Article Preview
Top1. Introduction
As China's economy has ushered in a new normal and the economic growth is innovation-driven other than previously investment- and factor-driven, innovation and entrepreneurship research has become a focused area in higher vocational colleges. As the direct performers of talent training, teachers need to strengthen their innovation and entrepreneurship competency so as to improve the overall level of these competencies in higher vocational colleges. However, in the academic circle, there is a research gap in the evaluation and promotion strategies of college teachers' innovation and entrepreneurship competency. How to evaluate the innovation and entrepreneurship competency of teachers in the higher vocational colleges to help improve such competencies has become one of the core issues in the reform and development of higher vocational education(Lee et al.,2011; White,1959).
Iceberg model theory was put forward by famous American psychologist McClelland in 1973(McClelland, 1973). According to the different manifestation of individual qualities, professor McClelland classified iceberg into two parts, one is superficial “part of the iceberg above the surface,” and the other is deep “part of the iceberg below the surface” The “part of the iceberg above the surface” that includes knowledge and skills are the external manifestations which can easily be understood and measured. Thus they are relatively easy to change through training and development. The “part of the iceberg below the surface” that includes social roles, self-image, features, and motivation are the internal manifestation and difficult to be measured. Although this part is less likely to be influenced and changed by the surroundings, it plays a crucial role in people’s behavior and performance. McClelland thinks that traditional intelligence and aptitude tests cannot predict people's professional success and other important achievements (McClelland,1998). He advocates the exploration of individual conditions and real behavioral characteristics, which is called the competency that affects job performance. Many researchers believe that the competency model is becoming an important part of human resource management, so modern enterprise management should use competency evaluation to predict job performance (Shipmann et al.,2000; Sandberg,2002; Yamazaki,2014; Parry,2009; Smolensky,1986).
Western studies of competency evaluation of teachers in universities started earlier. Representative methodologies are as follows: balanced scorecard, statistical analysis, Markov chain method, Analytic Hierarchy Process (AHP), comprehensive evaluation method, management by objectives, key performance indicators(Spencer and Spencer,1993; Boyatzis,1982; Glockshuber,2007; Stewart,2010; Erlich and Shaughnessy,2014) and so on. Chinese scholars have been continually improving and complementing models, methods, and techniques of teachers’ competency evaluation on the foundation of the experiences and results of western studies(Zhong,2011). Scholars such as Wang (2005), Qin(2007), and Zhang(2009) have used the method of 360-degree feedback on the evaluation of teachers’ performance, putting forward relevant evaluation criteria, procedures, and implementing strategies. Guo (2006), Xu (2007), and Cao (2012) have studied programs, models, and management of the performance evaluation of the teachers based on the balanced scorecard in universities. Xu (2007) has used AHP and fuzzy mathematics to establish an evaluation model. Zhu(2007) has analyzed the cases in universities by means of rough set theory and distinguished matrix to explore the rules of evaluation and obtain objective weighting of evaluating factor. Chen (2012) has made empirical analysis on the evaluation of teachers, suggesting the index of evaluation should be designed from developing strategies in the university. Su(2007) has applied AHP to the evaluation of teachers to determine the weight and build the right index of the evaluation system. Huang et al.(2020) have analyzed the influence of university students’ learning beliefs on their intentions to use mobile technologies in learning. Owusu(2020) has analyzed the determinants of Cloud Business Intelligence Adoption Among Ghanaian SMEs. Amo et al.(2020) has designed and implemented a solution based on a student’s data pseudonymization through aliases to enable adequate levels in confidentiality issues.