1. BIG DATA: BUILDING AND DISSEMINATING RESEARCH IN HIGHER EDUCATION

2. WHAT IS BIG DATA?

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

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

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

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

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

8. 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

9. 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

10. 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.

11. 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

12. 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

13. 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

14. 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.