A data analytics driven digital supervision model for enhancing school counselors’ competencies in the era of technological transformation
Abstract
This study addresses the need to enhance school counselors’ professional competencies through innovative supervision approaches in the era of digital transformation. The study aimed to develop and validate a data analytics-based digital supervision model for school counseling using a mixed-methods design. The quantitative phase involved 150 school counselors whose competencies were measured using a validated scale (Cronbach’s ? = .89). Results showed a significant increase in competency scores from 3.45 (SD = 0.52) before the intervention to 4.21 (SD = 0.48) after the intervention, with a mean difference of 0.76. A paired-samples t-test indicated a statistically significant improvement, t(149) = 12.34, p < .001, with a large effect size (Cohen’s d = 1.29). The qualitative phase included 30 semi-structured interviews with counselors, supervisors, and school principals. Findings revealed improvements in digital literacy, reflective practice, evidence-based decision-making, collaboration, and professional competence supported by real-time feedback. The integrated findings led to the development of a digital supervision framework incorporating data dashboards, predictive analytics, and adaptive feedback mechanisms. The results demonstrate that data-driven digital supervision effectively strengthens school counselors’ competencies and supports continuous professional development in technology-enhanced educational environments.
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