• Title/Summary/Keyword: Educational Data Mining

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A Study on the Development of the Use Index of Closed School Facilities Using Big Data -Focused on Text-Mining Techniques- (빅데이터를 활용한 폐교시설의 지표 개발에 관한 연구 -텍스트마이닝 기법을 중심으로-)

  • Kim, Jae-Young;Lee, Jong-Kuk
    • The Journal of Sustainable Design and Educational Environment Research
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    • v.18 no.2
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    • pp.1-11
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    • 2019
  • The purpose of this study is to make objective decisions in the use of closed schools through the development of utilization indicators for the efficient use of closed schools, which is expected to increase continuously. The research phase was largely carried out by drawing preliminary indicators for use in closed schools, drawing final indicators using big data, and quantifying indicators, and finally objectifying them through quantification. The institution intends to apply and verify the facility based on future indicators. This study has implications for the application of big data analysis methods that have not been attempted in planning and research for the use of closed school facilities to date.

Current Status of Educational Big Data Research (교육 빅데이터 관련 연구 동향)

  • Lee, Eun-young;Park, Do-oung;Choi, In-ong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2014.07a
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    • pp.175-176
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    • 2014
  • 본고에서는 교육 빅데이터의 개념, 가치, 처리 기술 및 분석 방법 등을 탐색하였다. '온라인과 오프라인 교수 학습 활동의 투입, 과정, 산출을 통해 생산되는 국가, 지역, 학교, 교사, 학생 수준의 자료'로 정의할 수 있는 교육 빅데이터는 Hadoop으로 대표되는 분산 컴퓨팅 기술을 통해 효율적으로 처리할 수 있다. 대규모 교육 자료에서 의미있고 유용한 결과를 도출하기 위해 주로 사용되는 분석 방법에는 교육 데이터 마이닝, 학습 분석학과 시각 자료 분석학이 있다. 교육 데이터 마이닝은 학생과 교사, 학교의 다양한 수준에서 자료를 폭넓게 분석하는 측면이 강한 반면에 학습 분석학은 학생 수준에서의 자료 분석에 더 초점을 맞추는 경향이 있으며, 시각 자료 분석학은 자료에 대한 분석 자체보다는 분석 결과를 효과적으로 표현하는 방식에 초점이 주어져 있다.

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Data Mining Analysis of Educational and Research Achievements of Korean Universities Using Public Open Data Services (정보공시 자료를 이용한 교육/연구성과 영향요인 추출 및 대학의 군집 분석)

  • Shin, Sun Mi;Kim, Hyeon Cheol
    • The Journal of Korean Association of Computer Education
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    • v.17 no.1
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    • pp.117-130
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    • 2014
  • The purpose of this study is to provide useful knowledge for improving indicators that represent competitiveness and educational competency of the university by deriving a new pattern or the meaningful results from the data of information disclosure of universities using statistical analysis and data mining techniques. To achieve this, a model of decision tree was made and various factors that affect education/research performance such as employment rate, the number of technology transfer and papers per full-time faculty were explored. In addition to this, the cluster analysis of universities was conducted using attributes related to evaluation of university. According to the analysis, common factors affecting higher education/research performance are following indicators ; incoming student recruitment rate, enrollment rate, and the number of students per full-time faculty. In the cluster analysis, when performed by the entire university, the size, location of the university respectively, clusters are mainly formed by well-known universities, art physical non-science and engineering religious leaders training universities, and others. The main influencing factors of this cluster are higher education/research performance indicators such as employment rate and the number of technology transfer.

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Towards a Deep Analysis of High School Students' Outcomes

  • Barila, Adina;Danubianu, Mirela;Paraschiv, Andrei Marcel
    • International Journal of Computer Science & Network Security
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    • v.21 no.6
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    • pp.71-76
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    • 2021
  • Education is one of the pillars of sustainable development. For this reason, the discovery of useful information in its process of adaptation to new challenges is treated with care. This paper aims to present the initiation of a process of exploring the data collected from the results obtained by Romanian students at the BBaccalaureate (the Romanian high school graduation) exam, through data mining methods, in order to try an in-depth analysis to find and remedy some of the causes that lead to unsatisfactory results. Specifically, a set of public data was collected from the website of the Ministry of Education, on which several classification methods were tested in order to find the most efficient modeling algorithm. It is the first time that this type of data is subjected to such interests.

Using Data Mining Techniques in Building a Model to Determine the Factors Affecting Academic Data for Undergraduate Students

  • Nafie, Faisal Mohammed;Hamed, Abdelmoneim Ali Mohamed
    • International Journal of Computer Science & Network Security
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    • v.21 no.4
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    • pp.306-312
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    • 2021
  • The main goal of higher education institutions is to present a high level of quality education to its students. This study uses data mining techniques to extract educational data from cumulative databases and used them to make the right decisions. This paper also aims to find the factors affecting students' academic performance in Majmaah University, KSA, during 2010 - 2017 period. The study utilized a sample of 6,158 students enrolled from two colleges, males and females. The results showed a high percentage of stumbling and dismissed between graduate and regular students where more than 62.5% failed to follow the plan. Only 2% of students scored distinction during their study of all graduated since their grade point average, secondary level, was statistically significant, where p<0.05. Dismissed percentage was higher among males. These results promoted some recommendations in which decision-makers could take them in considerations for better improvement of academic achievements: including of specialized programs to follow-up in regards to stumbling and failure. Utilization of different communication tools are needed to activate academic advisory for dismiss and dropout evaluation.

Education Data and Analytics: A Review of the State of the Art (교육 데이터와 분석 기법: 사례 연구를 중심으로)

  • Kwon, YoungOk
    • The Journal of Bigdata
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    • v.4 no.1
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    • pp.73-81
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    • 2019
  • With the increase of education data, there have been many studies on the application of various analytics to improve students' performance and educational environments over the past decade. This paper first introduces the cases of universities that successfully utilize the analysis results and, more specifically, examines which data and analytical techniques are used for each analysis purpose. Based on the findings, the limitations of the current analytics and the direction of future analysis are discussed.

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Study on Educational Utilization Methods of Big Data (빅데이터의 교육적 활용 방안 연구)

  • Lee, Youngseok;Cho, Jungwon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.12
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    • pp.716-722
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    • 2016
  • In the recent rapidly changing IT environment, the amount of smart digital data is growing exponentially. As a result, in many areas, utilizing big data research and development services and related technologies is becoming more popular. In SMART learning, big data is used by students, teachers, parents, etc., from a perspective of the potential for many. In this paper, we describe big data and can utilize it to identify scenarios. Big data, obtained through customized learning services that can take advantage of the scheme, is proposed. To analyze educational big data processing technology for this purpose, we designed a system for big data processing. Education services offer the measures necessary to take advantage of educational big data. These measures were implemented on a test platform that operates in a cloud-based operations section for a pilot training program that can be applied properly. Teachers try using it directly, and in the interest of business and education, a survey was conducted based on enjoyment, the tools, and users' feelings (e.g., tense, worried, confident). We analyzed the results to lay the groundwork for educational use of big data.

What Practical Knowledge Do Teachers Share on Blogs? An Analysis Using Text-mining

  • LEE, Dongkuk;KWON, Hyuksoo
    • Educational Technology International
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    • v.23 no.1
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    • pp.97-127
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    • 2022
  • With the recent advancement of technology, there has been an increase in professional development activities, including teachers using blogs to share practical knowledge and reflect on teaching and learning. This study was conducted to identify the contents of practical knowledge shared through the K-12 teachers' blogs. To achieve the research objective, 70,571 blog posts were collected from 329 blogs of K-12 teachers in Korean and analyzed using text mining techniques. The results of the study are as follows. First, practical knowledge sharing activities using teacher blogs have increased. Teachers posted a lot of blogs during the semester. Second, primary school teachers share various curriculum activities, reflections on project classes, class management, opinions related to education, and personal. Third, secondary school teachers share summaries and reviews of curriculum, materials related to college entrance exams, various instructional materials, opinions related to education, and personal experiences on their blogs. This study suggested that blogs are widely used as a venue for sharing practical knowledge of teachers, and that blogs can be a useful way to develop professionalism.

Tracing Students Performance by Intervention of the Academic Advisor

  • Mohamed, Abdelmoneim Ali;Nafie, Faisal Mohammed
    • International Journal of Computer Science & Network Security
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    • v.21 no.12spc
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    • pp.539-543
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    • 2021
  • Data mining technique was used to track student's performance during years studding in college and determine the impact of GPA_SEC on the GPA student rates according to the current academic advising method used on student's status. The study utilized a sample of 5436 individuals were drawn from two colleges in Majmaah University, KSA during 2013-2018 period. The results showed that the student's completion status in terms of graduation, dropout, Stumbling or dismissed was classified according to the average grades of admission from secondary school GPA_SEC. The results show the effect of the current academic advising that most of students gain less grades comparing with GPA_SEC in addition that the higher GPA_SEC was the higher graduation, dropout and dismissed decreased when GPA_SEC was high.. Therefore, the study recommends tracking students academically to evaluate their results of each semester to find out the causes of the deficiencies and addressing them within the departments.

An Analysis of Keywords on 'School Space Innovation' Policies using Text Mining - Focused on News Articles - (텍스트 마이닝을 활용한 '학교 공간 혁신' 정책 키워드 분석 - 뉴스 기사를 중심으로 -)

  • Lee, Dongkuk
    • The Journal of Sustainable Design and Educational Environment Research
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    • v.19 no.2
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    • pp.11-20
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    • 2020
  • The goal of this study was to investigate the implementation and related issues of the school space innovation issued by key Korean mass media using text mining. To accomplish this goal, this study collected 519 news articles associated with the school space innovation issued by 54 Korean mass media companies. Based on this data, this study performed the frequency analysis and network analysis regarding the keywords. Based on the findings, the characteristics of school space innovation are summarized as follows: First, school space innovation has progressed in response to future education. Second, users are actively participating in school space innovation. Third, experts are supporting the innovation of school space by establishing a cooperative system. Fourth, the community is actively considering the innovation of school space. Fifth, the main projects of the Ministry of Education and the Provincial Offices of Education are actively conducted in a mix of top-down and bottom-up approaches. The findings of this study will contribute to providing a clear direction for contemporary school space innovation and implications for future research agenda and implementation.