EDUCATIONAL BIG DATA MANAGEMENT FACTORS AFFECTING EFFECTIVENESS OF ART UNIVERSITIES IN SHENYANG CITY UNDER LIAONING PROVINCE
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Abstract
The objectives of this research were: (1) to study the component of educational big data management, the effectiveness of art universities, adoption technology skills, and teaching skills of art universities in Shenyang city under Liaoning Province; (2) to develop the model of educational big data management, adoption technology skills, and teaching skills factors affecting the effectiveness of art universities in Shenyang city under Liaoning Province, and (3) to decompose the effect of educational big data management, adoption technology skills and teaching skills on the effectiveness of art universities in Shenyang city under Liaoning Province. The population of this research was 1,037 teachers from 15 art universities in Shenyang city under Liaoning Province. The sample was 504 teachers, determined by the G*Power program (power of test .80), and using a stratified random sampling method. The data was analyzed by descriptive statistics, Confirmatory Factor Analysis, and Structural Equation Model.
The research found that: (1) Educational big data management components consisted of data collection, data storage and analysis, decision making, and impact on teaching. The components of effectiveness of art universities consisted of educational quality, student success, faculty excellence, research impact, and community engagement. The components of adoption technology skills consisted of technical proficiency, technology integration, training and support, and barriers to adoption. The components of teaching skills consisted of pedagogical competence, classroom management, communication skills, and assessment and feedback; (2) the model of factors affecting effectiveness of art universities fit well with empirical data (X²/df=2.542, GFI=0.935, AGFI=0.912, NFI=0.926, IFI=0.954, CFI=0.953, TLI=0.944, RMSEA=0.055); and (3) educational big data management, adoption technology skills, and teaching skills had positive direct effect on effectiveness of art universities. Educational big data management had indirect effect on effectiveness of art universities via adoption technology skills and teaching skills, as the mediating effect. So, the effectiveness of art universities should be development on adoption technology skills and teaching skills together.
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References
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