This is the first part of our three studies. Three kinds of multivariate approaches are methodologically possible to evaluate the pure temperamental factors free from social desirability factors in personality questionnaires. The first approach would be to obtain the factor-estimate scores by the multiple regression method (called the complete estimation method by Harman 1967) using the factor structure matrix of the predictive variables on the wanted pure temperamental factors which had been obtained for our special purpose by the partial correlation analysis of higher order. This is a special kind of “group principal factor analysis” combined with an ordinary oblique factor analysis of the residual correlation matrix out of which the social desirability factors had been partialed. The initial correlation matrix consists of the intercorrelations among the original personality questionnaire scores (12 YG scales in standard situation) plus the same number of scale scores in a valuation situation which are scored from the items of the same scales with the same keys.
The second one is to construct the pure temperamental factor scales by items selection according to the principle of factor-trueness proposed by Cattell and Tsujioka, where the items will be selected_by suppressing the social desirability factors and at the same time by aiming the true directions of the pure temperamental factors in the total factor space.
The third one is to directly orthogonalize the original number of personality questionnaire scales to those social desirability factors.
The present study is the first one of these approaches. In the authors' previous studies (1975a, 1975b) three social desirability factors: Social Desirability Factor for Emotionality (SD-E), Social Desirability Factor for Introversion-Extraversion (SD-I)and Personal Desirability Factor on Reflectiveness (PD-R); seven temperamental factors: Emotional Instability (¹E), Dominance (¹D), Impulsiveness (¹I), Unreflectiveness (¹R), Frustrativeness (CO), Aggressiveness (AG) and Fantasticalness (DO), named towards high score in YG scales, were established as orthogonal factors between two domains while as oblique factors within each domain (either temperamental factor space or social desirability factor space).
Ten pairs of the factor-estimates of 3 social desirability and 7 temperamental factors were calculated from 300 college (200 male and 100 female) students by Formula No.3 using 12 YG scores only or those plus 12 valuation judgement scores. The correlation matrix (partly shown in TABLE 1) among 10 pairs of factor-estimates was analysed by the principal component analysis and then 10 principal components were rotated to Varimax solution as shown in TABLE 2.
The results in Tables 1 and 2 reveal that each pair of the factor-estimates of the 7 temperamental factors behaves as if the pair is almost the same measures in the total factor space. However each pair of 3 social desirability factors behaves differently from one to another. In order to recover the reduction of the factor saturation of each social desirability factor, the writers decided to construct three scales for measuring three social desirability factors which can be selected from the items in the valuation judgements by the principle of factor-trueness by suppressing the temperamental factors in this case.
Finally a new experiment by the same method for checking the effectiveness of excluding the social desirability factors was suggested to be applied to the data which will be obtained in a more fakable situation.

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There are at least two processes in leaning to name letters: learning to differentiate graphic features of letters (perceptual discrimination learning) and learning to code letters to their sounds (associative learning). In the present study two experiments were reported which focused on the process of perceptual discrimination learning. Experiment I explored the relationships among the following three factors: the discrimination ability of letter-like figures, that of Japanese katakana letters, and the rate of naming katakana letters. Experiment II was designed to examine effects of discrimination training of figures and letters upon learning to name katakana letters.
Experiment I The Ss were 92 nursery school children with a mean age of 4 years, 9 months. They could not name any of the letters used in the experiment. The figure and letter discrimination tasks were provided, each of which consisted of four sets of four figures or four letters (FIG. 1). In each set one of the four stimuli was put on the upper center of a white card and the four stimuli were put on the bottom half in a row (FIG. 2). The S was given these 32 cards one by one in a mixed series of the figure and letter sets, and was required to point to one which was just the same as the upper one, out of the bottom four stimuli. No information was given about the S's responses. The letter-naming task consisted of four two-letter words, each of which was written on a white card. In the study trial the S was given these words one by one with the E naming the letters and was required to repeat after the E. In the test trial the S was given the letters without the E naming them and was required to name them. Two study trials and a test trial were given seven times alternatively. The correlation coefficients were statistically significant for all comparisons (TABLE 2). This suggests that S's ability to discriminate figures and letters was positively related to the rate of naming letters. The stimuli of Set 1 were more discriminable than those of Set 4 for the figure and letter sets (TABLE 3).
Experiment II The Ss were 60 nursery school children with a mean age of 5 years, 3 months. They could not name any of the katakana letters used in the experiment. Letter Set I, Letter Set 4, and Figure Set 4 were used as the discrimination tasks. The S was trained on one of these three sets with the E's information of “Hit” and “Miss.” After reaching a criterion of eight successive correct choices, the S was given a letter-naming task which consisted of the four katakana letters employed in Letter Set 4. The procedure for learning to name letters was nearly the same as that in Experiment I. Letter Set 1 was learned faster than the remaining two sets and the latter did not differ significantly (left half of TABLE 4). This indicates that discriminabiliy was positively related to the rate of discrimination among stimuli learning. The facilitative effect of discrimintion upon naming letters was more conspicuous when the S had been trained on the less discriminable sets than when the S had been trained on the more discriminable set (right half of TABLE 4). The fact that there was no differential effect of Figure Set 4 and Letter Set 4 upon naming letters can be explained by assuming that Ss acquired some general set to attend to and discriminate stimuli through the discrimination training of less discriminable figures.

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