MCDM Framework Dataset

This dataset supports advanced analysis of an innovative Multi-Criteria Decision Making (MCDM) framework designed to optimize the teaching and delivery of Physical Education (PE) curricula. The data is organized into three interconnected CSV files capturing stakeholder preferences, instructional method performance, and expert pairwise comparisons based on the Analytic Hierarchy Process (AHP).<b>Contents:</b><b>criteria_subcriteria_weights.csv</b>Detailed weights assigned to 25 sub-criteria grouped under five core evaluation dimensions (Pedagogical Quality, Student Engagement, Resource Availability, Inclusivity &amp; Accessibility, Curriculum Flexibility).Weights represent the relative importance given by five different stakeholder groups: PE Teachers, Curriculum Experts, School Administrators, Students, and Policy Advisors.<b>instructional_methods_detailed_scores.csv</b>Normalized performance scores (0 to 1) of four instructional approaches—Lecture-Based, Game-Based, Blended, and Project-Based Learning—across all sub-criteria.Reflects hypothetical but realistic effectiveness, engagement, resource needs, inclusivity, and flexibility ratings for each method.<b>pairwise_comparisons.csv</b>Simulated pairwise comparison matrices from 10 respondents for the five core criteria, using Saaty’s scale (1/9 to 9), suitable as AHP input data.Enables calculation of criteria weights and consistency validation.<b>Purpose and Use:</b><br>The dataset is intended for researchers, educators, and decision scientists interested in multi-criteria evaluation, curriculum optimization, and educational policy modeling. It enables replication of the MCDM framework, sensitivity analyses, ranking of instructional strategies, and development of decision-support tools tailored to PE curriculum delivery.