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Assessment of Data Analytics Maturity and Readiness in the Curriculum Planning for the Second-Year Electronics and Computer Technology Program at Top Link Global College Inc.


Authors : Fette Kyle G. Cabral

Volume/Issue : Volume 11 - 2026, Issue 4 - April


Google Scholar : https://tinyurl.com/5n86hvae

Scribd : https://tinyurl.com/mrcuhumt

DOI : https://doi.org/10.38124/ijisrt/26apr1199

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.


Abstract : The rapid technological evolution of Industry 4.0 necessitates agile, evidence-based curriculum planning in technicalvocational education to mitigate the ongoing skills mismatch. This study assessed the data analytics maturity and organizational readiness of the Electronics and Computer Technology (ECT) program at Top Link Global College Inc., focusing specifically on the curriculum planning processes for second-year students. Employing a descriptive-quantitative research design, a complete enumeration of ten (10) academic administrators and faculty members was surveyed using a structured instrument adapted from the DELTA Plus and Technology Acceptance Model 2 (TAM 2) frameworks. Findings revealed that the department operates in a "Maturing" phase of data analytics (Mean = 3.59) but experiences a severe analytical bottleneck in Data Usage (Mean = 3.10), struggling to transition from historical reporting to predictive analytics. Furthermore, organizational readiness was deemed "Moderately Ready" (Mean = 3.20), critically hindered by inadequate technological infrastructure (Mean = 1.70). This lack of automated infrastructure directly causes the primary operational barrier: severe time constraints and manual workloads for the faculty. To bridge the resulting velocity gap and resolve the operational perception disparities between administrators and teaching staff, the study proposed a localized Data-Driven Decision Support Framework. This framework emphasizes centralized data automation, targeted data literacy for Outcomes-Based Education (OBE) translation, and agile integration protocols to ensure graduates are equipped with the competencies demanded by the modern electronics industry.

References :

  1. Celeste, Rifel Jeene , and Nimfa Osias. “Challenges and Implementation of Technology Integration: Basis for Enhanced Instructional Program.” American Journal of Arts and Human Science, vol. 3, no. 2, 4 June 2024, pp. 106–130, https://doi.org/10.54536/ajahs.v3i2.2656.
  2. CHED. “Policies, Standards and Guidelines for the Bachelor of Science in Electronics Engineering (BSECE) Program Effective Academic Year (AY) 2018-2019.” Ched.gov.ph, 2017, www.ustp.edu.ph/wp-content/uploads/2023/07/BS_ECE_CMO-101-s.-2017-BS-Electronics-Engineering.pdfwww.ustp.edu.ph/wp-content/uploads/2023/07/BS_ECE_CMO-101-s.-2017-BS-Electronics-Engineering.pdf.
  3. Cleary, Jennifer, and Michelle Noy. A Framework for Higher Education Labor Market Alignment: Lessons and Future Directions in the Development of Jobs--Driven Strategies. Oct. 2014.
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  6. Morison, Robert, and International Institute for Analytics (IIA). Analytics Maturity Transition Guide: Stage 1 to Stage 2. Apr. 2023, https://iianalytics.com/uploads/portal-supplemental-resources/IIA-Research-Stage-1-2-Transition-Guide.pdf
  7. Schorr, Angela. “The Technology Acceptance Model (TAM) and Its Importance for Digitalization Research: A Review.” Sciendo EBooks, 16 June 2023, pp. 55–65, https://doi.org/10.2478/9788366675896-005.
  8. SEPO. “Policy Brief on Enterprise-Based Training.” Egacy.senate.gov.ph, Aug. 2024, legacy.senate.gov.ph/publications/SEPO/SEPO_Policy%20Brief%20on%20Enterprise-based%20Training_final.pdf.

The rapid technological evolution of Industry 4.0 necessitates agile, evidence-based curriculum planning in technicalvocational education to mitigate the ongoing skills mismatch. This study assessed the data analytics maturity and organizational readiness of the Electronics and Computer Technology (ECT) program at Top Link Global College Inc., focusing specifically on the curriculum planning processes for second-year students. Employing a descriptive-quantitative research design, a complete enumeration of ten (10) academic administrators and faculty members was surveyed using a structured instrument adapted from the DELTA Plus and Technology Acceptance Model 2 (TAM 2) frameworks. Findings revealed that the department operates in a "Maturing" phase of data analytics (Mean = 3.59) but experiences a severe analytical bottleneck in Data Usage (Mean = 3.10), struggling to transition from historical reporting to predictive analytics. Furthermore, organizational readiness was deemed "Moderately Ready" (Mean = 3.20), critically hindered by inadequate technological infrastructure (Mean = 1.70). This lack of automated infrastructure directly causes the primary operational barrier: severe time constraints and manual workloads for the faculty. To bridge the resulting velocity gap and resolve the operational perception disparities between administrators and teaching staff, the study proposed a localized Data-Driven Decision Support Framework. This framework emphasizes centralized data automation, targeted data literacy for Outcomes-Based Education (OBE) translation, and agile integration protocols to ensure graduates are equipped with the competencies demanded by the modern electronics industry.

Paper Submission Last Date
31 - May - 2026

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