Technology Utilization and Strategic Decision-Making Competence Among School Leaders in a State University

Abstract

This study presents an item-level diagnostic analysis of technology utilization and strategic decision-making competence among 81 school leaders in a multi-campus Philippine state university. The analysis uses the same 2025–2026 survey dataset as the parent dissertation but addresses a distinct descriptive question: which specific technology-supported leadership practices and strategic decision behaviors appear most and least developed at the indicator level? Eighteen technology-utilization items and 20 strategic decision-making competence items were examined using their reported means, standard deviations, and 95% confidence intervals. Technology-utilization item means ranged from 3.62 to 4.26. Digital records and documentation received the highest rating (M = 4.26), whereas use of forecasting tools or trend data for long-term decisions received the lowest (M = 3.62). Strategic competence item means ranged from 3.99 to 4.41. Clear problem definition was rated highest (M = 4.41), while consideration of multiple perspectives was lowest (M = 3.99). A descriptive alignment of conceptually related indicators suggested a recurring pattern: leaders reported favorable strategic competence, but the digital practices that support forecasting, alternatives appraisal, target setting, and post-decision monitoring were comparatively less intensive. The findings support focused leadership development around analytical and forward-looking technology use while preserving established strengths in records management, planning alignment, and feedback-oriented implementation. The analysis is descriptive and does not infer causal or item-to-item statistical relationships.

Introduction

This study examines how school leaders at Cebu Normal University use digital technologies and how they assess their strategic decision-making competence. It emphasizes that digital transformation involves more than using software for routine administrative tasks; it also requires applying digital tools to forecasting, evidence-based planning, evaluating alternatives, and monitoring decision outcomes.

The study uses a quantitative, nonexperimental, descriptive secondary analysis of survey data collected from 81 school leaders across the Main, Medellin, and Balamban campuses during the 2025–2026 dissertation study. It analyzes 18 technology-utilization indicators and 20 strategic decision-making competence indicators using item means, standard deviations, and confidence intervals. It also compares conceptually related indicators descriptively without claiming statistical relationships or causation.

Key Findings

1. Technology utilization

The highest-rated practice was using digital systems for institutional records and documentation (mean = 4.26). Online communication, workflow management, and using institutional data for planning were also highly rated.

The lowest-rated practices involved using forecasting tools and trend data for long-term decisions (mean = 3.62), applying data systems for evidence-informed leadership (3.69), comparing alternatives using technology (3.74), and using digital analytics for target setting and program development.

2. Strategic decision-making competence

The highest-rated competency was clearly defining institutional problems before proposing solutions (mean = 4.41). Aligning decisions with institutional goals, considering long-term impacts, anticipating future challenges, and using feedback to evaluate outcomes were also highly rated.

The lowest-rated competency was considering multiple perspectives when analyzing organizational issues (mean = 3.99). Other relative weaknesses included identifying root causes, establishing accountability, integrating digital transformation into institutional strategy, and evaluating the consequences of alternative decisions. Nevertheless, all competency ratings remained generally favorable.

3. Alignment between technology use and leadership competence

The comparison identified four important areas for improvement:

• Foresight: Leaders reported strong future-oriented thinking, but the use of digital forecasting tools was comparatively low.

• Evidence and target setting: Leaders demonstrated favorable planning competence, while digital analytics and performance indicators were used less intensively.

• Alternatives and problem analysis: Defining problems was a strength, but technology-supported comparison of alternatives and consideration of multiple perspectives could be strengthened.

• Implementation monitoring: Leaders reported effective use of feedback, but digital monitoring systems and accountability mechanisms offered opportunities for further development.

These findings represent descriptive differences in reported practices, not statistically proven relationships.

Conclusion

At the item level, the surveyed school leaders reported the strongest technology use in digital records, communication, and workflow support, while forecasting, alternatives appraisal, target-setting indicators, and evidence-oriented strategic systems were comparatively less intensive. Strategic decision-making behaviors were broadly favorable, with particular strengths in problem definition, institutional alignment, future orientation, and feedback use. The combined descriptive pattern suggests that the next stage of digital leadership development should focus less on basic administrative digitization and more on analytical, forward-looking, and monitoring-oriented uses of institutional technology. These findings are intended as a diagnostic basis for capacity-building, not as evidence that technology use causes strategic competence.

References

[1] Alenezi, M. (2021). Deep dive into digital transformation in higher education institutions. Education Sciences, 11(12), 770. https://doi.org/10.3390/educsci11120770 [2] Carvalho, M., Cabral, I., Verdasca, J. L., & Alves, J. M. (2021). Strategy and strategic leadership in education: A scoping review. Frontiers in Education, 6, Article 706608. https://doi.org/10.3389/feduc.2021.706608 [3] Chigbu, B. I., & Makapela, S. L. (2025). Data-driven leadership in higher education: Advancing sustainable development goals and inclusive transformation. Sustainability, 17(7), Article 3116. https://doi.org/10.3390/su17073116 [4] Jameson, J., Rumyantseva, N., Cai, M., Markowski, M., Essex, R., McNay, I., & Clough, G. (2022). A systematic review and framework for digital leadership research maturity in higher education. Computers and Education Open, 3, Article 100115. https://doi.org/10.1016/j.caeo.2022.100115 [5] Koh, G. A., Askell-Williams, H., & Barr, S. (2023). Sustaining school improvement initiatives: Advice from educational leaders. School Effectiveness and School Improvement, 34(3), 298–330. https://doi.org/10.1080/09243453.2023.2190130 [6] Lee, C., Camburn, E. M., & Sebastian, J. (2024). School context, school leaders’ data-informed decision making, and student achievement: Evidence from Florida. School Effectiveness and School Improvement, 36(1), 1–26. https://doi.org/10.1080/09243453.2024.2436889 [7] McCarthy, A. M., Maor, D., McConney, A., & Cavanaugh, C. (2023). Digital transformation in education: Critical components for leaders of system change. Social Sciences & Humanities Open, 8(1), Article 100479. https://doi.org/10.1016/j.ssaho.2023.100479 [8] Tawse, A., & Tabesh, P. (2021). Strategy implementation: A review and an introductory framework. European Management Journal, 39(1), 22–33. https://doi.org/10.1016/j.emj.2020.09.005

Copyright

Copyright © 2026 Shiena Niña R. Abarquez. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.