Patterns of Non-Compliance: Mapping Behavioral Escalation and Programmatic Clustering in Student Disciplinary Records

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Roilingel P. Calilung
Precious Bernadette DM Estrada

Managing student conduct in a private higher education context requires a transition from anecdotal observation to empirical analysis. This study examined three academic years (2023–2026) of student offense records from the Office of Student Affairs to identify behavioral trajectories across various academic programs. By applying a dual-mode strategy—quantitative frequency mapping alongside inductive thematic analysis—the researchers uncovered a disciplinary landscape defined by two distinct pressures. First, the data reveals a systemic normalization of regulatory non-compliance, specifically regarding dress code and identification policies, which accounted for the vast majority of infractions. Second, while major violations like vaping, peer aggression, and academic dishonesty are statistically fewer, their concentration in specific technology and business-oriented cohorts suggests localized behavioral "hotspots." Crucially, the findings validate an escalation pathway: repeated minor infractions often serve as measurable precursors to more severe disciplinary breaches. These results form the basis of a proposed tiered intervention framework that shifts institutional response from reactive adjudication to proactive, program-specific behavioral formation.

Patterns of Non-Compliance: Mapping Behavioral Escalation and Programmatic Clustering in Student Disciplinary Records. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(5), 2246-2253. https://doi.org/10.51583/IJLTEMAS.2026.150500179

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Patterns of Non-Compliance: Mapping Behavioral Escalation and Programmatic Clustering in Student Disciplinary Records. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(5), 2246-2253. https://doi.org/10.51583/IJLTEMAS.2026.150500179