• Title/Summary/Keyword: Educational Network

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Attendance Appraisal for Learner Participation Degree Based Virtual Lecture (학습자 참여도 정보기반 가상강좌 출석평가 모델)

  • Kim, Hyun-Ju
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.4
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    • pp.119-129
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    • 2009
  • In The increasing use of computers and high-speed Internet network has greatly influenced education, causing a veering away from the typical and traditional way of delivering instruction. Specifically, the various kinds of Web-based multimedia technology, the interactive activities on the Internet, and satellite broadcasting technology are accelerating the emergence of a virtual-lectures-based educational model, which transcends time and space. Such virtual lectures make it possible for the entire teaching-learning process to be done in a virtual learning environment, thus giving rise to problem regarding learning guidance, feedback, and appraisal. In this paper, we propose a system for attendance appraisal for learner participation degree based virtual lecture, an appraisal element in virtual learning environments. This appraisal model can set the elements of virtual learning environments in such a way as to reflect in the attendance appraisal of the opened virtual learning environment information regarding the learner's participation in class. In addition, this model motivates the learners to actively participate in the virtual learning environment and to support instructors by accomplishing the activities that are needed for attendance appraisal.

A Survey of the State-of-the-Art in Korean Commercial IoT Services for deriving Core elements of Curriculum for Major Courses of IoT using RaspberryPi3 (라즈베리파이3 활용 IoT 교육과정 핵심요소 도출을 위한 한국의 상용 서비스 현황 고찰)

  • Lee, Kang-Hee;Ganiev, Asilbek
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.4
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    • pp.623-630
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    • 2017
  • This paper surveys the state-of-the-art in korean commercial Internet of Things(IoT) services for deriving the core elements of a curriculum for major courses of IoT using RaspberryPi3. First, we survey the state-of-the-art of IoT researches and commercial services in three korean major telecommunication corporations such as Korean Telecommunications (KT), LGU+ Telecommunication (LGT), and SK Telecommunication(SKT). Second, we consider the components and advantages of the RaspberryPi3 which is popular as a representative educational tool. Concludingly, this paper derives the core elements of curriculum for major courses of IoT using RaspberryPi3 from above both processes. The corresponding elements consist of platforms, hardwares, softwares, and big-data network. Based on the important design elements of the IoT curriculum using Raspberry Pie 3, we taught embedded system course to junior students for one semester. It was successfully completed and more than 90% students were satisfied with its contents and amounts.

A Comparative Study of Prediction Models for College Student Dropout Risk Using Machine Learning: Focusing on the case of N university (머신러닝을 활용한 대학생 중도탈락 위험군의 예측모델 비교 연구 : N대학 사례를 중심으로)

  • So-Hyun Kim;Sung-Hyoun Cho
    • Journal of The Korean Society of Integrative Medicine
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    • v.12 no.2
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    • pp.155-166
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    • 2024
  • Purpose : This study aims to identify key factors for predicting dropout risk at the university level and to provide a foundation for policy development aimed at dropout prevention. This study explores the optimal machine learning algorithm by comparing the performance of various algorithms using data on college students' dropout risks. Methods : We collected data on factors influencing dropout risk and propensity were collected from N University. The collected data were applied to several machine learning algorithms, including random forest, decision tree, artificial neural network, logistic regression, support vector machine (SVM), k-nearest neighbor (k-NN) classification, and Naive Bayes. The performance of these models was compared and evaluated, with a focus on predictive validity and the identification of significant dropout factors through the information gain index of machine learning. Results : The binary logistic regression analysis showed that the year of the program, department, grades, and year of entry had a statistically significant effect on the dropout risk. The performance of each machine learning algorithm showed that random forest performed the best. The results showed that the relative importance of the predictor variables was highest for department, age, grade, and residence, in the order of whether or not they matched the school location. Conclusion : Machine learning-based prediction of dropout risk focuses on the early identification of students at risk. The types and causes of dropout crises vary significantly among students. It is important to identify the types and causes of dropout crises so that appropriate actions and support can be taken to remove risk factors and increase protective factors. The relative importance of the factors affecting dropout risk found in this study will help guide educational prescriptions for preventing college student dropout.

Domestic and International Experts' Perception of Policy and Direction on STEAM Education (융합인재교육(STEAM)의 정책과 실행 방향에 대한 국내외 전문가들의 인식)

  • Jung, Jaehwa;Jeon, Jaedon;Lee, Hyonyong
    • Journal of Science Education
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    • v.39 no.3
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    • pp.358-375
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    • 2015
  • The purposes of this study were to investigate the value, necessity and legitimacy of STEAM Education and to propose practical approaching methods for STEAM Education to be applicable in Korea through a variety of literature review, case studies and collecting suggestions from domestic and international educational experts. The research questions are as follows: (1) To investigate the perception, understanding and recognitions of domestic and foreign professionals in STEAM education. (2) To analyze policy implications for an improvement in STEAM. The following aspects of STEAM were found to be challenges in our current STEAM policy after analyzing multiple questionnaires with the professionals and case studies including their experiences, understanding, supports and directions of the policy from the governments. The results indicate that (1) there was a lack of precise and conceptual understanding of STEAM in respect to experience. Training sessions for teachers in this field to help transform their perception is necessary. Development of practical programs with an easy access is also required. It is important to get the aims of related educational activities recognized by the professionals and established standards for an evaluation. The experts perceived that a theme-based learning is the most preferred and effective approaching method and the programs that develop creative thinking and learning applicable to practice are required to promote. (2) The results indicate that there was a lack of programs and inducements for supporting outstanding STEAM educators. It is shown that making an appropriate environment for STEAM education takes the first priority before training numbers of teachers unilaterally, thus securing enough budget seems critical. The professionals also emphasize on developing specialized teaching materials that include diverse inter-related subjects such as science technology, engineering, arts and humanities and social science with diverse viewpoints and advanced technology. This work requires a STEAM network for teachers to link up and share their materials, documents and experiences. It is necessary to get corporations, universities, and research centers participated in the network. (3) With respect to direction, it is necessary to propose policy that makes STEAM education ordinary and more practical in the present education system. The professionals have recommended training sessions that help develop creative thinking and amalgamative problem-solving techniques. They require reducing the workload of teachers and changing teachers' perspectives towards STEAM. They further urge a tight cooperation between departments of the government related with STEAM.

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Analysis of Internet Biology Study Sites and Guidelines for Constructing Educational Homepages (인터넷상의 고등학교 생물 학습사이트 비교분석 및 웹사이트 구축방안에 관한 연구)

  • Kim, Joo-Hyun;Sung, Jung-Hee
    • Journal of The Korean Association For Science Education
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    • v.22 no.4
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    • pp.779-795
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    • 2002
  • Internet, a world wide network of computers, is considered as a sea of information because it allows people to share information beyond the barriors of time and space. However, in spite of the unmeasurable potential applications of the internet, its use in the field of biology education has been extremely limited mainly due to the scarcity of good biology-related sites. In order to provide useful guidelines for constructing user-friendly study sites, which can help high school students with different intellectual levels to study biology, comparative studies were performed on selected educational sites. Initially, hundreds of related sites were examined, and, subsequently, four distinct sites were selected not only because they are well organized, but also because each is unique in its contents. Also, a survey was carried out against the users of each site. The survey results indicated that the high school students regard the web-based biology study tools as effective teaching methods although there might be some bias in criteria for selecting target sites. In addition to the detailed biology topics and the related biology informations, multimedia data including pictures, animations and movies are found to be one of the important ingredients for desirable biology study sites. Thus, the inclusion of multimedia components should also be considered when developing a systematic biology study site. Overall, the role of the cyber space is expected to become more and more important. Since the development of the user-satisfied and self-guided sites require interdisciplinary collaborational efforts which should be made to promote extensive communication among teachers, education professionals, and computer engineers. Furthermore, the introduction of good biology study sites to the students by their teachers is also important factor for the successful web-based education.

Demands of Education Programs for Evaluation of the Efficacy of Health Functional Foods (건강기능식품 기능성평가 교육요구도에 관한 연구)

  • Lee, Hyun-Sook;Kwon, O-Ran;Won, Hye-Suk;Kim, Joo-Hee;Kwak, Jin-Sook;Jeong, Se-Won;Hong, So-Young;Hong, Jin-Hwan;Lee, Hye-Young;Kim, Ji-Yeon;Kang, Yoon-Jung;Kim, Mi-Kyung
    • Journal of the Korean Society of Food Culture
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    • v.24 no.3
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    • pp.331-337
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    • 2009
  • The principal objective of the present study was to survey the demands of an education program for evaluations of the efficacy of health functional foods. A questionnaire was developed and sent to 2,225 members of the Biofood Network Center. A total of 101 (4.6%) individuals responded, 54.5% of the respondents were male and 45.5% were female; the respondents' occupations (in order of prevalence) were as follows: company worker (48.5%)>researcher (27.7%)>student (13.9%)>professor (5.0%)>pharmacist (2%), and dietitian (2%). The businesses in which the respondents worked were (again in order of prevalence) as follows: research & development (64.4%)>marketing (11.9%)>consultation and education (5.9%)>manufacturing and others (17.9%). 41.6% of the respondents reported experience in businesses relevant to KFDA approval for functional ingredients and health functional foods. The results showed that 63.4% of the respondents had previously been educated about functional foods; the types of education program reported were (in order of prevalence): 'overview and acts of health functional food' (n=49)>'standards and specification for health functional food' (n=41)>'efficacy evaluation-human study' (n=24)>'safety evaluation' (n=21)>'efficacy evaluation-in vivo study' (n=13)>and 'others' (n=10). Respondents preferred off-line education programs (62.4%) to on-line programs (22.8%). The preferred duration of an educational program was '$2{\sim}3$ days: total $14{\sim}24$ hours' (30.7%); thus, short-term programs were favored. The primary requirements of a program, from the perspective of the learner, were as follows (scored on a 7-point scale); 'efficacy evaluation and case study-human study' (5.80 points)>'standards and specification for health functional food' (5.72 points)>safety evaluation' (5.7 points)>'overview and acts of health functional food' (5.67 points) and 'efficacy evaluation methods of health functional food by efficacy (intensive)' (5.67 points). Preference for functionality was as follows; 'body weight & body fat' (21.8%), 'immune function' (18.8%) > 'blood glucose' (10.9%). In summary, the educational demand for 'efficacy evaluation and case study' was highest among the curriculum options provided, and with regard to functionality, 'body weight & body fat', 'immune function' and 'skin care' were considered most important by respondents. These results differed among respondents with different jobs and duties, and this suggests that customized education programs for health functional food should be developed.

Access Restriction by Packet Capturing during the Internet based Class (인터넷을 이용한 수업에서 패킷캡쳐를 통한 사이트 접속 제한)

  • Yi, Jungcheol;Lee, Yong-Jin
    • 대한공업교육학회지
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    • v.32 no.1
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    • pp.134-152
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    • 2007
  • This study deals with the development of computer program which can restrict students to access to the unallowable web sites during the Internet based class. Our suggested program can find the student's access list to the unallowable sites, display it on the teacher's computer screen. Through the limitation of the student's access, teacher can enhance the efficiency of class and fulfill his educational purpose for the class. The use of our results leads to the effective and safe utilization of the Internet as the teaching tools in the class. Meanwhile, the typical method is to turn off the LAN (Local Area Network) power in order to limit the student's access to the unallowable web sites. Our program has been developed on the Linux operating systems in the small network environment. The program includes following five functions: the translation function to change the domain name into the IP(Internet Protocol) address, the search function to find the active students' computers, the packet snoop to capture the ongoing packets and investigate their contents, the comparison function to compare the captured packet contents with the predefined access restriction IP address list, and the restriction function to limit the network access when the destination IP address is equal to the IP address in the access restriction list. Our program can capture all passing packets through the computer laboratory in real time and exactly. In addition, it provides teacher's computer screen with the all relation information of students' access to the unallowable sites. Thus, teacher can limit the student's unallowable access immediately. The proposed program can be applied to the small network of the elementary, junior and senior high school. Our research results make a contribution toward the effective class management and the efficient computer laboratory management. The related researches provides teacher with the packet observation and the access limitation for only one host, but our suggested program provides teacher with those for all active hosts.

Major Class Recommendation System based on Deep learning using Network Analysis (네트워크 분석을 활용한 딥러닝 기반 전공과목 추천 시스템)

  • Lee, Jae Kyu;Park, Heesung;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.27 no.3
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    • pp.95-112
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    • 2021
  • In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

Time Series Analysis of Park Use Behavior Utilizing Big Data - Targeting Olympic Park - (빅데이터를 활용한 공원 이용행태의 시계열분석 - 올림픽공원을 대상으로 -)

  • Woo, Kyung-Sook;Suh, Joo-Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.46 no.2
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    • pp.27-36
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    • 2018
  • This study suggests the necessity of behavior analysis as changes to a park environment to reflect user desires can be implemented only by grasping the needs of park users. Online data (blog) were defined as the basic data of the study. After collecting data by 5 - year units, data mining was used to derive the characteristics of the time series behavior while the significance of the online data was verified through social network analysis. The results of the text mining analysis are as follows. First, primary results included 'walking', 'photography', 'riding bicycles'(inline, kickboard, etc.), and 'eating'. Second, in the early days of the collected data, active physical activity such as exercise was the main factor, but recent passive behavior such as eating, using a mobile phone, games, food and drinking coffee also appeared as a new behavior characteristic in parks. Third, the factors affecting the behavior of park users are the changes of various conditions of society such as internet development and a culture of expressing unique personalities and styles. Fourth, the special behaviors appearing at Olympic Park were derived from educational activities such as cultural activities including watching performances and history lessons. In conclusion, it has been shown that people's lifestyle changes and the behavior of a park are influenced by the changes of the various times rather than the original purpose that was intended during park planning and design. Therefore, it is necessary to create an environment tailored to users by considering the main behaviors and influencing factors of Olympic Park. Text mining used as an analytical method has the merit that past data can be collected. Therefore, it is possible to form analysis from a long-term viewpoint of behavior analysis as well as to measure new behavior and value with derived keywords. In addition, the validity of online data was verified through social network analysis to increase the legitimacy of research results. Research on more comprehensive behavior analysis should be carried out by diversifying the types of data collected later, and various methods for verifying the accuracy and reliability of large-volume data will be needed.

Value and Prosect of individual diary as research materials : Based on the "The 12th May Diaries Collection" (개인 일기의 연구 자료로서의 가치와 전망 "5월12일 일기컬렉션"을 중심으로)

  • Choi, Hyo Jin;Yim, Jin Hee
    • The Korean Journal of Archival Studies
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    • no.46
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    • pp.95-152
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    • 2015
  • "Archives of Everyday Life" refers to an organization or facility which collects, appraises, selects and preserves the document from the memory of individuals, groups, or a society through categorizing and classifying lives and cultures of ordinary people. The document includes materials such as diaries, autobiography, letters, and notes. It also covers any digital files or hypertext like posts from blogs and online communities, or photos uploaded on Social Network Services. Many research fields including the Records Management Studies has continuously claimed the necessity of collection and preservation of ordinary people's records on daily life produced every moment. Especially diary is a written record reflecting the facts experienced by an individual and his self-examination. Its originality, individuality and uniqueness are considered truly valuable as a document regardless of the era. Lately many diaries have been discovered and presented to the historical research communities, and diverse researchers in human and social studies have embarked more in-depth research on diaries, their authors, and social background of the time. Furthermore, researchers from linguistics, educational studies, and psychology analyze linguistic behaviors, status of cultural assimilation, and emotional or psychological changes of an author. In this study, we are conducting a metastudy from various research on diaries in order to reaffirm the value of "The 12th May Diaries Collection" as everyday life archives. "The 12th May Diaries Collection" consists of diaries produced and donated directly by citizens on the 12th May every year. It was only 2013 when Digital Archiving Institute in Univ. of Myungji organized the first "Annual call for the 12th May". Now more than 2,000 items were collected including hand writing diaries, digital documents, photos, audio and video files, etc. The age of participants also varies from children to senior citizens. In this study, quantitative analysis will be made on the diaries collected as well as more profound discoveries on the detailed contents of each item. It is not difficult to see stories about family and friends, school life, concerns over career path, daily life and feelings of citizens ranging all different generations, regions, and professions. Based on keyword and descriptors of each item, more comprehensive examination will be further made. Additionally this study will also provide suggestions to examine future research opportunities of these diaries for different fields such as linguistics, educational studies, historical studies or humanities considering diverse formats and contents of diaries. Finally this study will also discuss necessary tasks and challenges for "the 12th May Diaries Collection" to be continuously collected and preserved as Everyday Life Archives.