• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.21-30
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• 2021

Unlike behaviors that are generally known, information regarding unspecific behaviors is insufficient. For an education or guidance regarding the unspecific behaviors, collection and management of data regarding the unspecific behaviors of special-needs students are needed. In this paper, a consultation management model based on behavior classification of special-needs students using machine learning is proposed. It collects data by photographing the behavior of special students in real time, analyzes the behavior pattern, composes a data set, and trains it in the suggestion system. It is possible to improve the accuracy by comparing the behavior of special students photographed later into the suggestion system and analyzing the results by comparing it with the existing data again. The test has been performed by arbitrarily applying unspecific behaviors that are not stored in the database, and the forecast model has accurately classified and grouped the input data. Also, it has been verified that it is possible to accurately distinguish and classify the behaviors through the feature data of the behaviors even if there are some errors in the input process.

• Journal of the Korean School Mathematics Society
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• v.13 no.4
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• pp.499-524
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• 2010

In this paper, we applied NIE(Newspaper In Education) to the course of study for statistics unit of elementary mathematics which can improve students' abilities of concept of statistics, analyzing data and problem solving so they can do these with direct activity by themselves and find out how NIE effects on children's learning achievement for statistics unit and more effective solution for the course of study for elementary mathematics.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.141-154
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• 2006

Recently, the decrease of the number of a high-school graduate influences the number of limit matriculation. Based on the resident registration population, we forecast for the number of a high-school graduate until 2022 year.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.983-991
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• 2003

The Web-based instruction on the internet provides lots of learners with the related information and knowledge beyond time and space. But in the Web-based instruction, there is a problem that the teaming process statuses for learners can be known only through an exam. This paper introduces a web monitoring method to check whether the learner has some problems in learning process and to be able to find out the students with the problems. In the method this paper proposes a learning time prediction model for predicting the proper next study time intervals based on the learner`s learning times and grades on Previous learning units. This method provides the educator with the learning Process statuses for learners. The Loaming prediction model for web-based monitoring can be used to stimulate learners to take the good teaming processes by sending automatically alerting messages if their real teaming times exceeds on his predicted learning time interval. The results of the estimation through case study on the web-based monitoring to use the teaming time prediction model show that most of on-line learners with Poor teaming process statuses get poor grades. In addition, the results show that learner`s poor habits keep going on without change.

• Journal of The Korean Association For Science Education
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• v.44 no.2
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• pp.141-153
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• 2024

The 2022 revised science curriculum aims to develop the ability to solve scientific problems arising in daily life and society based on convergent thinking stimulated through participation in research activities using artificial intelligence (AI). Therefore, we developed a science-AI convergence education program that combines the science curriculum with artificial intelligence and employed it in convergence classes for high school students. The aim of the science-AI convergence class was for students to qualitatively understand the movement of a damped pendulum and build an AI model to predict the position of the pendulum using the block coding platform KNIME. Individual in-depth interviews were conducted to understand and interpret the learners' experiences. Based on Giorgi's phenomenological research methodology, we described the learners' learning processes and changes, challenges and limitations of the class. The students collected data and built the AI model. They expected to be able to predict the surrounding phenomena based on their experimental results and perceived the convergence class positively. On the other hand, they still perceived an with the unfamiliarity of platform, difficulty in understanding the principle of AI, and limitations of the teaching method that they had to follow, as well as limitations of the course content. Based on this, we discussed the strengths and limitations of the science-AI convergence class and made suggestions for science-AI convergence education. This study is expected to provide implications for developing science-AI convergence curricula and implementing them in the field.

• 한국벤처창업학회:학술대회논문집
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• 2022.11a
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• pp.119-122
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• 2022

본 연구의 목적은 중고등학생의 주관적 행복감이 공감 능력에 미치는 영향 관계에서 부모-자녀 의사소통의 매개효과를 실증적으로 검증하는 데 있다. 이를 위해 인천, 화성 등 경기도 내 거주 청소년을 대상으로 2022년 7월 10일에서 8월 20일까지 277명을 대상으로 설문조사를 실시하고, 277부 중 265부를 최종 분석에 사용하였다. SPSS 28.0과 Hayes(2013)가 제안한 Process Macro를 사용하여 자료를 분석하였다. 연구 결과는 첫째, 주관적 행복감이 높을수록 공감 능력이 높은 것으로 나타났다. 둘째, 주관적 행복감이 높을수록 부모-자녀 의사소통이 높은 것으로 나타났다. 셋째, 부모-자녀 의사소통이 높을수록 공감 능력이 높아지는 것으로 나타났다. 넷째, 주관적 행복감과 공감 능력의 관계에서 부모-자녀 의사소통은 정(+)적인 매개효과로 나타났다. 이는 부모-자녀 의사소통이 중고등학생의 공감 능력을 향상시킬 수 있는 예측 변인임을 시사하고 있다. 본 연구는 중고등학생의 공감 능력을 향상시키고, 사회성을 발달하기 위해 주관적 행복감의 수준을 활성화하고, 매개변인으로 부모-자녀 의사소통을 활성화하여 건전한 성장을 위한 효과를 높일 수 있는 다양한 청소년 프로그램 및 청소년 상담에 필요한 기초자료를 제공하는 데 의의가 있다.

• Science of Emotion and Sensibility
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• v.3 no.2
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• pp.85-101
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• 2000

감성은 의사결정에 많은 영향을 미침에도 불구하고, 시계열예측에 있어서의 연구는 매우 적은 편이다. 본 연구는 감성이 시계열 예측에 미치는 영향을 시계열정보의 형태 (그래프, 계정성)와 더불어 살펴보았다. 감성은 피험자로 하여금 인터넷시험을 보게 하고 즉시 그 결과를 아려줌으로 유발하였다. 시험결과가 좋은 피험자에게는 상금을 주어서 그 효과를 극대화하도록 하였다. 본 연구는 팩토리얼로 설계되었으며, 86명의 학생이 인터넷에서 운용되는 실험프로그램을 직접 사용하였다. 그 결과 감성은 그 자체로는 효과가 없었지만, 정보가 주어진 형태와 관련되어 그 효과가 타나났다는 점이 매우 흥미롭다. 특히 좋은 감성이 유발된 경우, 계절성이 테이블형태로 (그래프에서 잘 표현될 수 있다는 점에도 불구하고) 더욱 정확하게 처리하는 경향이 있었다. 또한 피험자의 뇌파를 분석한 결과 전두엽 베타파가 정확성에 많은 기여를 하는 것으로 나타났다.

• Journal of dental hygiene science
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• v.15 no.6
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• pp.807-814
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• 2015

The purpose of this study is to create a hypothetical model that explains and predicts oral health promotion behavior of adolescents by reviewing preceding literature on Pender's Health Promotion Model, and to verify the model's validity and proposed hypothesis through PLS (partial least square) structural equation model analysis. This study was cross-sectional survey consisted of self-administration questionnaires. The subjects in this study were a total of 293 alternative high school students in Jeollabuk-do Province. They were selected by convenience sampling. In alternative high school students, perceived benefit, locus of control, self-efficacy, and self-esteem had an effect on their oral health promoting behavior. As a result of the indirect effects in black is subjectively good subjective oral health, oral health related behaviors well past the more oral health promotion behavior showed a high. The prediction model of oral health promotion for adolescences, which was made using Pender's Health Promotion Model, was considered to be useful in explaining and predicting alternative high school students oral health promotion behavior.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.267-277
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• 2022

Achievement at university is recognized in a comprehensive sense as the level of qualitative change and development that students have embodied as a result of their experience in university education. Therefore, the academic achievement of university students will be given meaning in cooperation with the historical and social demands for diverse human resources such as creativity, leadership, and global ability, but it is practically an indicator of the outcome of university education. Measurement of academic achievement by such credits involves many problems, but in particular, standardization of academic achievement by credits based on evaluation methods, contents, and university rankings is a very difficult problem. In this study, we present a model that uses machine learning techniques to predict whether or not academic achievement is excellent for D-University graduates. The variables used were analyzed using up to 96 personal information and bachelor's information such as graduation year, department number, department name, etc., but when establishing a future education course, only the data after enrollment works effectively. Therefore, the items to be analyzed are limited to the recommended ability to improve the academic achievement of the department/student. In this research, we implemented an academic achievement prediction model through analysis of core abilities that reflect the philosophy, goals, human resources image, and utilized machine learning to affect the impact of the introduction of the prediction model on academic achievement. We plan to apply the results of future research to the establishment of curriculum and student guidance conducted in the department to establish a basis for improving academic achievement.

• Korean Journal of Comparative Education
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• v.28 no.4
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• pp.221-248
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• 2018

The purpose of this study was to analyze the performance of the Daegu Happiness Competency Education Program. It was confirmed that students, parents, teachers, and education professions are aware of the middle and higher level of education for happiness in Daegu in terms of the formation and operation of the curriculum. There is no significant difference between students and parents in terms of average value, and teachers' perception level is relatively high, which is understandable in that teachers are the subjects of the curriculum organization and operation. In addition, there was no statistically significant difference between the parents and the school level, but there were significant differences between students and teachers. In particular, students' and teachers' perceptions were lowered as the number of schools increased, unlike the predictions. They showed the lowest results in the special schools, autonomous schools and special schools. The reason for this is that Daegu Happiness Competency Education was implemented in 2014, and it was because there was little room to recognize and accept the new curriculum due to the burden of college entrance examination or employment. In the future, it will naturally improve as the education process is settled, but here we can find suggestions for the establishment of Daegu Happiness Competency Education.