• Journal of Korean Library and Information Science Society
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• v.47 no.1
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• pp.243-277
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• 2016

This study aimed at analyzing the influence factors of the academic library on college's education and research performances. The researched subject was 144 colleges targeted for information disclosure by Center for Higher Education Information Disclosure. The conclusion of the present study is as follows. First, the educational performance in college showed the positive relation with 'library environment' variables except 'seating capacity per capita'. Second, the educational performance in college was positively related to the variable of 'library outcome' and particularly, it was directly influenced by circulation, visit, and interlibrary loan. Third, the research performance in college showed a positive correlation with 'library environment' variables except facility scale of library. Fourth, the research performance in college showed a positive relation with the variable of 'library outcome' and research performance excluding 'publication in domestic journals per capita' was positively influenced by 'document delivery services usage per capita' and 'commercial DB usage per capita' in common.

• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.47-53
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• 2017

The university must open the "School Development Plan and Specialization Plan" at the university allimi. The reason for this is the Special Act on the Disclosure of Information by Educational Institutions, enacted on May 25, 2007, and the Plan for Reform of University Reform announced by the Ministry of Education on Mar 28, 2014. Therefore, we examined the similarity and standardized model of the "School Development Plan and Specialization Plan" published by a total of 137 colleges. As a result of the study, only 17(12.4%) of the college produced information in two ways(school development and specialization), and the rest were not. The school development plan presented quantitative indicators such as world number one, The characterization plan presented qualitative indicators such as human. Based on this, standardized research procedures and conception are presented.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.29 no.2
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• pp.169-197
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• 2018

The research aims to analyze current university information disclosure services in the perspectives of both university records management and services and to recommend ways to improve the current university information disclosure systems and services. The research collects and analyzes various raw data such as laws, guidelines, and manuals of university information disclosure services and the portal site of 'Higher Education in Korea' also known as 'dae-hak-al-ri-mi', and data on each homepage of 40 cooperative universities selected as the research sample. At the result, the research found some limits in the current operation of university information disclosure services: first, the information posted on the university disclosure information system is mostly focused on administrative information rather than information related to research or education within universities. Second, there are the high rate of error and frequent modification in the information posted on the disclosure information system. Third, the menus on both the information disclosure system and homepages of each cooperative university are useless or contents of the menus are empty. The research suggests some solutions to improve these problems: it is required to make up the current legal systems for university information disclosure services and to cooperate all organizations and universities related to university information disclosure services within the united system and rule. Also, it is crucial to attach the metadata of the disclosed information when to post the information to the university disclosure information systems. Finally, it is necessary for each university to employ archivists not only to develop qualified university records to maintain the unique roles and value of universities but also to disclose reliable and authentic information to users and manage the university information disclosure systems effectively and efficiently.

• Korean small business review
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• v.42 no.4
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• pp.285-308
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• 2020

This paper analyzes the factors which affect University professors and students on their startup activities, such as (a) University factors: their industrial cooperation organization and systems, their resources for startup support, their knowledge assets, and (b) socioeconomic characteristics in which Universities are located. We used the data and information from the University Information System and the National Statistical Office Publication to analyze 157 4-year Universities in Korea who uploaded their startup-related information on the system. Our analysis shows that Universities' systems, such as the term for Professors' leave of absence for startup activities, and their amount of knowledge assets affect the number of Professor startups significantly positively, while there is no significant effect on their performance, in terms of sales, from those factors, except for the amount of patents that the University has. In the meantime, the number of practical startup courses, the number of startup clubs, and the number of professor startups in the University affect the number of student startups, while the size of industrial cooperation body, the amount of knowledge asset, the area's socioeconomic characteristics didn't affect their performance. The result implies that we need to take different approaches to boost University professor startups and their student startups: better system and more knowledge for the former, more practical courses and programs for the latter. Further study is needed to get a more robust result because this analysis used only one year data, and personal trait data was not included in the analysis. A panel data analysis for several years is recommended for further research.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.187-193
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• 2020

In this study, we wanted to analyze the factors at the national university level that affect college students ' elimination. In addition, national universities, private universities, universities in Seoul and universities outside of Seoul were divided into more college-specific characteristics. Except for leave of absence and departure from school, it was defined as a middle school dropout among changes of students. The data were used for analysis by receiving raw data from "University Alerts," which are operated by the Ministry of Education and the Korean Council for Educational Universities. At the university notification, 222 universities out of the schools classified as "Universities" were utilized for final analysis, and jobs, credits, scholarships, tuition fees, students, independent students, and full-time teachers were secured through multiple education. Overall, the higher the average graduate level and employee-rate the lower the rate of elimination from the middle of college students, the analysis showed. Second, the higher the average tuition fees at private universities, the more negatively affects the rate of elimination of university students. Third, higher tuition fees at universities outside the Seoul metropolitan area have a negative impact on the rate of elimination of students.

• 한국벤처창업학회:학술대회논문집
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• 2018.04a
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• pp.123-125
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• 2018

본 연구는 우리나라 대학의 창업교육센터(Entrepreneurship Education Center)에 대한 조사를 수행하여 선행 조사DB와 비교 분석하였다. 창업교육센터 실태조사를 바탕으로 대학별 정량적 정성적 지표를 측정하여 상위그룹과 하위그룹의 구분하고 두 집단의 차이점과 성공운영 요인을 분석하였다. 창업교육센터의 일반 현황과 특성, 교직원(교수자수, 교원창업자수), 교과목(과목, 수강인 원수), 학내외 프로그램(창업동아리, 창업경진대회, 창업캠프), 재정운영(예산, 전담인력) 등의 계량 지표는 대학정보공시(대학 알리미)와 중앙일보 대학평가 DB를 기초하여 조사하였다. 그리고 운영상의 문제점, 센터의 성과측정 항목 등 정성지표는 창업교육센터장을 대상으로 설문 조사하였다. 또한, 국내 창업교육센터의 표본특성을 살펴본 후 상위그룹과 하위그룹의 차이를 규명하여 상위그룹이 보유하고 있는 인적 물적 역량과 프로그램의 분석하여 창업교육센터의 활성화 방안을 제시하였다. 본 연구는 교육부의 "산학협력 선도대학(LINC) 육성사업 (2012년~2106년)"에서 창업교육을 총괄 지원하기 위해 2012년 대학에 설치된 전담조직인 61개 창업교육센터의 성과를 분석하고 대학평가에서 상위 순위에 있는 대학 그룹들의 차이점을 도출하는데 의미가 있다. 또한 2017년에 새롭게 지정된 LINC+ 사업 ('17년~) 창업교육 분야의 정책적 시사점을 제시한다. 본 연구의 목적을 달성하기 위해 문헌연구와 창업교육센터 운영에 대한 구조적 설문지를 개발하여 실태를 분석하였다. 이 결과는 창업교육센터의 효율적 운영을 위해 대학교직원 연구자 공무원 학생 및 창업교육센터를 포함한 창업지원 기관의 이해 관계자에게 향후의 발전을 위한 자료로써 의미가 있을 것이다.

• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.2
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• pp.150-157
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• 2012

This study examined the differences in research capability among engineering fields using the data of research support organizations involving National Research Foundation of Korea(NRF), SCI Korean Council for University Education (KCUE) and so on. The findings of the study confirm that there are statistically significant differences in research capability among selected engineering fields, and provide implications for university administrators and academic policy-makers to adopt discriminative evaluation tools for performance evaluation of university faculties in consideration of their engineering fields.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.457-465
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• 2012

The purpose of this study is to analyze the association between indicators and to find statistical models based on important indicators at 'College Notifier' in Korea Council for University Education. First, Pearson correlation coefficients are used to find statistically significant correlations. By variable selection method, the important indicators are selected and their coefficients are estimated. As variable selection method, backward and stepwise methods are employed.

• Journal of Korea Technology Innovation Society
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• v.20 no.3
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• pp.642-663
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• 2017

The purpose of this study is to investigate the factors that affect professor startups and their performances in Universities in Korea. We included 5 categories of factors: University's size and reputation, University's technology commercialization staff number and startup deregulation, University's resources for research and technology commercialization, University's patents and professors' publication, and student startups. We analyzed 150 Universities, using Korean government's Academyinfo database, and additional data for University ranking and government's projects for University startups. Our analysis shows that Universities' fund amount for research and technology commercialization, Universities' amount of patents give a positive impact on Universities statistically significantly, while Universities' size or reputation does not. In addition, the amount of patents and startup projects funded by the government give a significantly positive impact on the annual sales of the professor startups. Furthermore, student startups are in a positive relationship with professor startups and their sales, showing a synergy effect between the two startup groups in Universities. The result implies that Universities and government need to focus on supporting patenting activities, providing technology commercialization funds, and collaboration activities between professors and students for their startup activities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.471-479
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• 2018

This research examines the sustainable mutual growth of academia and industry regarding human resource cultivation and recruitment of local communities. at the beginning of regularized survival competitions and university innovations according to University Basic Competence Evaluations and etc., This research considers the substantive effect of educational resources of universities on recruitment rates in the pursuit of enhancing university-industry cooperation. Therefore, to identify factors of recruitment rates, we employ a university-wise index based on a quantitative index of educational resources of universities. Regarding study methods, set-up and verification of hypothesis, empirical analysis, descriptive statistics analysis, and correlation analysis are used to identify the correlation between dependent variables and independent variables based on the three sub-indexes of open records at Higher Education including educational environments, educational finances, and research achievements. Implications were derived from multiple regression analysis results regarding education conditions and recruitment rates, educational finances and recruitment rates, and research achievement and recruitment rates. This research can be extended to predict regional university recruitment rates with empirical analysis considering regional characteristics.