**1. Introduction**

About two decades ago, digital instrument has begun to prevail in society, and the arrival of peoples' cognitive revolution has been forecasted [1]. Teachers also have begun to concern with the behavior of learners, so-called digital kids or students, because the latest technologies and information have been introduced one after another at the present field of education. On the other hand, however, it is questionable whether those technologies and information are understood conveniently.

Practically, it seems difficult for teachers to find out teaching strategies with using appropriate digital devices. It is not clear what has changed since the digital transformation of society and what are the causes of the change and their effects, because the individual differences of cognitive mechanism have not been clarified yet.

Accordingly, we have developed the measurements of individual traits concerning with human information processing as a fundamental research so that teachers might be able to understand those students more and instruct them appropriately depending on the criteria for individual traits.

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*Strategy and Behaviors in the Digital Economy*

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The experiments of this system have been conducted under conditions of presentations either sound voice or written letters. We have collected and analyzed various data, for instance, their replies and response time (decision-making time), after their listening or silent reading.

In the practical experiments of collaborative learning which have formed depending on students' individual traits, they have continuously had interactive communication among team members, even using text message through learning management system (LMS). Consequently, high-stake assessments of students have become significantly higher than those of previous students formed by traditional methods [2]. On the other hand, we have found that there were differences among teams when we have compared their results.

We have checked students' data concerning learning, for instance, their reports, text message among team members for subjects so that we can analyze those data with reaction time (decision-making time), and the so-called Big Data processing and analysis [3]. The purpose of this Big Data analysis is to clarify the cognitive mechanism during learning processes along with the hypothesis from the model of human information processing.

With results of Big Data analysis, we have found that there are two types of traits (visual type and auditory type) and they have proved the relation between those traits of information processing and learning effects in collaborative learning. For instance, members of an unsuccessful team have formed by the similar traits of information processing (three of four members), in contrast, those of a successful team has consisted of different traits.

Therefore, it is supposed that individual traits such as personality and cognitive style in terms of information processing might help teachers to make collective decisions, for example, instruction and forming team members. Consequently, we would like to propose the results of the measurements and analysis as criteria for teaching strategies so that teachers can make their decision for forming interactive team members from the prediction of students' behavior.
