INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026  
Patterns of Non-Compliance: Mapping Behavioral Escalation and  
Programmatic Clustering in Student Disciplinary Records  
Roilingel P. Calilung1, Precious Bernadette DM Estrada2  
1University Library and Archives, University of the Assumption, Philippines  
2Office of Student Affairs, University of the Assumption, Philippines  
DOI: https://doi.org/10.51583/IJLTEMAS.2026.150500179  
Received: 16 May 2026; Accepted: 21 May 2026; Published: 11 June 2026  
ABSTRACT  
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.  
Keywords: student offenses, thematic analysis, disciplinary records, higher education, intervention planning  
INTRODUCTION  
Student discipline records within the Office of Student Affairs represent a vital institutional dataset that mirrors  
broader behavioral trends, peer social norms, and the evolving culture of rule compliance within higher  
education. These records provide more than a simple ledger of infractions; they serve as a diagnostic tool for  
understanding how students navigate institutional expectations and academic integrity. A systematic analysis of  
this data allows a university to transition from a reactive, case-by-case adjudication model toward an evidence-  
based framework capable of informing both preventive strategies and developmental interventions. Given the  
increasing complexity of campus environments, institutional responses must integrate quantitative trends with  
qualitative insights to address the multifaceted nature of student misconduct.  
This study examines student offense records from a private university over a three-year period, covering the  
academic years 2023–2024 through 2025–2026. The investigation focuses on the prevalence of both minor and  
major offenses, with a specific interest in how recurring non-compliance may signal a need for broader policy  
refinement. The collection and analysis of administrative logs—rather than direct human participation—ensures  
an objective overview of institutional discipline patterns. Ultimately, the findings provide the empirical basis for  
a tiered intervention plan designed to strengthen student support systems and promote a proactive approach to  
professional formation and discipline.  
LITERATURE REVIEW  
The management of student conduct in higher education has evolved from a purely punitive "discipline and  
punish" model toward a developmental and evidence-based framework. Modern research underscores that  
disciplinary challenges often reflect deeper institutional cultures, peer norms, and ethical sensitivities (Eaton &  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026  
Fishman, 2025). As university environments become more complex, the integration of restorative and proactive  
interventions has become essential for maintaining campus harmony and student well-being.  
Restorative and Developmental Frameworks  
A significant shift in contemporary scholarship is the advocacy for restorative justice (RJ) within the university  
setting. Unlike traditional models that focus on rule-breaking and punishment, RJ emphasizes the repair of harm  
and the engagement of stakeholders to rebuild community cohesion (Karp, 2024). In a study of South African  
higher education, Mokomane (2024) found that restorative responses to misconduct—particularly academic  
dishonesty—foster greater individual accountability and reduce recidivism compared to standard suspension  
protocols.  
Ethical Sensitivity and Academic Integrity  
The relationship between student behavior and ethical awareness remains a focal point of recent inquiry. Ethical  
sensitivity acts as a protective factor against rule violations; students with higher ethical capacities are less likely  
to engage in cheating or plagiarism (Zhao et al., 2025).  
However, the digital landscape has complicated this dynamic. Huang et al. (2025) note that the digital learning  
environment presents new ethical dilemmas that traditional policies may not fully address, requiring institutions  
to update their integrity programs to include digital-specific ethical training (Chen & Macfarlane, 2024).  
Data-Driven Interventions and Behavioral Patterns  
Institutions are increasingly leveraging data-driven decision support systems to manage these evolving  
behavioral trends. The application of thematic and cluster analysis to disciplinary logs allows researchers to  
identify specific "hotspots" of misconduct that might otherwise remain undetected.  
Longitudinal thematic analysis of student records reveals patterns often obscured in case-by-case adjudication  
(Lopez & Tan, 2023). This analytical depth facilitates "Program-Based Clustering," a method where  
interventions are tailored to the specific professional cultures of different academic majors, such as the high-  
stress environments typical of technology or business programs (Williams, 2025).  
Preventive Programming and Wellness  
Scholarship further emphasizes that many conduct issues, such as the use of prohibited substances like vaping,  
are deeply intertwined with student health and social dynamics. Vaping on campus is increasingly viewed as  
both a disciplinary and a wellness issue, requiring formal partnerships between student affairs and health offices  
(Smith & Brown, 2023). Furthermore, the implementation of predictive analytics and early monitoring systems  
provides a mechanism for timely administrative intervention.  
Tracking the escalation of minor non-compliance into major offenses allows the institution to act before  
behavioral patterns become ingrained (Miller, 2024). Collectively, these studies highlight the necessity of a  
tiered, data-informed approach to student conduct that balances rigorous policy enforcement with holistic student  
development.  
Research Questions  
1. What types of student offenses were most frequently recorded by the Office of Student Affairs over the  
past three academic years?  
2. What recurring themes and patterns emerge from the thematic analysis of student offense records  
during the period under study?  
3. How can the identified themes from student offense data inform the development of a targeted  
intervention plan by the Office of Student Affairs?  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026  
METHOD  
Research Design and Framework  
This study utilized a descriptive-qualitative research design centered on a mixed-method inquiry. This approach  
was selected to facilitate a comprehensive examination of student behavioral trends while extracting deep  
thematic insights from institutional records. The integration of quantitative frequency analysis with qualitative  
thematic exploration allowed the researchers to generate evidence-based insights necessary for strategic  
intervention planning and policy refinement within the University.  
Data Sources and Collection  
The primary dataset comprised administrative student discipline records from the Office of Student Affairs,  
spanning the academic years 2023–2024 through 2025–2026. These records documented a spectrum of  
infractions, ranging from minor regulatory non-compliance, such as dress code and identification violations, to  
major incidents including bullying, academic dishonesty, and vaping.  
The collection process involved a formal administrative request to access verified institutional logs. The  
researchers compiled these entries into a structured secondary dataset, categorized by academic program and  
offense type. The collection relied exclusively on existing administrative data with no direct student interaction  
to maintain ethical integrity. All entries were de-identified during the transcription process, with student names  
replaced by alphanumeric codes to ensure absolute confidentiality.  
Data Analysis and Statistical Treatment  
The analytical phase was executed in two distinct stages to provide both breadth and depth. Initially, a  
quantitative analysis was conducted to tabulate the frequency and distribution of offenses. Descriptive statistics,  
specifically totals and percentages, were computed to identify longitudinal trends across the three-year period.  
Subsequently, qualitative descriptions within the offense logs were subjected to thematic analysis using the six-  
phase framework established by Braun and Clarke (2006). This involved an inductive coding process where  
recurring behaviors were identified, reviewed, and categorized into broader themes. This thematic layer allowed  
the researchers to move beyond simple statistics and understand the contextual nuances of student misconduct.  
The statistical treatment remained aligned with this dual-mode design, employing both descriptive tabulation for  
frequency data and qualitative synthesis for the identified behavioral patterns.  
RESULTS  
Table 1  
Table 1: Frequency of Student Offenses by Classification  
Type of Offense  
Classification  
Minor  
A.Y. 2024–2025  
A.Y. 2025–2026  
F
Dress Code Non-  
compliance  
1,467  
818  
2,285  
Identification (ID)  
Non-compliance  
Minor  
Minor  
51  
22  
–
–
51  
22  
Prohibited Accessories  
(Earrings)  
Vaping/Substance Use  
Major  
Major  
–
–
18  
9
18  
9
Peer  
Aggression/Bullying  
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Classroom/Lab  
Misconduct  
Major  
Major  
Major  
–
7
7
Academic Dishonesty  
(Cheating)  
–
2
2
Recidivism (Escalated  
Minors)  
–
2
2
Total  
1,540  
856  
2,396  
The distribution of student offenses across the observed academic years indicates a heavy concentration of minor  
infractions compared to major disciplinary breaches (see Table 1). Data from the 2024–2025 and 2025–2026  
periods show that regulatory non-compliance, specifically regarding dress code and identification policies,  
accounts for the vast majority of cases, totaling 2,358 incidents. While minor violations were predominantly  
recorded in the 2024–2025 academic year, the subsequent year saw the emergence of more diverse major  
offenses. Although major infractions such as vaping (18 cases) and peer aggression (9 cases) appear statistically  
low relative to the total volume, they represent high-stakes behavioral shifts that necessitate immediate  
administrative attention. The presence of two cases of recidivism, where minor offenses escalated to major  
violations, further suggests that a small segment of the student population exhibits persistent non-compliance  
that traditional sanctions may not be effectively deterring.  
Table 2  
Emergent Themes and Impacted Academic Programs  
Emergent Theme  
Primary Indicators  
Frequency  
2,358  
Most Impacted Programs  
All Academic Programs  
Regulatory Non-  
compliance  
Uniform, ID, and  
Accessory violations  
Prohibited Substance  
Use  
BSIT, BSTM, BSBA,  
BSCE, BSIE  
Vaping incidents  
18  
9
Interpersonal Conflict  
Academic Disruption  
Aggression and Bullying  
BSIT, BSHM, BSBA  
BSIT, BSTM, BSCPE  
Gaming/Non-academic  
lab use  
7
Recidivism (Escalated  
Minors)  
Behavioral Escalation  
Academic Integrity  
2
2
BSCE, BSIE  
Cheating  
General Distribution  
Thematic analysis of the disciplinary logs revealed that student misconduct is not distributed randomly but rather  
clusters around specific institutional themes and academic tracks (see Table 2). Regulatory non-compliance  
remains a universal challenge across all academic programs, yet major infractions show distinct programmatic  
"fingerprints."  
For instance, prohibited substance use (vaping) and academic disruptions in laboratories were most prevalent  
among students in the BSIT and BSTM programs. Similarly, interpersonal conflicts, including aggression and  
bullying, were notably concentrated in technology and business-oriented tracks.  
These patterns suggest that the social and professional cultures within specific departments may influence  
behavioral norms. The identification of these clusters allows for a transition away from "one-size-fits-all"  
disciplinary measures toward program-specific behavioral guidance.  
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Table 3  
Tiered Priority Framework for Intervention Planning  
Behavior Cluster  
Total Cases  
2,358  
Institutional Impact  
Priority Level  
High  
Erodes professional  
standards and policy  
baseline.  
Institutional Discipline  
Culture  
Student Safety &  
Wellness  
Threatens physical health  
and campus climate.  
27  
7
High  
Learning Environment  
Integrity  
Disrupts pedagogy and  
classroom focus.  
Medium  
Medium  
Compromises academic  
and institutional rigor.  
Professional Ethics  
2
The translation of frequency data into a strategic priority framework highlights the dual nature of the University’s  
disciplinary challenges (see Table 3). While regulatory non-compliance regarding dress codes is categorized as  
a high priority due to its sheer volume and its impact on the institutional discipline culture, student safety issues  
such as vaping and aggression share this high-priority status because of the severity of their impact on campus  
wellness. Medium-priority clusters, including academic integrity and classroom misconduct, represent localized  
disruptions to the pedagogical environment. This tiered classification serves as the foundation for the proposed  
response plan, suggesting that the institution must simultaneously address widespread cultural non-compliance  
through broad professional standards while tackling high-risk major offenses through targeted, wellness-oriented  
interventions.  
DISCUSSION  
The three-year trajectory of student offenses at the University reveals a disciplinary landscape dominated by  
high-volume, low-severity infractions. Most striking is the sheer frequency of dress code and identification non-  
compliance—totaling over 2,300 cases. This is not merely a matter of students "forgetting" their uniforms.  
Instead, the data suggests a systemic normalization of minor non-compliance across nearly all academic  
programs. When a violation occurs this frequently, it ceases to be an individual outlier and becomes a cultural  
baseline. This trend aligns with the observations of Eaton and Fishman (2025), who argue that disciplinary  
challenges often mirror the internal peer norms of an institution rather than a simple lack of awareness.  
While the minor offenses are a matter of volume, the major offenses are a matter of geography. Misconduct is  
not evenly distributed; it clusters. The concentration of vaping and laboratory-based disruptions within the BSIT  
and BSTM cohorts points to a specific "behavioral fingerprint" within those departments. These programs, which  
often involve high-stress environments and specialized facilities, may harbor localized subcultures where certain  
prohibited behaviors are more socially permissible. This "Program-Based Clustering" (Williams, 2025) confirms  
that the Office of Student Affairs cannot rely on universal mandates alone. If the goal is to curb vaping or  
aggression, the intervention must be spoken in the "language" of the specific department where those behaviors  
are surfacing.  
Perhaps the most critical finding is the evidence of an "escalation pathway." The data shows that major  
disciplinary cases are rarely "lightning strikes" or isolated incidents. Rather, they are often preceded by a history  
of unaddressed minor infractions. We see this in the two major cases of recidivism: the transition from  
"regulatory non-compliance" to "major violation" is a measurable trajectory. This validates Miller’s (2024)  
emphasis on the importance of early monitoring. By the time a student reaches a major infraction, the institutional  
relationship has already been strained. Consequently, the University’s primary opportunity for behavioral  
correction lies not in the punishment of major offenses, but in the proactive disruption of minor patterns before  
they solidify into a chronic disciplinary identity.  
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CONCLUSION  
The systematic analysis of disciplinary records at the University indicates a significant divergence between high-  
frequency regulatory non-compliance and low-frequency, high-impact behavioral risks. The data reveals that  
minor offenses—specifically regarding the institutional dress code and identification policies—constitute the  
vast majority of infractions. With over 2,200 recorded instances, it is concluded that such violations have become  
systemic, suggesting that students may perceive these regulations as peripheral to their academic experience  
rather than as core components of professional formation.  
Furthermore, while major offenses such as vaping, bullying, and academic dishonesty occur with less frequency,  
they pose a more direct threat to the campus climate and student well-being. A critical finding of this study is  
the presence of "behavioral clustering," wherein specific types of misconduct are concentrated within certain  
academic programs, such as technology and business-oriented tracks. Finally, the evidence supports the  
existence of an escalation pathway; repeated minor infractions often serve as a measurable precursor to more  
serious disciplinary breaches. Consequently, the Office of Student Affairs must transition from a reactive, case-  
by-case adjudication model to a proactive, data-informed strategy that prioritizes early intervention and the  
disruption of negative behavioral trajectories.  
RECOMMENDATION  
Based on the findings and conclusions of this study, the following recommendations are proposed for the Office  
of Student Affairs:  
1. Reconceptualization of Policy Orientation: It is recommended that the university frame the  
institutional dress code and ID policies as "Professional Readiness Standards." The OSA may reduce the  
high volume of minor offenses and foster a more profound internalization of institutional values among  
the student body by aligning compliance with future workplace expectations.  
2. Implementation of Program-Specific Interventions: The OSA should collaborate with college deans  
to develop targeted behavioral workshops for academic programs identified as high-frequency clusters.  
These interventions should address the specific nature of misconduct prevalent in those fields, such as  
digital etiquette for technology students or conflict resolution for business majors.  
3. Integration of Disciplinary and Wellness Services: For major offenses involving substance use  
(vaping) or interpersonal aggression, the university should adopt a multi-disciplinary approach. This  
involves a formal partnership between the OSA and University Health Services to ensure that disciplinary  
actions are supplemented by counseling and wellness support.  
4. Establishment of a Conduct Early Warning System (CEWS): To prevent the escalation of minor  
infractions into major violations, the institution should implement an automated monitoring flag. A  
mandatory guidance session should be triggered upon a student’s third minor offense, allowing for  
administrative mentoring before the behavior reaches a critical disciplinary threshold.  
5. Promotion of Restorative Accountability Models: The university should move toward restorative  
justice frameworks for cases of peer conflict and bullying. The institution can cultivate a campus  
environment where discipline is maintained through shared responsibility rather than solely through  
punitive measures by focusing on the repair of harm and community cohesion.  
Compliance with Ethical Standards  
The study was conducted in strict adherence to established ethical standards governing the use of institutional  
and archival records. Primary consideration was given to data confidentiality; all personal identifiers and student  
names were removed or anonymized at the point of collection, ensuring that the findings were reported solely  
through aggregate data. Furthermore, formal institutional approval and written permission were secured from  
the Office of Student Affairs prior to the retrieval and analysis of the disciplinary logs. Given the non-intrusive  
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nature of the research design, the study relied exclusively on existing secondary data with no direct interaction  
with the student body, thereby eliminating physical or psychological risk to participants. Data integrity and  
security were maintained by storing all digital records in an encrypted environment accessible only to the primary  
researchers. These combined measures ensured full compliance with both institutional policies and international  
ethical guidelines regarding the protection of privacy and the responsible academic use of administrative records.  
REFERENCES  
1. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in  
Psychology, 3(2), 77-101.  
2. Chen, X., & Macfarlane, B. (2024). The importance of promoting a culture of academic integrity in  
higher education institutions in China. Psicologia: Reflexão e Crítica, 37(1), 12-25.  
3. Eaton, S. E., & Fishman, T. (2025). Collegiate honor codes and mandatory reporting: Have we gone too  
far? Journal of Academic Ethics, 23(2), 145-160.  
4. Huang, C. L., Shao, X., & Wu, C. (2025). Navigating the digital learning landscape: Insights into ethical  
dilemmas and academic misconduct among university students. International Journal of Educational  
Technology in Higher Education, 22(29).  
5. Karp, D. R. (2024). Restorative justice in higher education: A review of the literature. In Restorative  
Justice and Practice in US Education (pp. 217-246). Springer Nature.  
6. Lopez, M., & Tan, K. (2023). Qualitative themes in student misconduct: A five-year longitudinal study.  
Journal of Student Affairs Research and Practice, 60(4), 412-428.  
7. Miller, J. (2024). Data-driven decision making in student affairs: From spreadsheets to strategy. Higher  
Education Quarterly, 78(1), 88-102.  
8. Mokomane, R. B. (2024). Restorative justice as an alternative response to student academic dishonesty  
in South African higher education institutions. Potchefstroom Electronic Law Journal, 27, 1-35.  
9. Smith, L., & Brown, T. (2023). Vaping and the campus climate: Policy implications for health and  
discipline. Journal of American College Health, 71(5), 567-575.  
10. Williams, D. (2025). Cultural silos: Why disciplinary infractions vary by academic major. Educational  
Sociology Review, 19(3), 201-218.  
11. Zhao, Y., et al. (2025). The efficacy of ethics workshops in reducing recidivism in student conduct cases.  
Journal of Moral Education, 54(1), 33-49.  
ANNEX A  
Proposed Targeted Intervention Plan  
Based on the thematic clusters identified (Dress Code, Substance Use, and Peer Conflict), the following tiered  
intervention framework is proposed for the Office of Student Affairs:  
1. The "Visible Campus" Initiative (Primary Prevention)  
Target: Dress code non-compliance and ID violations (2,285 cases).  
Action: Transition from punitive "policing" to a "Professional Readiness" campaign. Instead of treating  
uniforms as mere rules, frame them as preparation for workplace standards.  
Mechanism: Use digital signage and social media "spotlights" on students correctly wearing their  
uniforms, rather than only highlighting infractions.  
2. The Behavioral Wellness Program (Secondary Intervention)  
Target: Vaping (18 cases) and behavioral misconduct in labs (7 cases).  
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Action: Implement "Health over Habits" seminars. Since vaping is often a social or stress-coping  
behavior, the intervention should involve the University Health Services to provide cessation support  
rather than just disciplinary notes.  
Mechanism: Program-specific workshops for BSIT, BSTM, and BSBA-MM students, focusing on  
digital etiquette and the health impacts of vaping in enclosed academic spaces.  
3. Restorative Justice Circles (Tertiary Intervention)  
Target: Aggression, Bullying, and Peer Conflict (9 cases).  
Action: Move away from traditional suspension for first-time physical aggression. Implement  
Restorative Justice Circles where the offender, the victim, and a student mediator discuss the harm  
caused.  
Mechanism: Focus on accountability and "making it right" to prevent the escalation of conflict within  
interpersonal-heavy programs like BSHM and BSBA-MM.  
4. The Student Conduct Early Warning System (SCEWS)  
Target: Repeated minor offenses (2 major escalations).  
Action: Create an automated flag in the OSA database. When a student hits their 3rd minor offense,  
they are automatically scheduled for a "Guidance Check-in" before reaching the 5th offense (which  
triggers a major violation).  
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