• The Journal of Bigdata
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• v.4 no.2
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• pp.175-183
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• 2019

Drop-out issue is one of the challenges of cyber university. There are about 130,000 students enrolled in cyber universities, but the dropout rate is also very high. To lower the dropout rate, cyber universities invest heavily in learning analytics. Some cyber universities analyze the possibility of dropout and actively support students who are more likely to drop out. The purpose of this paper is to identify the learning data affecting the dropout prediction index. As a result of the analysis, it is confirmed that number of lessons(progress), credits, achievement and leave of absence have a significant effect on dropout rate. It is necessary to increase the accuracy of the prediction model through post-test on the student dropout prediction index.

• Journal of the Korean Institute of Educational Facilities
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• v.3 no.3
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• pp.41-57
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• 1996

본 연구는 광희중학교 학구내에서 재개발로 인하여 증가되는 인구수을 예측하여 장래 중학교 학생수를 예측하였다. 2016까지 학급당 학생수를 37명으로 하고 36학급 규모의 학교를 추구한다면 중학교는 적어도 1개 더 건축하여야만 재개발로 늘어나는 제1학군의 학생수를 수용할 수있을 것음을 분석하였다. 또, 교과과정을 분석한 결과 도덕 2.5교실, 국어 6교실, 사회 5교실, 수학 5교실, 과학 5교실, 체육 4교실, 음악 2교실, 미술 2교실, 가정 1.5교실, 기술 3교실, 영어 5.5교실, 한문 1교실, 컴퓨터 1교실로 분석되어 이용율이 88%가 되었다. 본 연구는 광희중학교 구체적 건축계획에 앞서 계획의 모델을 설정하여 이를 토대로 계획에 임하였다. 광희중학교 주변의 접근성, 교통 조건, 소음 상태, 지역사회인의 이용, 전망 등의 환경 분석을 토대로 4개의 죠닝(Zonning)안을 제시하여 평가한 후 가장 바람직한 안을 선정하였다. 이를 토대로 브록(Block)프랜을 5개 작성하여 평가후 1개 안을 채택하여 구체적 평면 계획안을 작성하였다. 36학급 37명 학생수를 기준으로 교과교실형으로 계획하였으며 특별 교실형의 학습도 가능하게 계획하였다. 교수, 학습의 복합화에 대처하여 칸막이를 이동 가능한 형태로 계획하였으며, 일반 교과도 컴퓨터를 이용한 수업이 가능하게 정보 코너를 설치하였다. 지역사회인에게 열린 교실이 되게 계획하였고 개별 학습이 가능한 구조로 계획하교 기자재의 선진화를 대비한 학습 환경의 제고도 고려하였다. 본 연구의 입면 형상은 주변 건물과 조화되게 수평적 요소가 강조되는 형상이 되도록 계획하며 고층의 아파트의 위협을 상쇄시키기 위하여 지붕이 있는 구조로 계획하여 지역사회에서 중심임을 강조하도록 계획하였다.

• Korean Educational Research Journal
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• v.43 no.1
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• pp.125-152
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• 2022

The purpose of this study is to examine the differences of perceptions of teachers and students regarding teaching skills. For the analysis, data was collected by ICALT(International Comparative Analysis of Learning and Teaching) class observation tool and students survey called My Teacher Questionnaire. a student survey. The data of teachers and students can be compared because as the two tools have seven common domains(Safe and stimulating learning climate, Efficient organization, Clear and structured instructions, Intensive and activating teaching, Adjusting instructions and learner processing to inter-learner differences, Teaching learning strategies, Learner engagement). In 2016, in Daejeon, Chungbuk and Chungnam. trained teachers collected data from 106 classes, and 2,866 students responded the survey. The reliability and validity of the two tools, class observation and MTQ(My Teacher Questionnaire) are proven to be satisfactory for use in Korean schools. Students perception on teaching was high, particularly when students are in lower grades and learning major subjects like English, Korean, and math. The domain of higher teaching skills, male students show higher perceptions while female students reported higher perceptions on lower-level teaching skill domains. To compare the perceptions of teachers and students, the predictive reliability of students engagement against teaching skill domains was used. Teachers showed higher predictive reliability on lower teaching skill domains while students showed higher predictive reliability on higher teaching skill domains. It is recommended for further study to develop a professional development model using a teacher class observation tool and the My Teacher Questionnaire for pre-service teachers and school teachers.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.469-476
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• 2021

The purpose of this study is to explore the predictors of academic probation in college. Especially, this study focused on student engagement variables among the predictors of academic probation in college. Student engagement variables include hours of absence from class and numbers of log to LMS(Learning Management System) and in extracurricular program system during four weeks after the opening of a course and the numbers of faculty counseling. GPA(grade Point Average) is a dependent variable and GPA of prior semester is a control variable in this study. 17,261 student data were collected for the study. Linear regression model and logistic regression model analyses were conducted in the study. The finding showed that the hours of absence from class and numbers of log in extracurricular program system during four weeks after the opening of a course predicted academic achievement of college students. The result also indicated that hours of absence from class and numbers of log-ins to LMS(Learning Management System) and in extracurricular program system during four weeks after the opening of a course were the predictors of academic probation in college. This study will contribute to investigate indicators of students with low academic performance and to provide proper support for underachievers.

• Journal of Gifted/Talented Education
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• v.23 no.5
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• pp.835-855
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• 2013

The purpose of this study was to investigate the predictive validity of behaviroal characteristics checklists that are widely used in Korea for identifying mathematically gifted students. Three most widely used checklists were selected and implemented to classroom teachers who could teach and observe gifted students in regular classes. The predictive validity of the tree checklists were explored by generating the correlations between their ratings using those three checklists and the performance levels of gifted students, which were measured by teachers in gifted classes. Findings of this study are the followings: First, all three checklists could statistically significantly predict the performance of gifted students in gifted programs, and the checklist B showed the highest predictability. Secondly, without the assistance by those checklists, teachers could not predict the performance level of gifted students. Lastly, teachers that were trained for educating gifted students could very effectively predict the performance of gifted students with the aid of those checklists while teachers without appropriate training could not at all even with the aid of those checklists.

• The Journal of Sustainable Design and Educational Environment Research
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• v.15 no.1
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• pp.30-39
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• 2016

Students receiving plan is not based on short-term indicators, such as student-centered, student-induced factor to address school needs new complaint, it is necessary to establish the school in the center of a long-term (30 years) perspective. Therefore, analysis of Cheongju students can examine the entire 30 years of the elementary school in this study are as follows: First, given the increasing number of students in seven models and presented the case to its types. Second, considering the geographical characteristics and the development of regional characteristics classify 55 elementary Schools in Cheongju City by dividing the number of students increase or decrease trend to 10 zones the results are as follows: Students Number increasing school group of 4 schools, 15 schools students Number fell in shot Term, the Students Number dropped in middle Term 26 schools, 10 was a small school. In particular, it is urgently necessary to establish measures for these small schools. Third, despite the reduced number of students indicated in the analysis result, caused the social conflict factors by excessive new school requirements. It also caused a number of students from schools when the Curve of Students Number are to remain flat or decline. It shows that no additional new demand of School in the region. Fourth, the number of students increasing trend forecasting model

• The Journal of Sustainable Design and Educational Environment Research
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• v.15 no.3
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• pp.26-36
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• 2016

The purpose of this study is to provide a basis for determining when a school established long term school plans accepted by analyzing the trend of increase or decrease elementary school students 30 years to target of following nine cities, 607 elementary schools in Korea - 4 metropolitan cities(Incheon, Seongnam, Su-won and Anyang), 2 central regional cities (Daejeon and Cheongju) and 3 southern regional cities(Busan, Yangsan and Kimhae) for this purpose. Results of this study are as follows: First, there were overwhelming numbers of type5 among15 types of increase / decrease in the number of students. Second, in comparison with the type of increase / decrease of the number of students by region, the metropolitan area is ranked as type5>type13>type10>type8, in the middle region type5>type11>type10>type13 and in southern region type5>type10>type11>type13>type2. Therefore, there were regional differences in the number of students. Third, the results of the Conflict Model I and Conflict Model II showed that Type1 and Type7 were not needed to be adopted.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.23-32
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• 2024

This study utilized minimum number of demographic variables and first-semester GPA of students to predict the final academic status of students at a vocational college in Seoul. The results from XGBoost and LightGBM models revealed that these variables significantly impacted the prediction of students' dismissal. This suggests that early academic performance could be an important indicator of potential academic dropout. Additionally, the possibility that academic years required to award an associate degree at the vocational college could influence the final academic status was confirmed, indicating that the duration of study is a crucial factor in students' decisions to discontinue their studies. The study attempted to model without relying on psychological, social, or economic factors, focusing solely on academic achievement. This is expected to aid in the development of an early warning system for preventing academic dropout in the future.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.1-10
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• 2021

Log data accumulated in the Learning Management System (LMS) provide high-quality information for the learning process of students. Until now, various studies have been conducted to predict students' academic achievement using LMS log data. However, previous studies were based on relatively small sample sizes of students and courses, limiting the possibility of generalization. This study developed and validated a deep neural network model for the early prediction of academic achievement of college students using massive LMS log data. To this end, we used 78,466,385 cases of LMS log data and 165,846 cases of grade data. The proposed model predicted the excellent-grade students with a high level of accuracy from the beginning of the semester. Meanwhile, the prediction accuracy for the moderate and underachieving groups was relatively low, but the accuracy improved as the time points of the prediction were delayed. This study is meaningful in that we developed an early prediction model based on a deep neural network with sufficient accuracy for practical utilization by only using LMS log data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.414-418
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• 2010

일반적으로 넓은 공간상에서 시간의 흐름에 따라 변화하는 이동객체의 '위치 정보'를 기반으로 사용자의 작업과 관련 있는 적절한 정보 또는 서비스를 제공하는 경우 이를 위치 추적(인식) 시스템으로 정의한다. RFID, USN, RTLS, GPS는 위치 인식 시스템의 대표적인 기술이며 해양, 농촌, 병원, 건축 등의 다양한 분야에서 적용 확산이 빠르게 진행되고 있다. 이러한 기술은 유비쿼터스 컴퓨팅의 핵심 기술로서 현대사회의 관심이 집중되고 있는 아동실종, 도난, 학교폭력 등의 문제를 해결하는데 적용될 수 있다. 본 논문에서는 이동객체를 모니터링하기 위한 접근법을 분석하고 이를 기반으로 RFID를 이용한 학생 이동 관리 시스템의 구축 내용을 기술한다. 이 시스템은 RFID로부터 획득되는 이동객체(학생)에 대한 실시간 데이터를 업무에 적절한 정보로 변환하여 사용자에게 알려준다. 이 시스템을 구축함으로써 관리자는 학교내부의 학생 위치를 실시간으로 식별 할 수 있고 미리 설정된 제한구역에 접근하는 학생을 신속하게 인지 할 수 있다. 또한 과거의 이력정보를 검색 할 수 있음으로써 실종, 도난 등에 대한 사후예측이 가능해짐에 따라 수동적이었던 학생 관리에 비해 융통적인 관리의 효과가 있고 안전한 학교생활을 학생들에게 제공해 줄 수 있게 된다.