Abstract
Nine Principles for Deep Knowledge of Habitual Domains (HDs) have been identified as an effective approach to expanding and enriching an individual’s HD, or in a broader sense, to improving learning. The purpose of this study was to examine the Principle for Deep Knowledge Survey (PDKS) and the correlations between the PDKS and other individual variables, such as gender, body mass index (BMI), and exercise routines. Seven hundred eighty-five industrial high school students completed the questionnaire. Overall, the results suggested that the psychometric properties of the PDKS were acceptable and also showed a significant relationship between gender and the Principles of Contrasting and Complementing and Cracking and Ripping. In addition, the Principles of Alternating, Changing and Transforming, and Void had a positive correlation with the variable of frequency of exercise. The results showed that exercise could be a mediator in expanding the competence of deep knowledge to improve learning.
Highlights
The Principles for Deep Knowledge have been identified by Habitual Domain (HD) as one of the three effective tool boxes for expanding an individual’s Habitual Domains (HDs)
The confirmatory factor analysis (CFA) indicated a good fit for Principle for Deep Knowledge Survey (PDKS): χ2(428) = 112.384, p = .000, Comparative Fit Index (CFI) = 0.93, Tucker–Lewis Index (TLI) = 0.92, Root Mean Square Error of Approximation (RMSEA) = 0.05, and Standardized Root Mean Square Residual (SRMR) = 0.04
Each of the nine factors displayed a satisfactory level of discriminant validity when measured by the average variance extracted (AVE; Fornell & Larcker, 1981)
Summary
The Principles for Deep Knowledge have been identified by Habitual Domain (HD) as one of the three effective tool boxes for expanding an individual’s HD Researchers in this field have disclosed a wealth of applications in mathematical L. Yu & Zhang, 1989a,1989b) and qualitative L. Yu & Chen, 2010; P. The previous literature has demonstrated that many methods have contributed to the expansion of HD, including the nine Principles for Deep Knowledge. The literature lacked quantitative evidence, such as questionnaires
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