Stevan STANKOVSKI
Generative artificial intelligence (GenAI) is transforming modern higher education by providing new opportunities for teaching, learning, and research. In the context of mechatronics and industrial engineering education, GenAI tool applications in programming and industrial automation instruction are particularly interesting. These fields require developing complex cognitive skills, such as abstract thinking, logical reasoning, and understanding physical processes and design conventions. The question is how GenAI tools affect the development of these competencies. Do they speed up and deepen the development of these skills, or do they replace cognitive effort without fostering genuine understanding? This paper analyzes the use of GenAI tools in an academic setting, focusing on two technical areas: generating program code and designing electropneumatic schemes.
Duško ČUČKOVIĆ, Dejan IGOV
The aim of this paper is to analyze theoretical perspectives on the relationship between TQM and organizational innovation performance based on a review of the relevant literature. The analysis indicates that the relationship between TQM and organizational innovation performance is neither universally synergistic nor inherently conflictual, but rather depends on the dimensions of TQM, the type of innovation, and the organizational context. Particular emphasis is placed on distinguishing between soft and hard TQM practices, as well as between incremental and radical innovation. It is concluded that TQM can provide an important organizational foundation for innovation, while the effects of individual TQM practices depend on how they are implemented and on the specific requirements of different types of innovation.