This stndy is the first step in investigating what effects “moral” classes have on the character development of children and is aimed at the analysis of the teacher-pupil interaction during “moral” education.
For this purpose three records of instructions by different teachers each pursuing one and the same aim, were analysed according to the following methods.
1) Analytic rating of the instruction process
Several trained observers rated 17 items according to 5 grades. The items consisted of three groups.
(1) instructional materials dealt with
(2) techniques of teaching
(3) teacher-pupil relationships
2) Content analysis of the instruction process according to certain categories
The classificatory system was based on the categories for the analysis of counseling processes and was revised especially for the present analysis of “moral” lessons.
They involved (α) categories concerning the content of the problem,(β) categories concerning the function of teacher's utterances and (γ) categories concerning the pupil's utterances.
Utterances were regarded as one unit when they expressed one completed idea and were classified from their psychological functions as well as from their contents, such as whether they described pupil's own conduct or the conduct of others, or whether or not they were expressed emotionally.
3) The pupil's cognition of the class (by means of a questionaire)
Immediately after the class was over, the pupil were required to evaluate the class.
(ex. Was it interesting? Did you learn something new? etc. The questionaire consisted of 15 items which were evaluated into 7 grades)
Five months after the class, the pupils were again asked to write what he had learned in the class.
The results gained through these methods were consistent with each other and seemed to reflect the characteristics of each “moral” lesson.
But as for the details, not a few points are still left, to be improved.
This study, we believe, played a pioneering role in studying about the effects of “moral” classes.

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By means of Brownfain's 25 items of selfconcept, a group of seven university students (one male and six female) were assessed by making each of them rate against 5-point scales.
a) rate himself as he considers himself to be,
b) rate himself as he considers the rest of his group consider him to be, and
c) rate each one of the rest as he considers him to be.
For the rating c), average score of the group was calculated, and from these three different scores obtained above, four indices were deviced, namely,
1) Index of Social Alienation (I. S. A.) ; from discrepancy between the scores a) and b).
2) Index of Social Awareness (I. S. Aw.); from discrepancy between the scores b) and c).
3) Index of Social Adaptation (I. S. Ad.); from discrepancy between the scores a) and c).
4) Index of Mutual Understanding (I. M. U.) from discrepancy between a) and the individual score of c).
These indices obtained were then compared with the result of Y-G Test which was given to the same group as an external criterion, and the reliability of the deviced indices were confirmed. The results indicated that these indices differentiated fairly well both interactions of the members of the group and their respective personality characteristics.

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The purpose of this paper is to study the basic factors behind educational attitudes by the Q-technique. As an instrument, Fred N. Kerlinger's Q-sort statements were used, somewhat revised to adapt for Japanese teachers. The original 80 item Q-sort had been constructed according to the following paradigm:
(A) Attitudes
(1) Restrictive-Traditional
(2) Permissive-Progressive
(B) Areas
(a) Teaching-Subject matter-Curriculum
(b) Interpersonal Relations
(k) Normative-Social
(m) Authority-Discipline
Thirty-one subjects, consisting of six university professors in Education, six university professors in Psychology, eight elementary school teachers, five junior high school teachers, five senior high school teachers and one layman, were asked to sort 80-statements on an approval-disapproval dimension.
Each subject's sort was analyzed with a factorial analysis of variance. As was expected, all the professors' educational attitudes were “permissive” at 1% level, and the other subjects were multifarious in their educational attitudes. About half of the latter had high F-ratios in the permissive direction and the rest had low F-ratios in the permissive or restrictive direction.
Twenty-two subjects' sorts were intercorrelated and the resulting correlation matrix was factor-analyzed. Orthogonally rotated factors, I, II and III were named “Progressivism”,“Traditionalism” and “Psychology” respectively. A Spearman rank order coefficient of correlation was computed between the attitudes F-ratios and the factors. The rhos were.86, -.24 and.44 for I, II and III respectively.
In addition, three factor arrays were computed to examine the nature of the factors. The results were commensurate with the foregoing interpretation of the factors. Although both I and III were progressive in nature, the subjects who had high loading of I were progressive, especially in “Normative-Social” and “Authority-Discipline” areas of education, and those who had significant positive loading of III were all psychologists and were inclined to be progressive in “Interpersonal Relations” and “Teaching -Subject matter-Curriculum”.

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Suppose that the pupils understood the subject matters (α₁=(α₁, α₂,..., α_k)) and didn't underst and (α₀=(α_k+1, α_k+2,..., α_m)), when the new subject matters (α=(α₁, α₂,..., α_m)) had been given by an educational action (A) to the pupils who had ha d fundamental abilities (S₁, S₂,..., S_n)(where S_i=1 or 0, 1 is understanding S_i, 0 is not understanding).
Then subject matters (α₁=(α₁, α₂,..., α_k)), which the pupils understood, are called region of readiness to learn of fundamental abilities (S₁, S₂,...S_n) and it is represented by R_s(α).
From the above point, R_s(α) is represented as follows, _??_ (1) where α_i=1 is understanding α_i, α_j=0 is not understanding α_j.
In this report, readiness region is analyzed from the following points.
(1) To consider the characters of readiness region.
(2) To abstruct the elements of readiness region.
(3) To consider the characters of boundary elements
The results obtained (1)-(3) are as follows.
(1) Let fα_i (S₁, S₂,..., S_n) be degree of achievement, obtained by the pupils who had fundamental abilities (S₁, S₂,..., S_n), on subject matter (α_i). Then, readiness region R_S(α), which is represented by formula (1), is defined by as following formulas (2),(3).
_??_ (2)
where i=1, 2,..., k
??_ (3)
where i=k+1, k+2..., m Let φ(S₁, S₂,..., S_n)(α₁=1, α₂=1,..., α_k=1, α_k+1=0, α_m=0) be ratio of the pupils, who have understood subject matters (α₁, α₂,..., α_k) and had fundamental abilities (S₁, S₂,..., S_n), to the all pupils who had fundamental abilities (S₁, S₂,..., S_n).
Then, from formulas (2),(3),
_??_ (4)
and in any other combination of (α₁, α₂,..., α_m)(where α_i=1 or 0, i=1, 2,..., m).
_??_ (5)
(2) According to the above consideration, readiness region will be abstructed by formula (6) in real material.
_??_ (6)when (α₁*, α₂*,..., α_m*) satisfied formula (6), R_S(α)=(α₁*, α₂*,..., α_w*)
(3) Let R_S(α) be readiness region and let R_S(α) be outside of readiness region, then the boundary elements(α_l) have following characters.
_??_
_??_where _??_ represents intersection of A and B.
and so
1>fα_l(S₁, S₂,..., S_n)>0
1>ψ(S₁,S₂,..., S_n)(α₁=1, α₂=1,..., α_l-1=1, α_l=1,
α_l+1=0,..., α_m=0)>0
1>ψ(S₁, S₂,..., S_n)(α₁=1, α₂=1,..., α_l-1=1, α_l=0, α_l+1=0,..., α_m=0).

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This investigation was undertaken in order to make a comparison of proficiencies in the national language, scores on the verbal and non-verbal intelligence tests given to city and farm-village children, and to obtain further informations about the relationship of the proficiency in the national language with the score of farm-village children in a verbal intelligence test.
The subjects were 100 first graders of two junior high schools in farm-villages, and 115 first graders of two junior high schools in a city. Both groups were given the following tests: group verbal and non-verbal test of intelligence, and a standardized language proficiency test. The results of those three tests are as Table 1.
No significant difference were found between the two groups in the variability of scores on the three tests respectively (Table 2), so I made a comparison of mean scores of each test between two groups. A highly significant difference was found in favor of the city group in the verbal intelligence and language proficiency test, but no difference was found in the non-verbal intellgence test. The mean difference amounted to 5.68 in verbal intelligence T-score, 4, 60 in language proficiency T-score (Table 3, 4, 5).
The differences of mean scores in verbal and non-verbal intelligence tests of both groups are significant in 0.1 percent level (Table 6). So, these differences are examined in relation to language proficiency. When I caluculated the mean difference in verbal and non-verbal T-scores in relation to higher, middle and lower gradation of the proficiency in the national language, I found the obvious tendency for the group with the higher language proficiency toshow a higher score on the verbal intelligence test than on the non-verbal intelligence test, and the group with lower language proficiency shows the reverse tendency (Table 10, 11).
An analysis of covariance was carried out in order to discover whether the differences observed in favor of the city group in the verbal intelligence test remained significant, when the two groups were equated for the proficiency in the national language (Table 13).
As the result of adjusting the verbal intelligence T-score on the common language proficiency basis, the difference 5.68 points reduced to 1.64 points, but remained significant (Table 14).
The regression of verbal intelligence T-scores on language proficiency scores and the correlation between above two scores proved to be similiar in both city and farm-village group (Table 15, 16).
The enquiry suggests that a group verbal intelligence test may not give an accurate T-score assessment for farm-village children, unless their inferiority in language profictency is taken into account.

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In this Journal (Vol.8, No.2, Vol.9, No.1) we have discussed the etiology and classification of mental deficiency, and found that several etiological classifications have been advocated.
The one most frequently used is that of A. A. Strauss, who divides mental deficiency into the exogenous or brain injured group and the endogenous or familiar group.
This classification has, however, imperfections regarding classification-validity and other procedural defects.
For the purpose of educational diagnosis of mental deficiency, we have tried to set up the typological approach from the standpoint of behavior patterns and of personality traits.
With relation to our approach, several problems about the procedural methodology were considered.

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