, use, and evaluation of human-AI hybrid systems for learning
• Intelligent and Interactive Technologies for Learning, including natural language processing and speech technologies; data mining and machine learning; knowledge representation and reasoning; semantic web technologies, chat bot-mediated learning, and conversational learning,
• AI-enabled applications for skills management and personalized learning, such as AI-enabled coaching, personalized skill management, and intelligent tutoring systems.
• Case studies for the implementation and use of AI-enabled learning and performance solutions, such as personal learning experience platforms, and automated performance feedback.
Tabla de materias
Part I – Conceptual and Empirical Perspectives.- Chapter 1 – AI-supported systems for integrated skills-management and skills-development (Christoph Meier, Sabine Seufert).- Chapter 2 – Four perspectives on personalized and adaptive learning environments for workplace learning (Yvonne M. Hemmler, Dirk Ifenthaler).- Chapter 3 – Shaping AI Transformation: digital competencies and augmentation strategies of HRD professionals (Judith Spirgi, Josef Guggenmos, Sabine Seufert).- Chapter 4 – Leveraging artificial intelligence techniques for effective scaffolding of personalized learning in workplaces (Duygu Umutlu, M. Emre Gursoy).- Chapter 5 – Supporting stress detection via AI and non-invasive wearables in the context of work (Mariano Albaladejo-González, José A. Ruipérez-Valiente).- Chapter 6 – Knowledge state networks for skill assessment in atomic learning (Julian Rasch, David Middelbeck).- Chapter 7 – The engine design of electronic performance support system for employees’ training based on training need analysis (Salim Atay, Muhittin Sahin, Aysu Cetinbinici, Deniz Subası, Furkan Aydın, Savas Ceylan).- Chapter 10 – AI-enhanced interfaces as informal guides (Melissa Peterson).- Part II – Practices and Case Studies.- Chapter 11 – Workplace learning in and with intelligent systems (Felix Miesen, Susanne Narciss).- Chapter 12 – Case Volkswagen Passenger Cars – Upskilling strategy for employees (Judith Spirgi, Andreas Meier).- Chapter 13 – Not plug-and-play: successful adoption of an ai-based learning experience platform (Nadia Eggmann).- Chapter 14 – Using AI-based Linkedin video platform for personalised learning: the case at Infineon Technologies (Judith Spirgi, Julia Tronsberg).
Sobre el autor
Dirk Ifenthaler is Professor and Chair of Learning, Design and Technology at University of Mannheim, Germany and UNESCO Deputy Chair of Data Science in Higher Education Learning and Teaching at Curtin University, Australia. Dirk’s research focuses on the intersection of cognitive psychology, educational technology, data analytics, and organisational learning.
Sabine Seufert is Professor for Business Education and Director of the Institute for Educational Management and Educational Technologies at the University of St.Gallen. Sabine’s research focuses on digital competences and digital transformation in education, Artificial Intelligence in professional and vocational education.
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