Purpose: To study the associative difference (or similarity) of some concrete concepts when presented through verbal mode (printed words) and pictorial mode (line drawings) of stimuli. Free association method was taken. According to the previous studies and Tada's hypotheses, the following hypotheses were formulated; 1. Sense impression responses (SIR) will be much evoked by words (W) than by pictures (P). 2. Nouns : W>P. 3. Adjectives : W>P. 4. Verbs : P>W. 5. P will take longer reaction time (RT) than W. Method: 1) Materials : A list of Japanese common nouns were pretested, and 40 nouns were selected to be used in the experiments. 2) Subjects : Exp. I; A total of 611 college students (freshmen and sophomors) were used, 271 for W-group, 340 for P-group. Exp. II; A total of 50 freshmen, 20 for W-group, and 30 for P-group. 3) Procedure : Experiments were conducted by groups using intact classes. In Exp. I stimuli were projected on a screen by an Overhead Projector, for 8 sec. with 2 sec. intervals. In P-group, instruction was given to respond with words "other than the names of pictures". Exp. II was run in a "Language Laboratory Room". Stimuli were presented through TV and responses were recorded. Other procedures are the same as Exp. I. Results and Discussion: 1) Rate of SIR was W(8.04%)>P(5.73%). Hypothesis 1 was supported, which was explained mainly from the difference between words and pictures in their denotative fields. 2) Rate of nouns was P(78.01%)>W(70.01%), which was contradictory to Hypothesis 2, and mainly explained from Paivio's dual coding hypothesis in its possible relationship to the effect of instruction to P-group. 3) Rate of adjectives was W(9.02%)>P(7.51%), which supported Hypothesis 3, Partly, the same explanation as 1) was presented, but there remained a problem of connotative affective responses. 4) Rate of verbs was W (16.91%) > P (11.17%) ; contradictory to Hypothesis 4. This was explained from the difference between W and P in their denotative fields of actions of referents. 5) Mean RT was longer with P (3,83 sec.) than with W (3.57 sec.), which supported Hypothesis 5 ; interpreted according to Paivio's dual coding hypothesis. 6) K-value was defined as the number of different kinds of responses. When K/N were compared, a little lower value was shown with P-group (though not significant), which was considered to suggest the narrowness of their denotative fields. 7) In all the indices above, rank corelations between W and P stimuli were significant, which suggested that associations of concepts were similar over W and P mode. 8) For a few pairs of stimuli, opposite tendencies were shown to the results as a whole, which suggested the possible exceptions of the explanations presented above.

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(I) Problem The educational equipments enlarge and substitute some of the functions carried out by the instructors. By using the educational equipments correctly, we can make the education more effective to provide the suitable instructions according to the different needs of each student. And also this introduction of the educational equipments, in another word the technological innovation in education, will bring about the innovation in the traditional instructional process. The aims of this report are as follows: (1) To find the indices which indicate the degree of national technological innovation in education. (2) To find the determinants of the technological innovation in education. (II) Method To find the indices of the educational technological innovation (which indicate the degree of overall technological innovation in education) the following numerical values are used : The diffusion rates of Overhead Projector, VTR, TV, Magnetic Sheet Recorder in elementary schools : Overhead Projector, VTR, TV, Magnetic Sheet Recorder, Language Lab. in junior high and Overhead Projector, VTR, Language Lab. in senior high schools. These five equipments are the most diffused ones in Japan. From tweleve variables, using principal component analysis, we seek the first multiple component. And this shows the state of deffusion of all the equipments. We regress this index of technological innovation in education into 5 variables : the budget for the equipment provided for the teacher per class, the proportion of the women teachers, the number of teachers per pupil, the percentage of the college applicants, and a special class for mentally retarded children. (III) Results & Discussion The first multiple component as the result of the principal component analysis, the α coefficient is 0.87, contribution rate is 40.3% which enables us to consider it as the variable indicating the overall degree of technological innovation. We name this, the "index of technological innovation in education". The prefecture which has the high score of this index is Toyama, Aichi, Osaka, and Tokyo. As the result of the multiple analysis, multiple correlation is 0.74 and the following were high in β coefficient : applicant rate for college, the proportion of women teachers, and the number of teachers per pupil. This result suggests the following : (1) Either the great demand for education or cosmopoliteness has the close relationships with the technological development. (2) The proportion of women teachers in education, which represents the cosmopoliteness has the close relationships with the technological innovation. (3) The bigger the class size the more extended the technological innovation. (IV) Conclusion The important aspects for the development of technological innovation in education seems not money but the favorable inclination for innovation and also the great demand for technological innovation.

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