Effects of pedagogy and information technology utilization on innovation creation by SECI model

Abstract

In today’s society, innovation and creativity are needed in many areas, Unfortunately, graduated students miss out on employment opportunities due to a lack of creativity (Bateman 2013). Base on literature review, classroom observation and administrator s’ feedback, there are three areas to support student ‘s creativity: Learner Engagement, Physical Environment and Learning Environment (Richardson and Mishra, Thinking Skills and Creativity, 27, 45-54. 2018). A learning environment is an atmosphere of a classroom which influence the behaviors between teacher and students (Greenhow et al. 2011). The relationship among them leads to an integral role in supporting creativity. The role of freely communication, cooperation and trust each other is a good learning environment that emphasizes positive relationships, initiative and investigative learning towards the support of creativity (Peterson et al. 2005). And also fund that Nonaka’s SECI model developed from knowledge creation is the key source of creating innovation (Yuan-zi and Ting 2010) and the best-known conceptual framework for understanding knowledge generation processes to produce innovation(Farnese et al. Frontiers in Psychology, 10, 2730.2019). The SECI (Socialization, Externalization, Combination and Internalization) model can be applied in pedagogical content in order to generate, transfer and recreate explicit and tacit knowledge (Cheng 2019). To explores the study of learning environment, the purposes of this quantitative research were: (1) to study pedagogy, information technology utilization, and innovation creation using the SECI Model of undergraduate students, (2) to develop a causal model of innovation creation using the SECI Model of undergraduate students with knowledge sharing as mediator,(3) to validate the consistency of the developed causal model with the empirical data. The samples were 540 undergraduate students of three different disciplines, including health science, science and technology, and humanities and social sciences. The researcher used a questionnaire to collect the opinions. The research methodology as it was discussed in more details: Structure equation model (SEM) was used in this research to analyze direct and indirect effects of instruction and the use of information technology (IT) on creating innovation according to SECI Model. Sharing knowledge of undergraduate students is mediator variable. The variables used in this research are 1. Dependent variable which is one of the latent variables in creating innovation according to SECI Model and can be measured from 4 observed variables including (1) socialization (2) externalization (3) combination and (4) internalization. 2. Independent variables were 1) Pedagogies which consisted of (1) inquiry-based learning (2) cooperative learning (3) project-based learning (4) collaborative learning (5) brainstorming technique 2) The use of information technology (IT). The results were as follows: 1. Brainstorming techniques, inquiry method, collaborative learning method, project-based learning method, information technology utilization, and knowledge sharing among the undergraduate students were rated at the high level. The undergraduate students’ innovations created using the SECI Model were rated at the high level for both overall and each module: socialization, externalization, combination and internalization. 2. Regarding the causal model of innovation creation using the SECI Model of undergraduate students with knowledge sharing as mediator, it was found that the use of information technology resulted in partial mediator through knowledge sharing to innovation creation using the SECI Model. While inquiry method and collaborative learning method brought about perfect mediation through knowledge sharing, contributing to innovation creation using the SECI Model at a statistically significant level of .05. 3. The causal model of innovation creation using the SECI Model of undergraduate students with knowledge sharing as mediator was fit to the empirical data (Chi-Square, 82 n = 387) =100.064, p = 0.09, GFI = 0.98, AGFI = 0.96, NFI = 1.00, CFI = 1.00, RMR =0.01, RMSEA = 0.02 Seventy percent of the variables in the model could explain the variance of knowledge sharing and 77 % could explain the variance of innovation creation using the SECI Model.

Appendix

Table 4 Mean, Standard Deviation and Correlation Coefficient between observed variables in the research model