C. Mele, Marialuisa Marzullo, Swapnil Morande, T. R. Spena
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引用次数: 8
Abstract
This paper widens the focus on how artificial intelligence (AI) can foster the learning abilities of human actors, adopting a wider view with respect to a strict focus on tasks and activities. The interaction between AI and human learning has not been investigated in service research. Placing its theoretical roots in work by Huang and Rust [Huang MH, Rust RT (2021) Engaged to a robot? The role of AI in service. J. Service Res. 24(1):30–41.] in service research and on Bloom’s revised taxonomy in education studies [Anderson LW, Krathwohl DR, Airasian PW, Cruikshank KA, Mayer RE, Pintrich PR, Raths J, Wittrock MC (2001) A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives (Longman, London).], this study offers an integrative framework for the ways AI enhances human learning abilities. Some cases in the context of COVID-19 offer insightful illustrations of the framework.
期刊介绍：
Service Science publishes innovative and original papers on all topics related to service, including work that crosses traditional disciplinary boundaries. It is the primary forum for presenting new theories and new empirical results in the emerging, interdisciplinary science of service, incorporating research, education, and practice, documenting empirical, modeling, and theoretical studies of service and service systems. Topics covered include but are not limited to the following: Service Management, Operations, Engineering, Economics, Design, and Marketing Service System Analysis and Computational Simulation Service Theories and Research Methods Case Studies and Application Areas, such as healthcare, energy, finance, information technology, logistics, and public services.
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