Artificial Intelligence Education in the Context of Work [electronic resource] / edited by Dirk Ifenthaler, Sabine Seufert.

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). .

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.