A Study on the Application of Big Data to the Korean College Education System

Kim, Yeon Hee; Ahn, Jin-Ho

doi:10.1016/j.procs.2016.07.096

Cited by 20 publications

(6 citation statements)

References 2 publications

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“…The education sector is one of which generates more data, and this is because the internet is a fundamental tool for students, necessary for their learning (Hao et al, 2018). The result of the analysis of data on student academic achievement can present the future career, area of interest, and educational curriculum for a specific student, and can provide individualized learning given the fact that it individually provides learning methods and personalized information (Kim & Ahn, 2016).…”

Section: Adoption Of Big Datamentioning

confidence: 99%

Smart University: a vision of technology adoption

Bautista

Guerrero

Collázos

et al. 2021

Rev. colomb. comput.

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Smart University is an emerging concept, strongly anchored to smart technologies and considered by different authors in the literature. Organizations, including universities, need to incorporate smart technologies to take advantage of their capabilities to transform their processes and drive them toward new organizational models. A Smart University focuses on improving its technological infrastructure for achieving its quality educational goals. This paper presents the integration of the key factors for adopting four smart technologies: Cloud Computing, Big Data, Artificial Intelligence, and the Internet of Things. This characterization and integration allow us to conclude on the need to align digital technologies with the organization's processes, requiring greater interaction with the company’s senior management.

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Section: Adoption Of Big Datamentioning

confidence: 99%

Smart University: a vision of technology adoption

Bautista

Guerrero

Collázos

et al. 2021

Rev. colomb. comput.

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“…Besides, with the rapid development of modern science and technology, various emerging intelligent technologies such as virtual reality technology, network technology, information technology, and big data technology, etc. have begun to be applied in higher education [15][16][17][18], providing many new methods and means for knowledge acquisition of graduate students. The reasonable application of these methods and means will greatly improve the efficiency and quality of graduate students' knowledge acquisition, thereby enhancing their knowledge innovation ability.…”

Section: Knowledge Acquisition Of Graduate Studentsmentioning

confidence: 99%

Influence of Teacher-Student Matching on Knowledge Innovation of Graduate Students

Jin-gui¹,

Yanming²

2020

Int. J. Emerg. Technol. Learn.

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The teacher-student (T-S) matching in colleges has not been studied in a thorough and systematic manner. It remains unclear how college T-S matching affects the knowledge innovation of graduate students. Therefore, this paper firstly analyzes the factors affecting the knowledge innovation of graduate students, and selects the T-S matching mode that promotes their knowledge innovation. Then, the promotion of knowledge innovation was investigated under the T-S matching. Finally, the authors quantified the importance of knowledge innovation among graduate students, and summarized the strategies and methods for cultivating innovation ability based on T-S matching. The research results provide a panoramic view of the cultivation of innovation ability among graduate students from the angle of T-S matching.

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“…Since the availability of large quantities of data generated from several types of educational frameworks, the necessity to analyze such data to obtain insights is growing. Analysis of these types of data requires special techniques for efficient processing that are more suitable for big data techniques [76]. Big data solutions can produce fantastic results and offer innovative data-driven approaches for student learning.…”

Section: Educationmentioning

confidence: 99%

Big Data: Analytical Solutions, Research Challenges and Trends

Ali¹,

Novikov²

2020

Proceedings of ISP RAS

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The term Big Data refers to an extensive collections of digital data generating every second. Produced datasets come in structured, semi-structured, and unstructured formats throughout the world, which is difficult for the traditional database management systems to analyze. Recently, big data analytics emerges as an essential research area due to the popularity of the Internet and the advent of new Web technologies. This growing area of research represents a multidisciplinary that attracts researchers from various research fields. Interested researchers are invited to design, develop, and implement several tools, technologies, architecture, and platforms for analyzing these large volumes of data. This paper begins with a brief introduction to big data and related concepts, including the main characteristics of big data, followed by discussions of the most significant open research challenges and emerging trends. Next, we review a study of big data analytics, the advantages of using big data solutions, and the preliminary assessments required before migrating from traditional solutions. Finally, we present a review of the recent main applications to obtain a broad perspective of big data analytics.

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A Study on the Application of Big Data to the Korean College Education System

Cited by 20 publications

References 2 publications

Smart University: a vision of technology adoption

Smart University: a vision of technology adoption

Influence of Teacher-Student Matching on Knowledge Innovation of Graduate Students

Big Data: Analytical Solutions, Research Challenges and Trends

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