Big Data and analytics in higher education: Opportunities and challenges

2014 ◽  
Vol 46 (5) ◽  
pp. 904-920 ◽  
Author(s):  
Ben Daniel
Keyword(s):  
Higher Education ◽  
Big Data

scholarly journals A News Big Data Analysis of Issues in Higher Education in Korea amid the COVID-19 Pandemic

2021 ◽  
Vol 13 (13) ◽  
pp. 7347
Author(s):  
Jangwan Ko ◽  
Seungsu Paek ◽  
Seoyoon Park ◽  
Jiwoo Park
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analysis ◽  
College Education ◽  
Big Data Analysis ◽  
Second Phase ◽  
Public Attention ◽  
Job Market ◽  
Media Reports ◽  
The Government

This paper examines the main issues regarding higher education in Korea—where college education experienced minimal interruptions—during the COVID-19 pandemic through a big data analysis of news articles. By analyzing policy responses from the government and colleges and examining prominent discourses on higher education, it provides a context for discussing the implications of COVID-19 on education policy and what the post-pandemic era would bring. To this end, we utilized BIgKinds, a big data research solution for news articles offered by the Korea Press Foundation, to select a total of 2636 media reports and conducted Topic Modelling based on LDA algorithms using NetMiner. The analyses are split into three distinct periods of COVID-19 spread in the country. Some notable topics from the first phase are remote class, tuition refund, returning Chinese international students, and normalization of college education. Preparations for the College Scholastic Ability Test (CSAT), contact and contactless classes, preparations for early admissions, and supporting job market candidates are extracted for the second phase. For the third phase, the extracted topics include CSAT and college-specific exams, quarantine on campus, social relations on campus, and support for job market candidates. The results confirmed widespread public attention to the relevant issues but also showed empirically that the measures taken by the government and college administrations to combat COVID-19 had limited visibility among media reports. It is important to note that timely and appropriate responses from the government and colleges have enabled continuation of higher education in some capacity during the pandemic. In addition to the media’s role in reporting issues of public interest, there is also a need for continued research and discussion on higher education amid COVID-19 to help effect actual results from various policy efforts.

scholarly journals Design on Big data Platform-based in Higher Education Institute

2020 ◽  
Vol 10 (4) ◽  
pp. 36
Author(s):  
Sajeewan Pratsri ◽  
Prachyanun Nilsook
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analysis ◽  
Digital Media ◽  
Data Storage ◽  
Security And Privacy ◽  
Digital Learning ◽  
Learning Platform ◽  
Data Platform ◽  
Tools And Techniques

According to a continuously increasing amount of information in all aspects whether the sources are retrieved from an internal or external organization, a platform should be provided for the automation of whole processes in the collection, storage, and processing of Big Data. The tool for creating Big Data is a Big Data challenge. Furthermore, the security and privacy of Big Data and Big Data analysis in organizations, government agencies, and educational institutions also have an impact on the aspect of designing a Big Data platform for higher education institute (HEi). It is a digital learning platform that is an online instruction and the use of digital media for educational reform including a module provides information on functions of various modules between computers and humans. 1) Big Data architecture is a framework for an architecture of numerous data which consisting of Big Data Infrastructure (BDI), Data Storage (Cloud-based), processing of a computer system that uses all parts of computer resources for optimal efficiency (High-Performance Computing: HPC), a network system to detect the target device network. Thereafter, according to Hadoop’s tools and techniques, when Big Data was introduced with Hadoop's tools and techniques, the benefits of the Big Data platform would provide desired data analysis by retrieving existing information, to illustrate, student information and teaching information that is large amounts of information to adopt for accurate forecasting.

scholarly journals Uncovering Trend-based Research Insights on Teaching & Learning in Big Data

2020 ◽  
Author(s):  
Young-Eun Park
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Teaching And Learning ◽  
Learning Algorithm ◽  
Semantic Network ◽  
Academic Leaders ◽  
Student Centered ◽  
Diverse Learning ◽  
Quality Programs ◽  
Future Education

Abstract Along with the occurrence of the big data era, digital transformation has had a transformative effect on modern education tremendously in higher education. It transforms an institutional core value of education to better meet students' needs by leveraging big data and digital technology. Based on this background, this study attempts to catch the principal trends, or new directions, paradigms as predictors with an association of each topic by discovering the up-to-date research trends on teaching and learning in higher education via text mining technique. For this, 285 research articles in the area of teaching and learning in higher education were collected from several big databases (distinguishable publishers' web platforms) through search engines for two years in 2018 ~ 2019. Then it was analyzed using a semantic network analysis that processes natural human language. In consequence, research results show a relatively high connection with 'student' or 'student-centered/led' rather than 'teacher-led.' Moreover, it exhibits that the practice and assessment in learning can be attained via diverse learning activities, containing community or outreach activities. Besides, research in academic contexts, experience-based classes, the effect of group activities, how students' feelings or perceptions, and relationships affect learning outcomes were addressed as the main topics through topic modeling of LDA, a machine learning algorithm. This study proposes that educators, researchers, and even academic leaders can exert the extraordinary power to reshape educational quality programs for future education and in a timely manner with recognizable trends or agendas in teaching and learning of higher education.

Sign in / Sign up

Export Citation Format

Share Document