DFAM: A DISTRIBUTED FEEDBACK ANALYSIS MECHANISM FOR KNOWLEDGE BASED EDUCATIONAL BIG DATA

Authors

  • Rashidah F. Olanrewaju Department of Electrical & Computer Engineering, Kulliyyah of Engineering, International Islamic University, Malaysia
  • Burhan Ul Islam Khan Department of Electrical & Computer Engineering, Kulliyyah of Engineering, International Islamic University, Malaysia
  • Roohie Naaz Mir Department of Computer Science & Engineering, National Institute of Technology, Kashmir
  • Asifa Mehraj Baba Department of Electronics & Communication Engineering, Islamic University of Science and Technology, Kashmir
  • Farhat Anwar Department of Electrical & Computer Engineering, Kulliyyah of Engineering, International Islamic University, Malaysia

DOI:

https://doi.org/10.11113/jt.v78.10020

Keywords:

Big data, data analytics, data mining, educational data, knowledge discovery

Abstract

There is almost digitization of the entire educational system, as there is an abundant of digital materials available. The educational system is not left out from the global standardization as well as authorities are imposing certain standard at local and global level. As a result, these data which are getting generated in the context of educational also complies all the basic characteristics of the Big Data such as volume in terms of size, and others velocity, variety etc. In order to store, search and process an open source project, Apache Hadoop has been conceptualized, whereas it lags the application specific needs especially in the field of education to enhance the teaching and learning processes. In this paper, an architectural model is illustrated to demonstrate the existing eco-system and a proposed model for provisioning the enhanced teaching -learning mechanism, so that it can be adopted to enhance the intelligence into mechanism of educational framework.

References

Devadass, R., L. Haldurai., G. Vidya, R. Gokilavani, and T. Madhubala. 2015. Data Visualization Techniques on Partially Purified Plant Extracts against Aedes aegypti (Culicidae: Diptera). IJARCSSE, 5(1)

Domenico, T. 2011. Cloud Computing and Software Agents: Towards Cloud Intelligent Services. In WOA. 11: 2-6

Kim, S., S. Su-Mi, and Y. Yong-Ik. 2011. Smart Learning Services Based on Smart Cloud Computing. Sensors, 11 (8): 7835-7850

Nir, K. 2010. Cloud Computing in Developing Economies. Institute of Electrical and Electronics Engineers Computer. 43(10): 47-55

Rani, U. 2013. Effective Ways Cloud Computing can Contribute to Education Success. Advanced Computing. 4(4)

Macfadyen, L.P., D. Shane, P. Abelardo, and G. Dragan. 2014. Embracing Big Data in Complex Educational Systems: The Learning Analytics Imperative and the Policy Challenge. Research & Practice in Assessment. 9(2): 17-28

Tulasi, B. 2013. Significance of Big Data and Analytics in Higher Education. International Journal of Computer Applications. 68(14)

Paul, P., A. Felician, and V. Marius. 2009. Using Cloud Computing for E-Learning Systems. In Proceedings of the 8th WSEAS International Conference on Data Networks, Communications, Computers (Dncoco'09). 7-9

Ahmed, A., M.E. Hazem, M., E-Razek, M.A. Samir, E. Yehia, and M. Nikos. 2014. Enhancing Big Data Processing in Educational Systems. Research & Practice in Assessment. 17-28

Sultan, N. 2010. Cloud Computing for Education: A New Dawn. International Journal of Information Management. 30(2): 109-116

Drigas, A.S., and L. Panagiotis. 2014. The Use of Big Data in Education. International Journal of Computer Science Issues (IJCSI). 11(5): 58.

Nasr, M. and S. Ouf. 2011. An Ecosystem in E-Learning using Cloud Computing as Platform and Web2.0, The Research Bulletin of Jordan ACM 2.134-140.

Pratiba, D., and G. Shobha. 2014. Educational Big Data Mining Approach in Cloud: Reviewing the Trend. International Journal of Computer Applications. 92(13): 43-50

Gutierrez-Carreon, G., T. Daradoumis and J. Jorba. 2015. Integrating Learning Services in the Cloud: An Approach that Benefits Both Systems and Learning. Journal of Educational Technology & Society. 18(1): 145-157

Fardoun, H.B., S. R. Lopez, D. M. Alghazzawi, and J. R. Castillo. 2012. Education System in the Cloud to Improve Student Communication in the Institutes of: C-Learni XML. Procedia-Social and Behavioral Sciences. 47:1762-1769

Dong, B., Q. Zheng, J. Yang, H. Li, and M. Qiao. 2009. An E-Learning Ecosystem Based on Cloud Computing Infrastructure. In Advanced Learning Technologies, ICALT, Ninth IEEE International Conference. 125-127

Masud, M.A.H. and X. Huang. 2012. An E-Learning System Architecture Based on Cloud Computing. System, 10(11)

Fernandez, A., D. Peralta, F. Herrera, and J. M. Benítez, 2012. An Overview of E-Learning in Cloud Computing. In Workshop on Learning Technology for Education in Cloud (LTEC'12), Springer Berlin Heidelberg. 35-46

Nuzzo, A., C. Fuchsberger, and R. Bellazzi. Retrieved, 10th Oct, 2015. Data Mining Approaches to Forecast Molecular Phenotypes from SNPs Data.

Chen, H., R.H.L. Chiang, and V.C. Storey. 2012. Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly/. 36(4): 1165-1188.

Goebel, M., and L. Gruenwald 1999. A Survey of Data Mining and Knowledge Discovery Software Tools. ACM SIGKDD Explorations Newsletter. 1(1): 20-33.

Aghabozorgi, S., H. Mahroeian, A. Dutt, T.Y. Wah, and T. Herawan. 2014. An Approachable Analytical Study on Big Educational Data Mining. In Computational Science and Its Applications–ICCSA. Springer International Publishing. 721-737

Ngo, L.B., P. Xuan, K. Ferguson, C. Marshall, J. McCann, Y. Zheng, and A.W. Apon 2012. An Infrastructure to Support Data Integration and Curation for Higher Educational Research. In Proc. 8th IEEE International Conference on e-Science, Chicago. 8-12

Daniel, B. 2015. Big Data and Analytics in Higher Education: Opportunities and Challenges. British Journal of Educational Technology. 46(5): 904-920.

Moniruzzaman, A.B.M., and S.A. Hossain. 2013. Nosql Database: New Era of Databases for Big Data Analytics-Classification, Characteristics and Comparison. arXiv preprint arXiv:1307-0191

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Published

2016-12-15

How to Cite

DFAM: A DISTRIBUTED FEEDBACK ANALYSIS MECHANISM FOR KNOWLEDGE BASED EDUCATIONAL BIG DATA. (2016). Jurnal Teknologi (Sciences & Engineering), 78(12-3). https://doi.org/10.11113/jt.v78.10020