Demographic Dynamics of Data Analytics Readiness: A Comparative Exploration of Chinese Higher Education Faculty?
DOI:
https://doi.org/10.37134/Keywords:
Big data, DELTA, Higher educationAbstract
Amid the growing imperative for digital transformation in higher education, the readiness of academic faculty to adopt data analytics tools remains underexplored, particularly in the Chinese context. This study investigates the influence of demographic and professional characteristics on faculty readiness for big data analytics (BDA) across International Scholarly Exchange Curriculum (ISEC) and non-ISEC institutions. The primary objective is to examine differences in BDA readiness across variables such as ISEC affiliation, gender, professional rank, and educational background. Using a non-experimental causal-comparative design, data were collected from 154 full-time faculty members across 10 Chinese universities. A modified DELTA+ model served as the assessment framework, covering six key dimensions of analytics readiness: data, enterprise, leadership, targets, technology, and analysts. Statistical analysis using t-tests and two-way ANOVA revealed that while most readiness dimensions did not significantly differ, technology readiness was significantly higher among non-ISEC faculty. Gender, rank, and education showed no main effects, though a significant interaction between ISEC status and education was observed. These findings underscore the complexity of technological readiness and suggest that institutional affiliation and educational background interact in shaping analytics capabilities. The study calls for targeted institutional policies and further research to refine professional development strategies in higher education.
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