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Inspecting children’s structural drawing is developmentally and psychologically important. Today’s digital availability of such data from electronic tablets, inspires automatic analysis; however, converting such data to an informative feature vector for further analysis and identification of related indicators, needs appropriate algorithms. This study presents simple, fast methods for detecting X, O and 4 basic lines’ drawing strategies. The functionality of the algorithms is tested on an available database subtending the performances of 74 (6–7years) pupils. Results demonstrate typical behaviors such as counterclockwise popularity in circle drawing, and other tendencies in the population’s structural pattern drawing’s performance. Algorithms clearly reveal all different strategies used by participators. Consequently the suitability of the algorithms, in effectively detecting strategic features, is clarified. In addition, according to the data labels in database, some features are suggested to serve as attributes distinguishing handwriting ability.

Sequential strategies of digitized tablet drawings by 6-7-yr.-old children (N = 203) of average and below-average handwriting ability were analyzed. A Beery Visual Motor Integration (BVMI) and a Bender-Gestalt (BG) pattern, each composed of two tangential shapes, were predefined into area sectors for automatic analysis and adaptive mapping of the drawings. Girls more often began on the left side and used more strokes than boys. The below-average handwriting group showed more directional diversity and idiosyncratic strategies.