Analysis in man-task system behavior studies
P. Loslever · Systems Research and Behavioral Science · 1993
Studies of man-task system behavior start with the obtaining of behavioral data. The recorded variables are generally numerous, can be objective and/or subjective and can be classified by their scale types. The next stage is to describe the behavior through a preprocessing technique in such a way that all variables have the same scale type. To achieve this goal, the qualitative scale is chosen but to lose as little information as possible from a quantitative to qualitative scale transformation, fuzzy categories are considered. The next stage is to analyze the resulting data set. A data set is considered through an observation X category table and studied using either the simple or multiple correspondence factor analysis. These methods yield both mathematical and descriptive behavior patterns. Their advantages are to not consider a priori too much constrained mathematical hypotheses and too much synthesized indicators (computed over the subject sample, for example). The general data analysis procedure (data characterizing/correspondence analysis) is described for four different data set types: judgments using quantitative scales, multidimensional signals, viewer behavior using eye movements, and operator behavior in tracking task.