Carswell C M
University of Kentucky, Lexington.
Hum Factors. 1992 Oct;34(5):535-54. doi: 10.1177/001872089203400503.
Effect sizes obtained from 39 experiments were used to evaluate the predictions of the basic tasks model of graphical efficacy. This model predicts that performance will be attenuated with graphical displays as a function of the particular specifier, or visual dimension, used to code data values. In this review the basic tasks model predicted performance more accurately than did Tufte's data-ink principle. In addition, variability in effect sizes across studies revealed that the model was more successful at predicting performance in local (focusing) tasks than in global information synthesis tasks. Furthermore, the model was better at predicting performance in tasks requiring the use of physically present rather than remembered graphs. Further differences in effect sizes resulted from variability in the exact specifiers used in experimental graphs. Minimal differences were obtained among graphs that used position, length, or angle as specifiers. However, graphs that used area or volume to represent quantitative values were associated with consistently worse performance than found with other formats.
从39个实验中获得的效应量用于评估图形功效基本任务模型的预测。该模型预测，作为用于编码数据值的特定说明符或视觉维度的函数，图形显示会使性能衰减。在本综述中，基本任务模型比塔夫特的数据-墨水原则更准确地预测了性能。此外，各研究中效应量的变异性表明，该模型在预测局部（聚焦）任务的性能方面比在全局信息综合任务中更成功。此外，该模型在预测需要使用实际存在的图形而非记忆图形的任务的性能方面表现更好。实验图形中使用的精确说明符的变异性导致了效应量的进一步差异。使用位置、长度或角度作为说明符的图形之间差异极小。然而，使用面积或体积来表示定量值的图形与其他格式相比，始终表现出更差的性能。
