Abstract
A Likert scale is a psychometric response scale primarily used in questionnaires to obtain participants’ preferences or degree of agreement with a statement or set of statements. Respondents are asked to indicate their level of agreement with a given statement using an ordinal scale. Nowadays, Companies often use Likert surveys to discern the capabilities and skills of current or potential employees, asking multiple questions about each competency. With such a questionnaire, different competencies are evaluated and therefore, the result of a questionnaire will provide important information about capabilities and skills of the respondents. As an example, we will describe, for a real questionnaire, how to classify each question with the corresponding competency. That is, to find, for each Likert item, which competency is evaluated. We will present how to face and solve the problem using two different techniques: an approximate method, using a genetic algorithm and an exact algebraic method, solving a quadratic system of n equations and n unknowns. Finally, we will set the basics to solve this competency-assignment problem for a generalized version of similar questionnaires with n Likert items for evaluating m competencies. The advantages and disadvantages of both techniques will be also shown.
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Galán-García, J.L., Merino, S., Martínez, J. et al. Genetic and Algebraic Algorithms for Classifying the Items of a Likert Questionnaire. Math.Comput.Sci. 11, 49–59 (2017). https://doi.org/10.1007/s11786-017-0289-1
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DOI: https://doi.org/10.1007/s11786-017-0289-1