BIG DATA: BUILDING AND DISSEMINATING RESEARCH IN HIGHER EDUCATION

WHAT IS BIG DATA?

“Big data refers to large growing data sets with heterogeneous format which requires advanced technology and algorithm in order to access it”

BIG DATA BASIC CHARACTERISTICS Volume BIG DATA BASIC CHARACTERISTICS (3Vs) Velocity Variety

VOLUME VALUE VELOCITY BIG DATA Key VARIETY VERACITY Characteriztics VERIFICATION VARIETY VERACITY

BIG DATA APPLICATIONS Smart Grid E-health Internet of Things Public Utilities Transportation and Logistics Education

BIG DATA FOR HIGHER EDUCATION Building and Disseminating Research FORCASTING A NEW PLATFORM TEACHING METHODOLOGY Research Exchange

EDUCATION FORCASTING The core of big data is forecast, which applies mathematical algorithm to predict the likelihood of things happening. This technology can also be used to predict the enrollment, employment, students’ demand and the future development of colleges and universities

A new platform for education New platforms could transfer all-kinds of education. As an example, online education has been grown whether by companies or universities. For instance, the famous online education company courses has reached an agreement with more than 30 universities worldwide such as Princeton, Berkeley, Duke, Hong Kong Institute of Technology, it provides courses for free through these platforms

A new Teaching Mode In the era of big data, the way for learners to acquire knowledge is no longer the classroom, online study is becoming a major way for learning. On the Internet, learners have access to the world’s best courses which are better than the courses that are offered by any single university.

Promoting the exchange of research and innovation : Disseminating Researches Big data could be utilized as a tool to: Raise information in the form of “library” Provide communication between researchers, scholars, institutions and experts

Promoting the exchange of research and innovation Education data mining Education data mining analyses data collected in the process of teaching and learning by statistics, machine learning and data mining technology to inspect on study theories and guide education practice 2. Learning analysis Learning analysis analyses data collected in the process of education management and service by information science, sociology, psychology, statistics, machine learning and data mining technology to directly influence the education practice with its applying program

1 2 3 4 5 6 7 BIG DATA CHALLENGES Big Data Management Big Data Cleaning 2 Big Data Aggregation 3 Imbalance System Capacity 4 Big Data Imbalance 5 Big Data Analytics 6 Big Data Machine Learning 7 BIG DATA CHALLENGES

References [1] L. Meng, “Application of Big Data in Higher Education,” no. Ictcs, pp. 1–2, 2014. [2] B. K. Daniel, “Big Data in Higher Education : The Big Picture,” no. May, 2018. [3] A. Oussous, F. Benjelloun, A. Ait, and S. Belfkih, “Big Data technologies : A survey,” J. King Saud Univ. - Comput. Inf. Sci., vol. 30, no. 4, pp. 431–448, 2018. [4] Y. Li, X. Zhai, Y. Li, and X. Zhai, “Review and Prospect of Modern Education using Big Data Review and Prospect of Modern Education using Big Data,” PROCEDIA-COMPUTER Sci., vol. 00, no. 129, pp. 341–347, 2018. [5] H. Aldowah, H. Al-samarraie, and W. M. Fauzy, “Educational Data Mining and Learning Analytics for 21stcentury higher education: A Review and Synthesis,” Telemat. Informatics, 2019.