Entropy-Weight Derivation for Ranking STEM–CBE Preparedness Indicators in Public Senior Secondary Schools: Evidence from Bungoma County, Kenya

• Author(s): Yasiro Carren Mutua; Moses Kololi; Jacinta Mutwiwa
• Paper ID: 1719671
• Page: 1007-1015
• Published Date: 10-07-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 10 Issue 1 July-2026

Abstract

The rollout of Competency Based Education (CBE) in Kenya’s senior secondary schools has created a need for objective, data-driven tools to monitor school readiness for the Science, Technology, Engineering and Mathematics (STEM) pathway. School preparedness is multidimensional, yet most evaluation schemes treat its indicators as equally important, which overweights indicators that carry little discriminating information and underweights those that separate schools most sharply. This paper derives objective weights for twelve STEM–CBE preparedness indicators using Shannon entropy, as a preliminary step to entropy-weighted clustering. Data were collected from 112 public senior secondary schools across the nine sub-counties of Bungoma County through structured questionnaires and facility observation checklists under stratified random sampling. After min–max normalisation, the informational contribution of each indicator was quantified through its normalised Shannon entropy, converted to a degree of diversification, and normalised to a unit-sum weight vector. The derived weights ranged from 0.022 to 0.141—a spread of roughly six-fold—and summed to unity. ICT device provision (weight 0.141) and ICT-integrated lesson frequency (0.119) were the two sharpest markers of preparedness, and together with stakeholder engagement (0.112) and the presence of a STEM strategic plan and budget (0.104) the ICT and institutional-leadership indicators carried about 47.6 percent of the total informational value. Student competency in STEM tasks (0.022), practical lesson frequency (0.041) and STEM teacher density (0.052) were least informative, reflecting limited variation across schools rather than low substantive importance. The ranking identifies the digital divide and governance capacity as the conditions that most sharply differentiate senior-school readiness in the county and supplies a defensible, reproducible weight vector for downstream profiling.

Keywords

Entropy Weighting, Shannon Entropy, STEM–CBE Preparedness, Indicator Ranking

Citations

IRE Journals:
Yasiro Carren Mutua, Moses Kololi, Jacinta Mutwiwa "Entropy-Weight Derivation for Ranking STEM–CBE Preparedness Indicators in Public Senior Secondary Schools: Evidence from Bungoma County, Kenya" Iconic Research And Engineering Journals Volume 10 Issue 1 2026 Page 1007-1015

IEEE:
Yasiro Carren Mutua, Moses Kololi, Jacinta Mutwiwa "Entropy-Weight Derivation for Ranking STEM–CBE Preparedness Indicators in Public Senior Secondary Schools: Evidence from Bungoma County, Kenya" Iconic Research And Engineering Journals, vol. 10, no. 1, Jul. 2026

APA:
Yasiro Carren Mutua, Moses Kololi, Jacinta Mutwiwa (2026). Entropy-Weight Derivation for Ranking STEM–CBE Preparedness Indicators in Public Senior Secondary Schools: Evidence from Bungoma County, Kenya. Iconic Research And Engineering Journals, 10(1).

MLA:
Yasiro Carren Mutua, Moses Kololi, Jacinta Mutwiwa "Entropy-Weight Derivation for Ranking STEM–CBE Preparedness Indicators in Public Senior Secondary Schools: Evidence from Bungoma County, Kenya" Iconic Research And Engineering Journals, vol. 10, no. 1, Jul. 2026.

BibTeX

@article{1719671,
author = {Yasiro Carren Mutua, Moses Kololi, Jacinta Mutwiwa},
title = {Entropy-Weight Derivation for Ranking STEM–CBE Preparedness Indicators in Public Senior Secondary Schools: Evidence from Bungoma County, Kenya},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {1},
pages = {1007-1015},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1719671.pdf},
abstract = {The rollout of Competency Based Education (CBE) in Kenya’s senior secondary schools has created a need for objective, data-driven tools to monitor school readiness for the Science, Technology, Engineering and Mathematics (STEM) pathway. School preparedness is multidimensional, yet most evaluation schemes treat its indicators as equally important, which overweights indicators that carry little discriminating information and underweights those that separate schools most sharply. This paper derives objective weights for twelve STEM–CBE preparedness indicators using Shannon entropy, as a preliminary step to entropy-weighted clustering. Data were collected from 112 public senior secondary schools across the nine sub-counties of Bungoma County through structured questionnaires and facility observation checklists under stratified random sampling. After min–max normalisation, the informational contribution of each indicator was quantified through its normalised Shannon entropy, converted to a degree of diversification, and normalised to a unit-sum weight vector. The derived weights ranged from 0.022 to 0.141—a spread of roughly six-fold—and summed to unity. ICT device provision (weight 0.141) and ICT-integrated lesson frequency (0.119) were the two sharpest markers of preparedness, and together with stakeholder engagement (0.112) and the presence of a STEM strategic plan and budget (0.104) the ICT and institutional-leadership indicators carried about 47.6 percent of the total informational value. Student competency in STEM tasks (0.022), practical lesson frequency (0.041) and STEM teacher density (0.052) were least informative, reflecting limited variation across schools rather than low substantive importance. The ranking identifies the digital divide and governance capacity as the conditions that most sharply differentiate senior-school readiness in the county and supplies a defensible, reproducible weight vector for downstream profiling.},
keywords = {Entropy Weighting, Shannon Entropy, STEM–CBE Preparedness, Indicator Ranking},
month = {July}
}