A factor analytic method for investigating differences between groups of individual learning curves

In this method of analyzing learning data, entire learning curves are described quantitatively by single numbers which are used in a statistical test to determine whether two or more groups of learning curves are significantly different. The method has some logical advantages over prevailing methods in that it avoids the use of average learning curves and of arbitrary measures of slope and asymptote. Its disadvantage is computational. Since it involves the use of factor analytic procedures, it may be tedious to apply unless computation is carried out on a high-speed computer.This investigation was begun and carried out for the most part while the author was a Psychometric Fellow of Educational Testing Service at Princeton University. It was completed at University College, London, during successive tenures of post-doctoral fellowships from The National Institute of Mental Health, U.S.P.H.S., and The National Science Foundation. Data for the numerical example were processed by the high-speed computer facilities of the Western Data Processing Center, Los Angeles.