Re-Analysis of Morse Code Learning Data Using Structural Equation Models

Abstract

The correlation matrix of 14 tests and the time to reach four levels of Morse code proficiency reported in Fleishman, Roberts and Friedman (1958) and Fleishman and Fruchter (1960) was analyzed using structural equation methodology. This methodology was not available at the time of the original research and is especially suited for the data in these studies. The method is based on the standard maximum-likelihood approach for parameter estimation and goodness of fit. Five factors were extracted from the correlation matrix of 14 tests. These factors were significantly correlated and differed only slightly from the factors obtained in the original factor analysis. The factors were auditory perceptual speed, auditory rhythm perception, speed of closure, visualization and verbal ability. The time to reach a level of proficiency on Morse code was significantly predicted by the time to reach the previous two proficiency levels. The Auditory Perceptual Speed factor was a significant predictor of Morse code learning to each of the four proficiency levels. A speed of closure factor significantly predicted learning to the second proficiency level. The visualization factor was a significant negative predictor of learning to the 2nd and 3rd proficiency levels. This result suggests that individuals who are high in visualization ability may adopt a visual strategy (such as visualizing dots and dashes) that is detrimental to performance at the middle learning levels. In contrast to the earlier findings, the auditory rhythm factor was unrelated to reaching any of the proficiency levels. Overall, the results demonstrate the usefulness of correlation structure models in the area of selection and training.