:: Volume 14, Issue 2 (9-2017) ::
QJFR 2017, 14(2): 87-104 Back to browse issues page
The Power of Intellectual Capital and Knowledge Management in Predicting Teachers’ Learning
M. Samiee Zafarghandi, Ph.D. , N. Aghakasiri
Abstract:   (6071 Views)
The purpose of this study was to identify the power of intellectual capital and knowledge management in predicting teachers’ learning. In this applied research, the design was descriptive and correlational. The statistical population of the study comprised all schoolteachers in Tehran. The sample size was determined to be 550 according to Morgan’s table and the participants were selected through simple random sampling method. The instruments consisted of Organization Learning Capability Scale (Jerez-Gómez, 2005), Knowledge Management Questionnaire (Rezai Malek, Radfar & Reshadatjou, 2012) as well as Intellectual Capital Questionnaire (Bakhtiyariyan Shahri & Faraji, 2014). Despite the fact that the instruments had already been standardized, their validity and reliability were examined through content validity, factorial validity and Cronbach’s alpha coefficient. The KMO index was greater than 0.6 and equal to 0.735 and the internal consistency of the measure was 0.935. Hence, the validity and reliability of the instruments were approved. The obtained data were analyzed through linear regression analysis. Results revealed that there was a significant, positive relationship between knowledge management, intellectual capital, and teachers’ learning. Furthermore, the results demonstrated that dimensions of intellectual capital, i.e., structural, human, and relational capital, held the power for predicting 29, 28, and 27 percent of variance in teachers’ learning. Moreover, dimensions of knowledge management, i.e., knowledge identification, creation, and transfer, could predict 20, 39 and 26 percent of variance in teachers’ learning.
 
 
Keywords: knowledge management, intellectual capital, learning, teachers
Full-Text [PDF 682 kb]   (3601 Downloads)    
Type of Study: Research | Subject: Special
Received: 2016/06/22 | Accepted: 2017/05/6 | Published: 2017/09/5


XML   Persian Abstract   Print



Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 14, Issue 2 (9-2017) Back to browse issues page