Palabras clave
Educational analytics
Student well-being
Behavioral engagement
Decision support systems
Higher education
Strategic decision-making
Cómo citar
Resumen
Purpose: This study proposes a Competitive Intelligence Decision Support Framework (CI-DSF) for higher education, integrating academic performance, psychological well-being, and behavioral engagement as strategic inputs for institutional decision-making..
Methodology: A multi-dataset synthetic integration design was employed using construct-level data from four publicly accessible sources: PISA 2022 (full N ≈ 690,000), the China Education Panel Survey (n ≈ 20,000), the Open University Learning Analytics Dataset (n = 32,593; 10.6 million logs), and the UCI Student Performance Dataset (n = 649). The model was tested via Structural Equation Modeling (bootstrap = 5,000), behavioral analytics of LMS data, and cross-dataset validation.
Originality/Relevance: The study advances the literature by integrating Competitive Intelligence with educational analytics, shifting from predictive approaches to a strategic intelligence architecture, positioning student-level data as a core institutional intelligence asset.
Findings: Self-regulated learning was the strongest predictor of academic performance (β = 0.389), followed by social engagement (β = 0.341) and psychological well-being (β = 0.267), collectively explaining 58.7% of outcome variance (all p < .001). Cross-dataset validation provides evidence of consistent relationships across datasets. A theoretically specified moderation analysis indicates institutional competitive intelligence capability may strengthen the well-being–performance relationship under high-capability conditions.
Theoretical/methodological contributions: The study contributes by developing an integrative Competitive Intelligence model for higher education, transforming academic, behavioral, and psychological data into actionable intelligence. Methodologically, it introduces a novel multi-dataset integration approach for theory building and cross-context validation in heterogeneous educational environments.
Citas
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Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Derechos de autor 2026 Journal of Sustainable Competitive Intelligence