4. Discussion

non-emotional contexts. This tendency is found in the patterns of the scatter diagram, which shows distributions of each response time how they diff between emotional and non-emotional contexts. On the other hand, in the case of Eidetic

Figure 10 shows the quantitative interaction between two types of students, comparing their scores between the first and the second semesters (F = 5.3, p< 0.01). The average of Eidetic type in the first semester was better than that of

This phenomenon should be examined in detail, checking whether the statistical results are right or not by seeing individual performances practically. Therefore, we have chosen team members whose team was success or ill-success in low- and highstakes' assessments. In the case of low-stakes assessments, Team B members' records were shown the best improvement among teams, comparing pre-post test scores. On the other hand, in the case of Team C, their records were the worst in class. Those tests conducted in the first semester, and the average of Team C (=77.5) was lower than Team B (=87.3). In the second semester, traits of the whole tendency of teams were the same; however, looking into individual performances, their tendencies were also the same as Figure 10. For instance, both scores of eidetic type; SubB-2 and SubC-2 in the second semester were lower than in the first semester, on the other hand, in the case of Adjusting type, SubB-1 and SubC-3, their scores in the second semester, became much better than those of the first semester.

In order to check them from another viewpoint practically, their descriptions of answering questionnaires were compared among types of information processing

type (N = 11), there are no differences between them.

3.2.1.3 Comparison of team performance

Comparison of scores first and second semester.

Assistive and Rehabilitation Engineering

3.2.2 Qualitative analyses

3.2.2.1 Description

Figure 10.

(Appendix 1 and 2).

62

Adjusting type; however, in the second semester, it was reversed.

#### 4.1 Meaning of clarifying human information processing

There are a significant number of studies, which have been conducted about human information processing in the world [17, 18]. Every study is very important for us; on the other hand, most of them are still vague and unclear, because we need to observe real time while it is working, from outside. It should be difficult, however, to see inside of our mind directly. Therefore, we have developed the measurement of individual traits from cognitive aspects so that we can clarify human information processing and predict their behaviors. I would like to make it a meaningful measurement; however, it is still exploratory research and data analysis.

Although there might be a lot of methods to find out the mechanism of human information processing [21, 22], there should be different approaches from each other to achieve a goal, depending on their own purposes. The end of this study is to improve personalized education, however, both the environments in society and educational field have been changing, which must be a lot of elements and always impact on our cognitive system, in other words, on the way of human information processing. This means that we always need to find out the problems which might be courses of ill-success in education.

For instance, in our study case, we have supported collaborative learning in nursing class, which has been introduced for cutting age electronic equipment. It must help students when they start to work at hospital, coping with electronic equipment. On the other hand, they are required to obtain the skill of interactive communication with patients and coworkers. For this reason, the instructors have introduced the method of collaborative learning, which needs to divide students into teams with four members in each. It seems cumbersome to decide the members of teams, if instructors seek for effective learning, because they would be required to predict students' behaviors by analyzing their data, for instance, individual traits and their needs. Hence, we have begun to support optimizing combination; however, there is no exact solution for it [23]. For those reasons, we have developed the support system or personalized education and learning. This has the measuring system to provide students' data to instructors before starting classes.

the context of sentences, we might process them with different ways, PFC or NFC Loop. One hundred twenty psychological questionnaires were used as a task for one session, but they consisted of mainly two types of contexts, emotion and non-emotion. From the previous studies, when the emotional context is processed, it is considered that we tend to use STM because the effect of emotion on hippocampal-dependent memory consolidation [25, 26]. Then, the categorization of types concerning contexts is performed, Eidetic [27] and Adjusting type, depending on the differentiation of correlation coefficients between emotional or non-emotional contexts (Table 2). In the case of adjusting type, the differentiation of response time was clear, and the average of response time to

Dual Loop Theory: Eidetic Feedback Control and Predictive Feedback Control

emotional contexts is significantly faster than non-emotional ones. This means

4.3 Relevance between individual differences and personality

is considered negative feedback control (NFC).

which have shown matching with each other.

are subjective and a little bit uncooperative.

5. Conclusions

65

matching members of team by optimizing combinations.

examine more details for this hypothesis.

DOI: http://dx.doi.org/10.5772/intechopen.89681

that students of Adjusting type might change their strategies to read silently and make decision depending on contexts. In the case of emotional contexts, they might use STM or PFC; on the other hand, in non-emotional contexts, their correlation coefficient is higher and much longer time spent from starting silent reading to making decision [28, 29]. This means that they might read silently with phonologization of words, referring concepts of words meaning by sound voice with image schema. This information processing might help them to reflect on their comprehension is right or not, which

From these results, we have proved hypothesis (c); however, we would like to

Two teams were selected from the aspect of low stakes assessments (highest and lowest teams, assessing for ability of conceptual metaphor and collaboration), in order to examine more in detail from the aspect of individual differences (Table 7). It is easy to compare the improvement performances among students' traits and records or between teams by parallel processing and analyses. The result of the comparison of the average scores between Eidetic and Adjusting types and between first and second semesters has been examined this parallel processing and analyses,

Moreover, the comparison of those examinations between results of scores and descriptions of students (Appendix 1 and 2) by parallel processing has shown their matching. From this viewpoint, whether those results are matching with the evaluation of personality, regarding the factors of lack of objectivity (O Factor) and lack

of cooperativeness (Co Factor) among 12 factors (Appendix 3). Students of Adjusting type (SubB-1, SabB-4, and SubC-3) have taken low scores for both factors; in other words, they are evaluated as objectivity and cooperativeness are strong. On the other hand, students of eidetic type (SubB-3 and SubC2) have taken high score in both factors, comparing with the former students, which means they

Consequently, we might be also able to predict their behavior from traits of information processing. Though the results of our experiments have been proven useful, they are complicated for us. In addition to it, instructors must be busy to prepare other instructions for students. From these reasons, AI machine or doctor which might be able to obtain machine learning is expected and prospected for

In this chapter, dual loop theory, which consisted of two kinds of feedback control, concerning with human information processing, was proposed (Figure 6)

As I have mentioned above, however, it has been becoming complicated to combine members of teams. Therefore, if AI doctor or machine would solve this problem by optimizing combination, personalized education and learning would be improved. To achieve this meaningful goal, we need to clarify information processing for interactive communication. This must have synergic effect on AI doctor, care assisting robots and so on, because they need to obtain the ability of interactive communication with people by machine learning.

From these viewpoints, this study and the measuring system for clarifying human information processing must be meaningful to achieve our goal.

#### 4.2 Examination of dual loop theory

We have planned to examine dual loop theory, which I have proposed as hypotheses and implemented experiments, gathered data, and analyzed them. Those ideas were hinted by Card's Model Processor [18], which is a "cognitive model of the user to be employed by the designer in thinking about the human interaction with computer at the interface" and "the Recognize-Act Cycle of the Cognitive Processor," from the view of LTM and STM as a simple reaction time. Although they have introduced this model, they have tried to propose another one (GOES: Goals, Operations, Methods, and Selections) for tasks which can be taken from the half-second level to the two-second level. Approximately, dual loop theory model (Figure 6) might be a combination of those two models and we can predict subjects' behavior. Many of such models have been introduced; however, there might be a few to find out individual differences in human information processing.

The idea of this dual loop theory might be similar to the others, however, we seek for finding out individual differences which patters would indicate some types of trait concerning with cognitive behavior.

Although having said that, when the model is examined, we need to use previous studies as references. For instance, by comparing processing between sound voice and letters [24] and cycle reaction time which is proposed by Card [18], we have examined calibration of measuring instrument. From the results of analysis for response time by presenting sound voice have been shown the high level of the calibration from the viewpoints of reliability and the reproducibility (Figure 7, left), considering the high correlation coefficient with the number of words which means cycle of response time. On the other hand, in the letter presentation case, it was recognized reproducibility; however, its correlation coefficient with the number of words was not shown high.

From this result, it was predicted that individual differences clearly among students concerning the way of silent reading. Then, categorized types of trait (visual or auditory type) by strengthening of the correlation coefficient between response time and the number of words or duration of reading aloud. There are no differences between the two types of reaction time represented questionnaires by sound voice, but recognized significantly differences by letters (Figure 8 under Table 5). Students of Auditory type have needed time longer than those of Visual type from starting to silent reading to making decision (Figure 5). This means that the auditory type might tend to process a word and a sentence with phonologization, using LTM or NFC loop; conversely, the visual type tends to process directly encoding symbol using STM or PFC loop.

From these results of analyses, the hypotheses [a] and [b] have been proved, and next hypothesis [c] should be examined. It was predicted that depending on Dual Loop Theory: Eidetic Feedback Control and Predictive Feedback Control DOI: http://dx.doi.org/10.5772/intechopen.89681

the context of sentences, we might process them with different ways, PFC or NFC Loop. One hundred twenty psychological questionnaires were used as a task for one session, but they consisted of mainly two types of contexts, emotion and non-emotion. From the previous studies, when the emotional context is processed, it is considered that we tend to use STM because the effect of emotion on hippocampal-dependent memory consolidation [25, 26]. Then, the categorization of types concerning contexts is performed, Eidetic [27] and Adjusting type, depending on the differentiation of correlation coefficients between emotional or non-emotional contexts (Table 2). In the case of adjusting type, the differentiation of response time was clear, and the average of response time to emotional contexts is significantly faster than non-emotional ones. This means that students of Adjusting type might change their strategies to read silently and make decision depending on contexts. In the case of emotional contexts, they might use STM or PFC; on the other hand, in non-emotional contexts, their correlation coefficient is higher and much longer time spent from starting silent reading to making decision [28, 29]. This means that they might read silently with phonologization of words, referring concepts of words meaning by sound voice with image schema. This information processing might help them to reflect on their comprehension is right or not, which is considered negative feedback control (NFC).

From these results, we have proved hypothesis (c); however, we would like to examine more details for this hypothesis.

#### 4.3 Relevance between individual differences and personality

Two teams were selected from the aspect of low stakes assessments (highest and lowest teams, assessing for ability of conceptual metaphor and collaboration), in order to examine more in detail from the aspect of individual differences (Table 7). It is easy to compare the improvement performances among students' traits and records or between teams by parallel processing and analyses. The result of the comparison of the average scores between Eidetic and Adjusting types and between first and second semesters has been examined this parallel processing and analyses, which have shown matching with each other.

Moreover, the comparison of those examinations between results of scores and descriptions of students (Appendix 1 and 2) by parallel processing has shown their matching. From this viewpoint, whether those results are matching with the evaluation of personality, regarding the factors of lack of objectivity (O Factor) and lack of cooperativeness (Co Factor) among 12 factors (Appendix 3). Students of Adjusting type (SubB-1, SabB-4, and SubC-3) have taken low scores for both factors; in other words, they are evaluated as objectivity and cooperativeness are strong. On the other hand, students of eidetic type (SubB-3 and SubC2) have taken high score in both factors, comparing with the former students, which means they are subjective and a little bit uncooperative.

Consequently, we might be also able to predict their behavior from traits of information processing. Though the results of our experiments have been proven useful, they are complicated for us. In addition to it, instructors must be busy to prepare other instructions for students. From these reasons, AI machine or doctor which might be able to obtain machine learning is expected and prospected for matching members of team by optimizing combinations.

#### 5. Conclusions

In this chapter, dual loop theory, which consisted of two kinds of feedback control, concerning with human information processing, was proposed (Figure 6)

and their needs. Hence, we have begun to support optimizing combination; however, there is no exact solution for it [23]. For those reasons, we have developed the support system or personalized education and learning. This has the measuring

As I have mentioned above, however, it has been becoming complicated to combine members of teams. Therefore, if AI doctor or machine would solve this problem by optimizing combination, personalized education and learning would be

From these viewpoints, this study and the measuring system for clarifying

We have planned to examine dual loop theory, which I have proposed as hypotheses and implemented experiments, gathered data, and analyzed them. Those ideas were hinted by Card's Model Processor [18], which is a "cognitive model of the user to be employed by the designer in thinking about the human interaction with computer at the interface" and "the Recognize-Act Cycle of the Cognitive Processor," from the view of LTM and STM as a simple reaction time. Although they have introduced this model, they have tried to propose another one (GOES: Goals, Operations, Methods, and Selections) for tasks which can be taken from the half-second level to the two-second level. Approximately, dual loop theory model (Figure 6) might be a combination of those two models and we can predict subjects' behavior. Many of such models have been introduced; however, there might be a few to find out individual differences in human information processing. The idea of this dual loop theory might be similar to the others, however, we seek for finding out individual differences which patters would indicate some types

Although having said that, when the model is examined, we need to use previous studies as references. For instance, by comparing processing between sound voice and letters [24] and cycle reaction time which is proposed by Card [18], we have examined calibration of measuring instrument. From the results of analysis for response time by presenting sound voice have been shown the high level of the calibration from the viewpoints of reliability and the reproducibility (Figure 7, left), considering the high correlation coefficient with the number of words which means cycle of response time. On the other hand, in the letter presentation case, it was recognized reproducibility; however, its correlation coefficient with the num-

From this result, it was predicted that individual differences clearly among students concerning the way of silent reading. Then, categorized types of trait (visual or auditory type) by strengthening of the correlation coefficient between response time and the number of words or duration of reading aloud. There are no differences between the two types of reaction time represented questionnaires by sound voice, but recognized significantly differences by letters (Figure 8 under Table 5). Students of Auditory type have needed time longer than those of Visual type from starting to silent reading to making decision (Figure 5). This means that

the auditory type might tend to process a word and a sentence with

process directly encoding symbol using STM or PFC loop.

phonologization, using LTM or NFC loop; conversely, the visual type tends to

From these results of analyses, the hypotheses [a] and [b] have been proved, and next hypothesis [c] should be examined. It was predicted that depending on

system to provide students' data to instructors before starting classes.

interactive communication with people by machine learning.

4.2 Examination of dual loop theory

Assistive and Rehabilitation Engineering

of trait concerning with cognitive behavior.

ber of words was not shown high.

64

improved. To achieve this meaningful goal, we need to clarify information processing for interactive communication. This must have synergic effect on AI doctor, care assisting robots and so on, because they need to obtain the ability of

human information processing must be meaningful to achieve our goal.

and examined by analyzing the results of experiments. The data were gathered students' response time, using psychological questionnaires (Figures 4 and 5) and their records of performances in collaborative learning class and analyzed by the way of parallel distributed processing. The results were as follows:

traits of information processing type (Figure 9). In the case of Adjusting type, the average of response time for emotional contexts was significantly faster

4.Therefore, the average scores of students' records were compared between Eidetic and Adjusting types. The result has shown the quantitative interaction

5.Moreover, we have examined whether those individual differences are

connected to other students' performances (Table 7, Appendix 1 and 2), and then, checking the verification of the criteria which classified traits both of

6.Finally, we have discussed on hypotheses (2.3), from three aspects: meaning of clarifying human information processing, the examination of dual loop theory, and the relevance between individual differences and personality. In conclusion,

processing by both positive and negative feedback controls, comparing the other type of students, depending on the context. In addition to this result, we have

We need to examine this theory furthermore and optimize the combination of members in order to communicate interactively among students and instructors. Eventually, those results would help the modern style machine learning of artificial intelligent to predict human behavior depending on types and consequently

In conclusion, dual loop theory would be expected to help us to understand the system of human information processing and predict our behavior according to its patterns. It would be also applicable widely to the machine learning system, for instance, AI doctor and assistive robots which requires the interactive communica-

The author is grateful to Dr. Kiyoko Tokunaga and participants for collaboration

the feature of Adjusting type has been shown their way of information

checked their performances, descriptions, and interviews practically.

than that of non-emotional contexts (Table 6).

Dual Loop Theory: Eidetic Feedback Control and Predictive Feedback Control

personality and cognitive features (Appendix 3).

improve their interactive communication with human beings.

between them (Figure 10).

DOI: http://dx.doi.org/10.5772/intechopen.89681

tion with human.

Appendix 1

67

Acknowledgements

in our practical research.


It was found out that the average of response time depending on types was different between each other. In the case of Auditory type, the average of response time was significantly longer than those of Visual type (Table 5 and Figure 8).

3.Next, when the sentences were divided into two categories, emotion and nonemotion, there were found different phenomena among students, regarding


#### Table 6.

Results of tests, the significant differentiation of reaction time between emotion and non-emotion context for Adjusting type.


Table 7. Comparison scores between teams.

traits of information processing type (Figure 9). In the case of Adjusting type, the average of response time for emotional contexts was significantly faster than that of non-emotional contexts (Table 6).


We need to examine this theory furthermore and optimize the combination of members in order to communicate interactively among students and instructors. Eventually, those results would help the modern style machine learning of artificial intelligent to predict human behavior depending on types and consequently improve their interactive communication with human beings.

In conclusion, dual loop theory would be expected to help us to understand the system of human information processing and predict our behavior according to its patterns. It would be also applicable widely to the machine learning system, for instance, AI doctor and assistive robots which requires the interactive communication with human.
