Construction Of Digital Competency Index System For Engineering Students In The Digital-era

The development of emerging digital intelligence technologies such as big data,enabled the industry to gradually realize digitalization and intelligence.At present,the most prominent problem in the digital and intelligent transformation of Chinese enterprises,especially the SMEs,is the lack of support for high-quality talents,especially composite and innovative digital talents.As a talent traning base,it has become an important task to provide high-quality digital talents for industrial production activities.Therefore,strengthening the cultivation of engineering students’ digital competency has become one of the important goals of universities.What is digital competency? What are the specific requirements for the digital competency of engineering students? Before strengthening the digital competency of engineering students,these are two issues that must be solved.At present,although the importance of the digital competency of engineering students is self-evident,the research on the digital competency of engineering students in China is very weak,and few scholars have conducted in-depth discussions on the connotation and requirements of the digital competency of engineering students.Therefore,this study aims to conceptually define the digital ability of engineering students on the basis of literature analysis,and try to construct a set of digital competency index system for engineering students,in order to provide a certain reference for the formulation of specific training programs.With the help of the iceberg model of ability and quality proposed by Spencer and Mc Clelland,through in-depth interviews with engineering teachers,students and enterprise practitioners,a digital competency index system for engineering students is preliminarily constructed,including two first-level indicators of benchmark ability quality and discriminating ability quality,as well as nine second-level indicators of basic knowledge,professional knowledge,data skills,digital research and development and design,digital equipment use,digital system thinking,learning adaptability,digital ethics,and communication and cooperation ability.In order to ensure the scientific nature of the indicators,experts are invited to evaluate the indicators using the Delphi method.A total of two rounds of expert consultations were completed in this study,the first round of 51 expert questionnaires was recovered,and the second round of 67 expert questionnaires were recovered.Through the analysis of two rounds of data,the two indicators of "cloud-based data storage and management can be carried out to protect digital resources in engineering activities" and "can choose to use more efficient and lower cost digital resources and equipment" are finally excluded.The final digital competency index system for engineering students includes 2 first-level indicators,9 second-level indicators and 33 third-level indicators(specific requirements).