• Title/Summary/Keyword: Education Topic

Search Result 967, Processing Time 0.026 seconds

A Study on Educational Data Mining for Public Data Portal through Topic Modeling Method with Latent Dirichlet Allocation (LDA기반 토픽모델링을 활용한 공공데이터 기반의 교육용 데이터마이닝 연구)

  • Seungki Shin
    • Journal of The Korean Association of Information Education
    • /
    • v.26 no.5
    • /
    • pp.439-448
    • /
    • 2022
  • This study aims to search for education-related datasets provided by public data portals and examine what data types are constructed through classification using topic modeling methods. Regarding the data of the public data portal, 3,072 cases of file data in the education field were collected based on the classification system. Text mining analysis was performed using the LDA-based topic modeling method with stopword processing and data pre-processing for each dataset. Program information and student-supporting notifications were usually provided in the pre-classified dataset for education from the data portal. On the other hand, the characteristics of educational programs and supporting information for the disabled, parents, the elderly, and children through the perspective of lifelong education were generally indicated in the dataset collected by searching for education. The results of data analysis through this study show that providing sufficient educational information through the public data portal would be better to help the students' data science-based decision-making and problem-solving skills.

Analysis of Trends in Domestic Learning Counseling Research Using Text Mining Methods (텍스트 마이닝 방법을 활용한 국내 학습상담 연구 동향 분석)

  • Hyun, Yong-Chan;Yang, Ji-Hye;Park, Jung-Hwan
    • Journal of Convergence for Information Technology
    • /
    • v.12 no.3
    • /
    • pp.302-310
    • /
    • 2022
  • This study examined the results obtained using the text mining method for research trends related to learning counseling among adolescents and suggested subsequent research directions. The top 1 and 2 of Korean youth concerns are learning and career paths. Topic modeling analysis was conducted using text mining techniques that can minimize researcher's subjectivity and prejudice for 201 academic papers above KCI registration candidates through RISS with keywords such as Learning Counseling and Academic Counseling. Learning counseling topic results showed counseling experience [topic 1], group counseling research [topic 2], parent counseling [topic 3], and learning technology program development [topic 4]. Research related to learning counseling is developing counseling for emotional stability. Group counseling, parent counseling, and learning technology programs. Learning counseling to solve adolescents' concerns is expected to continue research on integrated support through psychological emotion, parent counseling, and collaboration with learning technology experts.

A study on research trends for pregnancy in adolescence: Focusing on text network analysis and topic modeling (청소년 임신에 대한 연구 동향 분석: 텍스트 네트워크 분석과 토픽 모델링)

  • Park, Seungmi;Kwak, Eunju;Park, Hye Ok;Hong, Jung Eun
    • The Journal of Korean Academic Society of Nursing Education
    • /
    • v.30 no.2
    • /
    • pp.149-159
    • /
    • 2024
  • Purpose: The aim of this study was to identify core keywords and topic groups in the "adolescent pregnancy" field of research for a better understanding of research trends in the past 10 years. Methods: Topics related to adolescent pregnancy were extracted from 3,819 articles that were published in journals between January 2013 and July 2023. Abstracts were retrieved from five databases (MEDLINE, CINAHL, Embase, RISS, and KISS). Keywords were extracted from the abstracts and cleaned using semantic morphemes. Text network analysis and topic modeling were performed using NetMiner 4.3.3. Results: The most important keywords were "health," "woman," "risk," "group," "girl," "school," "service," "family," "program," and "contraception." Five topic groups were identified through topic modeling. Through the topic modeling analysis, five themes were derived: "health service," "community program for school girls," "risks for adult women," "relationship risks," and "sexual contraceptive knowledge." Conclusion: This study utilized text network analysis and topic modeling to analyze keywords from abstracts of research conducted over the past decade on adolescent pregnancy. Given that adolescent pregnancy leads to physical, mental, social, and economic issues, it is imperative to provide integrated intervention programs, including prenatal/postnatal care, psychological services, proper contraception methods, and sex education, through school and community partnerships, as well as related research studies. Nurses can play a vital role by actively engaging in prevention efforts and directly supporting and educating socially disadvantaged adolescent mothers, which could significantly contribute to improving their quality of life.

Development and Application of STEAM Education Program based on Topic-specific Project (주제중심 프로젝트 기반 STEAM 교육 프로그램 개발 및 적용)

  • Lee, Youngseok;Cho, Jungwon
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.13 no.12
    • /
    • pp.5770-5775
    • /
    • 2012
  • For this study, we reviewed theoretical background of STEAM education and domestic and international studies in STEAM education, by doing so, we developed and applied the STEAM education program based on topic-specific project. This program is designed for the 3rd and 4th lesson of 6th graders' science in elementary school. As a result, the positive attitude about science of the students who went through the researched program increased with meaningful difference compared to that of the sample population. The result of this study shows that the STEAM education program based on topic-specific project can brings positive changes for the science-related affective domains.

Identifying research trends in the emergency medical technician field using topic modeling (토픽모델링을 활용한 응급구조사 관련 연구동향)

  • Lee, Jung Eun;Kim, Moo-Hyun
    • The Korean Journal of Emergency Medical Services
    • /
    • v.26 no.2
    • /
    • pp.19-35
    • /
    • 2022
  • Purpose: This study aimed to identify research topics in the emergency medical technician (EMT) field and examine research trends. Methods: In this study, 261 research papers published between January 2000 and May 2022 were collected, and EMT research topics and trends were analyzed using topic modeling techniques. This study used a text mining technique and was conducted using data collection flow, keyword preprocessing, and analysis. Keyword preprocessing and data analysis were done with the RStudio Version 4.0.0 program. Results: Keywords were derived through topic modeling analysis, and eight topics were ultimately identified: patient treatment, various roles, the performance of duties, cardiopulmonary resuscitation, triage systems, job stress, disaster management, and education programs. Conclusion: Based on the research results, it is believed that a study on the development and application of education programs that can successfully increase the emergency care capabilities of EMTs is needed.

A Study on the Categorizes of School Bullying through Topic Modelling Method (토픽모델링 기반의 학교폭력 사례 유형 연구)

  • Shin, Seungki
    • 한국정보교육학회:학술대회논문집
    • /
    • 2021.08a
    • /
    • pp.181-185
    • /
    • 2021
  • As part of an effort to derive measures to prevent school violence, which is continuously emphasized in the school field, this study tried to examine the topic that has recently become an issue related to school violence from the perspective of data science. In particular, it was attempted to crawl posts related to school violence using online SNS data and examine the characteristics of each type by using the topic modeling method. As a result of arranging the keywords for each topic derived from the topic modeling analysis by type, it was possible to divide the contents into three main categories: prevention of school violence, punishment of perpetrators, and measures to be taken. First, as the contents of school violence prevention activities, it is the contents of the role of specialized organizations for the prevention of school violence. Second, it was derived from the contents of measures and procedures for school violence. Third, it was possible to examine the contents of recent issues of school violence. In future research, it is necessary to conduct research that is used to solve the social problems facing based on data-based prediction.

  • PDF

An analysis of domestic research trends of mathematics curriculum research through topic modeling: Focused on domestic journals published from 1997 to 2019 (토픽모델링을 활용한 국내 수학과 교육과정 연구 동향 분석 : 1997년부터 2019년까지 게재된 국내 수학교육 학술지 논문을 중심으로)

  • Son, Taekwon;Lee, Kwangho
    • The Mathematical Education
    • /
    • v.59 no.3
    • /
    • pp.201-216
    • /
    • 2020
  • This study analyzed 493 domestic mathematics curriculum articles published in KCI's listings from 1997 to 2019 using LDA topic modeling. As a result, domestic mathematics curriculum research could be categorized into eight topics such as 'context in a curriculum', 'analysis a curriculum by the mathematical concept', 'form, system, meaning, and character of a curriculum', 'instruction and application of a curriculum', 'implementation and evaluation of a curriculum', 'tasks in a curriculum', 'analysis of a curriculum based on ability', 'compare and analysis curriculum and textbook'. The topic 'implementation and evaluation of a curriculum' was identified with the lowest proportion. Also, we performed the simple regression analysis with the weight of topics in the application period of the curriculum, and 'analysis of a curriculum based on ability' appeared as a 'hot topic'. Furthermore, topics appeared differently depending on the application period of the curriculum. Some of the appeared topics showed a tendency to match the emphasis of the highlight in a mathematics curriculum. Based on the results, future studies should develop frameworks for mathematics curriculum studies and extend the field of mathematical curriculum studies to make progress. Furthermore, future studies are needed to examine the enactment, feedback, and competency evaluation in the mathematical curriculum.

Analyzing Students' Non-face-to-face Course Evaluation by Topic Modeling and Developing Deep Learning-based Classification Model (토픽 모델링 기반 비대면 강의평 분석 및 딥러닝 분류 모델 개발)

  • Han, Ji Yeong;Heo, Go Eun
    • Journal of the Korean Society for Library and Information Science
    • /
    • v.55 no.4
    • /
    • pp.267-291
    • /
    • 2021
  • Due to the global pandemic caused by COVID-19 in 2020, there have been major changes in the education sites. Universities have fully introduced remote learning, which was considered as an auxiliary education, and non-face-to-face classes have become commonplace, and professors and students are making great efforts to adapt to the new educational environment. In order to improve the quality of non-face-to-face lectures amid these changes, it is necessary to study the factors affecting lecture satisfaction. Therefore, This paper presents a new methodology using big data to identify the factors affecting university lecture satisfaction changed before and after COVID-19. We use Topic Modeling method to analyze lecture reviews before and after COVID-19, and identify factors affecting lecture satisfaction. Through this, we suggest the direction for university education to move forward. In addition, we can identify the factors of satisfaction and dissatisfaction of lectures from multiangle by establishing a topic classification model with an F1-score of 0.84 based on KoBERT, a deep learning language model, and further contribute to continuous qualitative improvement of lecture satisfaction.

Open-Ended Response Analysis for University Course Evaluations using Topic Modeling (토픽 모델링을 활용한 대학 강의평가 개방형 응답분석)

  • Su-Hyun Ahn;Sang-Jun Lee
    • Journal of Practical Engineering Education
    • /
    • v.15 no.3
    • /
    • pp.539-547
    • /
    • 2023
  • In recent years, university education has emphasized a learner-centered education model with a change in educational paradigm. This study aims to explore students' diverse opinions and improve the quality of education by analyzing the open-ended responses of university lecture evaluations using topic modeling. To this end, a total of 45,001 open-ended responses based on the results of lecture evaluations from 2017 to 2022 in non-metropolitan universities were divided into majors and liberal arts, and a short-form optimized Biterm Topic Modeling (BTM) analysis was conducted. As a result of the analysis, major lectures were divided into "attitude toward non-face-to-face classroom experience", "attitude toward questions and discussions", "attitude toward attendance and grading", "attitude toward practical activities and presentations", and "attitude toward communication and collaboration", while liberal arts lectures were divided into "attitude toward non-face-to-face classroom experience", "attitude toward grades and evaluations", "attitude toward attendance and syllabus", "attitude toward academic knowledge and interest", and "attitude toward communication and questions". The results of this study, which analyzed various feedback from students, provide insights that can be used to compare the characteristics of majors and liberal arts courses and improve teaching and learning experiences.

A study on research trends for gestational diabetes mellitus and breastfeeding: Focusing on text network analysis and topic modeling (임신성 당뇨와 모유수유에 대한 연구 동향 분석: 텍스트네트워크 분석과 토픽모델링 중심)

  • Lee, Junglim;Kim, Youngji;Kwak, Eunju;Park, Seungmi
    • The Journal of Korean Academic Society of Nursing Education
    • /
    • v.27 no.2
    • /
    • pp.175-185
    • /
    • 2021
  • Purpose: The aim of this study was to identify core keywords and topic groups in the 'Gestational diabetes mellitus (GDM) and Breastfeeding' field of research for better understanding research trends in the past 20 years. Methods: This was a text-mining and topic modeling study composed of four steps: 1) collecting abstracts, 2) extracting and cleaning semantic morphemes, 3) building a co-occurrence matrix, and 4) analyzing network features and clustering topic groups. Results: A total of 635 papers published between 2001 and 2020 were found in databases (Web of Science, CINAHL, RISS, DBPIA, RISS, KISS). Among them, 3,639 words extracted from 366 articles selected according to the conditions were analyzed by text network analysis and topic modeling. The most important keywords were 'exposure', 'fetus', 'hypoglycemia', 'prevention' and 'program'. Six topic groups were identified through topic modeling. The main topics of the study were 'cardiovascular disease' and 'obesity'. Through the topic modeling analysis, six themes were derived: 'cardiovascular disease', 'obesity', 'complication prevention strategy', 'support of breastfeeding', 'educational program' and 'management of GDM'. Conclusion: This study showed that over the past 20 years many studies have been conducted on complications such as cardiovascular diseases and obesity related to gestational diabetes and breastfeeding. In order to prevent complications of gestational diabetes and promote breastfeeding, various nursing interventions, including gestational diabetes management and educational programs for GDM pregnancies, should be developed in nursing fields.