Applying the Pythagorean Model to Derive a Correction Factor for Estimating Minimal Competence with Greater Fidelity

Abstract

We propose an alternate psychometric method for judging minimal competence using core knowledge as a major variable. Utilizing the ‘Pythagorean’ model, we offer to establish a mathematically valid relationship between a borderline candidate’s scores in test items reflecting core knowledge, desirable or higher knowledge, and the total raw score obtained in a given test. Using this method, it is possible to establish a mathematical relationship between the above variables and derive a positive integer, named herein as the Correction Factor (CF) that would help in providing a better means to identify minimal competence with greater fidelity.

Keywords: Cut-point; Domain-referenced; Minimal competence; Core knowledge, Correction Factor.