Know-why? and know-how? in the development of nuclear talents: An analysis of recent nuclear engineering Ph. D. research

The relationship between the industry and academia is widely considered the key driver or obstacle in producing and using new knowledge. This is, at least in part, a consequence of different forms of knowledge being of different utility for the industry and academia (conceptual, e.g., why? and procedural, e.g., how?). In so-called "high-tech" industries, where the attraction and development of new talents are in significant part carried out through academic research-based higher education system, successful cooperation in the development of new knowledge automatically results in successful attraction and development of new talents. In well-established, strongly regulated, and very procedural industries, such as nuclear power, the pragmatic focus on procedural over conceptual knowledge may also result in the pathways of talent development outside of the research-based higher education system. Some definitions, features, and risks of different approaches to conceptual and procedural knowledge are outlined and discussed in the paper and an attempt is made to connect them with the notions of basic and applied research. It is suggested that suitable sequences and balance of know-why? and know-how? may lead to the best results in the attraction and development of new nuclear talents, while minimizing the risks of reduced ability to manage unexpected, reduced need for innovation and weakening the nuclear knowledge centers outside of the industry and regulators. This is supported by an analysis of 51 Ph.D. theses in nuclear engineering developed in Slovenia since 1993 to discern their contributions towards basic or applied research. The Pasteur's quadrant, developed by (Stokes, 1997), was used as the underlying framework. Ph.D. graduates and supervisors were independently asked to evaluate the basic and applied contributions through three variables, describing the stages of the creative research process: input, processing, and output, respectively. The predominantly mixed (basic and applied) contributions of the analyzed Ph.D. theses indicate that academic nuclear engineering education is an enabler of successful careers in academia and industry.