Methodological pathway for instrument validation in engineering research - Abanto Duran, Roger Francisco (2026)
The process of validating measurement instruments is fundamental to research, especially in engineering, to ensure that the data obtained is reliable. This process consists of two main phases: a qualitative and a quantitative one. The qualitative phase is based on the judgment of experts, who evaluate the instrument's relevance. To quantify this consensus and reduce subjectivity, Aiken's V coefficient is used. Subsequently, the quantitative phase focuses on measuring the instrument's internal reliability using Cronbach's Alpha, with an acceptable value between 0.7 and 0.9. After validation, the normality of the data is evaluated using tests such as Shapiro-Wilk for small samples (less than 50) or Kolmogorov-Smirnov for large samples (50 or more). This evaluation is crucial for selecting the appropriate statistical tests: if the data follows a normal distribution, parametric tests like the t-Student are applied; otherwise, non-parametric tests like the Mann-Whitney U are chosen.