Teaching and learning of industry 4.0: expectations, drivers, and barriers from a knowledge management perspective

Guilherme Tortorella, Paulo A. Cauchick Miguel, Enzo Frazzon, Alberto Portioli-Staudacher and Maneesh Kumar

Knowledge Management Research & Practice, 2023, vol. 21, issue 4, 876-891

Abstract: This paper aimed at (i) identifying the expectations, drivers, and barriers for the teaching and learning in Industry 4.0 (I4.0), and (ii) verifying how they contribute to the knowledge management (KM) in I4.0. For that, we carried out an exploratory, qualitative study in which we collected data through semi-structured interviews with 21 graduate students who coursed an I4.0 48-hour subject in an Industrial Engineering graduate programme. In the content analysis of these data, we framed the identified commonalities according to the four main KM activities: creation, retrieval, transfer, and application. We identified four main drivers, expectations and barriers for teaching and learning I4.0. Results also indicated that those expectations, drivers, and barriers might be related to each other, concurrently affecting more than one KM activity. These results supported the formulation of four propositions for future theory testing and validation, raising the awareness of instructors and lecturers regarding those aspects.

Date: 2023
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DOI: 10.1080/14778238.2022.2088418

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