• Convergence Security Journal
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• v.23 no.5
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• pp.117-123
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• 2023

Recently, as the demand for Generative Artificial Intelligence (AI) and artificial intelligence has increased, the seriousness of misuse and abuse has emerged. However, intelligent CCTV, which maximizes detection of abnormal behavior, is of great help to prevent crime in the military and police. AI performs learning as taught by humans and then proceeds with self-learning. Since AI makes judgments according to the learned results, it is necessary to clearly understand the characteristics of learning. However, it is often difficult to visually judge strange and abnormal behaviors that are ambiguous even for humans to judge. It is very difficult to learn this with the eyes of artificial intelligence, and the result of learning is very many False Positive, False Negative, and True Negative. In response, this paper presented standards and methods for clarifying the learning of AI's strange and abnormal behaviors, and presented learning measures to maximize the judgment ability of intelligent CCTV's False Positive, False Negative, and True Negative. Through this paper, it is expected that the artificial intelligence engine performance of intelligent CCTV currently in use can be maximized, and the ratio of False Positive and False Negative can be minimized..

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.83-90
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• 2004

Strategic games are missing special qualities of genre these days. Game engines neither reason about behaviors of computer objects nor have learning ability that can prepare countermeasure in variously command user's strategy. This paper suggests a strategic game engine that applies non-monotonic reasoning and inductive machine learning. The engine emphasizes three components -“user behavior monitor”to abstract user's objects behavior,“learning engine”to learn user's strategy,“behavior display handler”to reflect abstracted behavior of computer objects on game. Especially, this paper proposes two layered-structure to apply non-monotonic reasoning and inductive learning to make behaviors of computer objects that learns strategy behaviors of user objects exactly, and corresponds in user's objects. The engine decides actions and strategies of computer objects with created information through inductive learning. Main contribution of this paper is that computer objects command excellent strategies and reveal differentiation with behavior of existing computer objects to apply non-monotonic reasoning and inductive machine learning.

• Journal of vocational education research
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• v.36 no.4
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• pp.1-20
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• 2017

The purpose of this study is to identify the cognitive and psychological precedence factors of career preparation behaviors of university students and to clarify the structural relationships between the variables. First, the effects of reflective learning on university students' career preparation behaviors were examined and the mediating effect of grit between reflective learning and career preparation behavior was verified. The research analyzed 307 university students in the 3rd and 4th year. The results of the study have shown that the reflective learning had a significant positive relationship with all variables of grit and career preparation behavior, but non-reflective learning have an insignificance relationship with all the main variables. In addition, reflective learning has a direct positive effect on career preparation behavior, and grit has a mediating effect on the relationship between reflective learning and career preparation behavior. The results of this study indicate that the more original variables are further identified and extended to improve career preparation behaviors of university students. It is significant that they are provided with the basic data for the development of career and job preparation education programs that can be applied in the university education field. In addition, it has been confirmed that it is important for university students to improve their ability to critically reflect on themselves, their surroundings and circumstances in order to keep them engaged and to maintain their interests. Moreover, higher education institutions should provide fundamental and extensible method of practice and educational environment.

• Journal of Gifted/Talented Education
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• v.21 no.4
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• pp.829-845
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• 2011

The purpose of this study was to examine mathematical performance predictions with gifted behavior ratings by teachers and parents. The participants of this study were 787 elementary 5th and 6th grade gifted students who took the mathematical performance test. This study asked gifted teachers and parents to rate gifted behaviors of these gifted students with using SRBCSS-R (Renzulli et al., 2002, 2009). The results indicated that gifted teachers rated gifted behaviors of the 5th grade gifted students higher than the 6th grade gifted students, except in 'mathematical characteristics.' Gifted teachers rated 'learning' gifted behaviors of male gifted students higher than those of female gifted students. In the meanwhile, parents of the 5th grade gifted students rated gifted behaviors higher than parents of the 6th grade gifted students in 'learning' and 'motivation.' In comparing the gifted behavior ratings by gifted teachers and parents, there were significant differences in 'learning' and 'motivation' ratings. That is, gifted teachers rated significantly higher 'learning' and 'motivation' of gifted students than parents. When this study explored the prediction of gifted behavior ratings by gifted teachers and parents on mathematical performances of gifted students, 'learning' and 'mathematical characteristics' ratings by gifted teachers predicted the mathematical performances of gifted students.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.651-660
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• 2015

This study was conducted to consider application methods of infographic that corresponds to the educational goals of English subject, which is applied with different teaching and learning standards than other subjects. The aim of this study is to analyze the types and the characteristics of 'infographic completed by know-how learning', in other words, 'User behaviors involved infographic', which is frequently used in English textbook. Based on an analysis according to the teaching and learning standards, infographic used in English textbook were suggested in three types, which are 'General Concept', 'Significance' and 'Signification' centered infographic. In addition, according to the level of diagram composition, the main visualization attributes were derived as 'Overview', 'Structure', 'Relationships', 'Sequence', 'Transition between states' and 'Messages'. The major findings of this study are as follows: First, it is necessary to conduct a study on diverse display methods for 'Signification-centered infographic' that need to be displayed on the basis of two or more visual attributes. Second, as the purpose of application for applying infographic in English textbook collides with that in information design fields, it is found that verification is required on the educational effects in relation to this aspect.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.619-624
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• 2014

This paper introduces a robot-based learning system which is designed to teach multiplication to children. In addition to a small humanoid and a smart device delivering educational content, we employ a type of mixed-initiative operation which provides enhanced multi-modal cognition to the r-learning system through human intervention. To investigate major factors that influence people's intention to use the r-learning system and to see how the multi-modality affects the connections, we performed a user study based on TAM (Technology Acceptance Model). The results support the fact that the quality of the system and the natural interaction are key factors for the r-learning system to be used, and they also reveal very interesting implications related to the human behaviors.

• Educational Technology International
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• v.15 no.2
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• pp.71-88
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• 2014

A variety of studies to predict students' performance have been conducted since educational data such as web-log files traced from Learning Management System (LMS) are increasingly used to analyze students' learning behaviors. However, it is still challenging to predict students' learning achievement in blended learning environment where online and offline learning are combined. In higher education, diverse cases of blended learning can be formed from simple use of LMS for administrative purposes to full usages of functions in LMS for online distance learning class. As a result, a generalized model to predict students' academic success does not fulfill diverse cases of blended learning. This study compares two blended learning classes with each prediction model. The first blended class which involves online discussion-based learning revealed a linear regression model, which explained 70% of the variance in total score through six variables including total log-in time, log-in frequencies, log-in regularities, visits on boards, visits on repositories, and the number of postings. However, the second case, a lecture-based class providing regular basis online lecture notes in Moodle show weaker results from the same linear regression model mainly due to non-linearity of variables. To investigate the non-linear relations between online activities and total score, RF (Random Forest) was utilized. The results indicate that there are different set of important variables for the two distinctive types of blended learning cases. Results suggest that the prediction models and data-mining technique should be based on the considerations of diverse pedagogical characteristics of blended learning classes.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.145-156
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• 2022

Children are the foundation and future of this society and understanding their impressions and behaviors is very important and the child's behavioral problems are a burden on the family and society as well as have a bad impact on the development of the child, and the early diagnosis of these problems helps to solve or mitigate them, and in this research project we aim to understand and know the behaviors of children, through artificial intelligence algorithms that helped solve many complex problems in an automated system, By using this technique to read and analyze the behaviors and feelings of the child by reading the features of the child's face, the movement of the child's body, the method of the child's session and nervous emotions, and by analyzing these factors we can predict the feelings and behaviors of children from grief, tension, happiness and anger as well as determine whether this child has the autism spectrum or not. The scarcity of studies and the privacy of data and its scarcity on these behaviors and feelings limited researchers in the process of analysis and training to the model presented in a set of images, videos and audio recordings that can be connected, this model results in understanding the feelings of children and their behaviors and helps doctors and specialists to understand and know these behaviors and feelings.

• Journal of Korean Elementary Science Education
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• v.34 no.4
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• pp.447-457
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• 2015

This study has attempted to find the teaching methods for the elementary students with low science achievement by examining the differences of science learning motivation, academic stress and stress coping styles and the characteristics shown in the relationship between them. To achieve this, the differences of science learning motivation, academic stress and stress coping styles of the elementary students with low science achievement and their relationship was set up as a study problem. A science learning motivation using a science learning motivation questionnaire reconfigured with PALS along with underachievers diagnosis were measured targeting 660 elementary students located in Seoul. Using an academic stress questionnaire and stress coping style questionnaire, an academic stress and stress coping styles were measured. The results of analyzing the collected data are as follows. First, a science learning motivation of elementary students with low science achievement was lower than the general students but the academic stress was shown higher. Especially, the self-efficacy of science learning motivation was significantly lower and the school stress was highest. For stress coping styles, a tendency of passive and avoidment coping styles were shown higher than the general students. Second, among the science learning motivation of elementary students with low science achievement, the self-efficacy motivation and school stress have shown a negative correlation but had a positive correlation with the goal-oriented motivation centered on ability. In the correlation between the science learning motivation of elementary students with low science achievement and the stress coping styles, the pursuit of social support coping styles have shown a significant positive correlation with the science learning motivation and its subcategories. As a result of conducting a regression analysis on the influence of academic stress and stress copying styles on the science learning motivation of elementary students with low science achievement, among the academic stresses, the school stress was shown to have the biggest influence. Among the stress coping styles, the pursuit of social support coping styles had the biggest influence on the science learning motivation followed by active coping behaviors, passive and avoidment coping behaviors. Low science learning motivation as underachievement factors of elementary students with low science achievement was identified as having a relationship with high school stress and undesirable stress copying styles. Therefore, guidance and a program are required for the elementary student with low science achievement to have desirable stress coping methods on the stressful situations. In addition, for the improvement of science learning motivation, a learning environment is needed for the elementary students with low science achievement with seeking of relevant educational methods.

• Journal of The Korean Association For Science Education
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• v.20 no.2
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• pp.234-243
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• 2000

This study investigated the relationships between verbal behaviors and chemistry problem solving ability in cooperative learning. Based on the previous chemistry achievement. 11th-graders were assigned heterogeneously into three-membered groups. Small cooperative group problem solving processes in using 4 stage-problem solving strategy were audio/video taped. Students' chemistry problem solving ability was then measured by a problem solving strategy performance test. Their verbal behaviors were classified into giving information, receiving information, asking questions, and disagreeing. These were further coded into 16 subcategories. Providing, a subcategory of giving information, was the most frequent behavior. In studying partial correlation between verbal behaviors and problem solving ability, 7 categories were found to have significantly positive relationships. Providing showed the highest correlation with the problem solving ability as reported previously. Moreover, this study also revealed significant correlations in the categories of clarifying provided, correcting, justifying, and clarifying. In the case of low-ability students, the verbal behaviors of giving or receiving information were strongly correlated with problem solving ability. However, these verbal behaviors did not enhance the problem solving ability of high- and medium-ability students.