AIRCC's International Journal of Computer Science and Information Technology

Open Access Open Access  Restricted Access Subscription Access

Developing an Integrated Framework to Utilize Big Data for Higher Education Institutions in Saudi Arabia


Affiliations
1 Information Management Department, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia
 

In recent years, there has been widespread use of the Internet, the Internet of things, mobile devices, networks, and applications. All this usage produces daily huge data that cannot be processed using existing database management techniques and tools because of the size, the volume, the heterogeneity, and the unstructured nature of the data. This has led many sectors like healthcare, business, education, and so forth to start using Big Data technologies to analyze, process, decision making and performance. Big Data is “datasets which could not be captured, managed, and processed by general computers within an acceptable scope” [1].Education sectors are one of the most important sectors that use information and communication technology (ICT).However, the education sector in Saudi Arabia is still behind other developed countries in terms of the adopting and implementation of Big Data techniques. The aim of this study is to develop an integrated framework to utilize Big Data for higher educational institutes in Saudi Arabia and to support decision making and improve performance. While many studies look at data mining and Big Data in the education sector, there are few studies that touch on this issue in Saudi education, especially in universities. The study collected data through self-administered surveys as a principal quantitative method and through semi structured in depth interviews as the follow-up qualitative method. The study used SPSS software to analyze the data from surveys and used manual analysis to analyze the interview data. This study’s major contribution addresses issues related to the development of a research framework that presents factors affecting the adoption and implementation of Big Data.

Keywords

Big Data, Education, Data Mining, Saudi Arabia, Riyadh, Factors, Adoption.
User
Notifications
Font Size

  • Singh, M. and Kumar G, D. Effective Big DataManagement andOpportunities for Implementation. United States of America by:Information Science Reference, N.d.

  • G. Picciano, ―The evolution of Big Dataand learning analytics in American higher education,” Journal of Asynchronous Learning Networks, vol. 16, pp. 9-20, 2012.

  • T. Poleto, V. D. H. De Carvalho, and A. P. C. Seixas Costa, Theroles of Big Datain the decisionsupport process: An empiricalinvestigation,” Lecture Notes in Business, pp. 10-21, 2015.

  • Mukthar and M. Sultan, ―Big Dataanalytics for higher education inSaudi Arabia,” International Journal Of Computer Science AndInformation Security, vol. 15, no. 6, pp. 3–22, 2017.

  • Deepa and E. C. Blessie, ―Big Dataanalytics for accreditation inthe higher education sector,” International Journal of ComputerScience and Information Technologies, vol. 8, no. 3, pp. 357– 360,2017.

  • Hussain and M. Safdar, ―Role of information technologies inteaching learning process: perception of the faculty,” Turkish OnlineJournal of Distance Education-TOJDE, vol. X, pp. 46–56, April2008.

  • F. Hamidi, M. Meshkat, M. Rezaee, and M. Jafari, Informationtechnology in education,” In Procedia Computer Science (Vol. 3),Netherlands: Elsevier Ltd, 2011.

  • Ryann K. Ellis, A Field Guide to Learning Management Systems.American Society for Training and Development (ASTD), 2009.

  • Letouzé, ―United Nations Global Pulse,ǁ Unglobalpulse.org, BigData for Development: Opportunities & Challenges, 2012.

  • W. Pan, Q. Yang, C. Aggarwal, and C. Koch, ―Big Data,” IEEEIntelligent Systems, vol. 32, no. 2, pp. 7–8, 2017. doi: 10.1109/mis.2017.32.

  • P. Zikopoulos, C. Eaton, D. deRoos, T. Deutsch, and G. Lapis,Understanding Big DataAnalytics for Enterprise Class Hadoop andStreaming Data, New York: McGraw-Hill, 2011.

  • L. Hbibi and H. Barka, Big data: Framework and issues. In 2016 International Conference on Electrical and Information Technologies (ICEIT) pp. 485–490, 2016.

  • S. Petter, W. DeLone, and E. McLean, ―Measuring information systems success: Models, dimensions, measures, and interrelationships.” European Journal of Information Systems, vol. 17, no. 3, pp. 236–263, 2008.

  • T. Oliveira and M. Martins, ―Literature review of information technology adoption models at firm level,” Electronic Journal of Information, vol. 14, no. 1, pp. 110–121, 2011.

  • L. Tornatzky, M. Fleischer, and A. Chakrabarti, ―The Processes of Technological Innovation,ǁ Lexington, Mass.: Lexington, 1990.

  • Drigas, and P. Leliopoulos, ―The use of Big Datain education,”International Journal of Computer Science Issues, vol. 11 no. 5, pp. 58–63, 2014.

  • B. Tulasi and R. Suchithra, ―Big Dataanalytics and E learning in higher education,” International Journal on Cybernetics & Informatics, vol. 5, no. 1, pp. 81–85, 2016. doi: 10.5121/ijci.2016.5108

  • B. Daniel, (2014). ―Big Dataand analytics in higher education: Opportunities and challenges,” British Journal of Educational Technology, vol. 46, pp. 1–10, 2014.

  • M. Saunders, P. Lewis, and A. Thornhill, Research Methods for Business Students, Harlow: Financial Times Prentice Hall, 2012.

  • V. Sarala, and J. Krishnaiah, ―Empirical Study Of Data Mining Techniques In Education System,” International Journal of Advances in Computer Science and Technology (IJACST), vol.4, pp. 15– 21,2015.

  • P. Veeramuthu, D. R. Periyasamy, and V. Sugasini, Analysis ofStudent Result Using Clustering Techniques,”International Journalof Computer Science and Information Technologies, pp. 5092– 5094, 2014.

  • S. Suganya and V. Narayani, ―Analysis of students dropoutforecasting using data mining,” In 3rd International Conference onLastest Trends in Engineering, Science, Humanities andManagement, 2017.


Abstract Views: 277

PDF Views: 181




  • Developing an Integrated Framework to Utilize Big Data for Higher Education Institutions in Saudi Arabia

Abstract Views: 277  |  PDF Views: 181

Authors

Noura A. Alsheikh
Information Management Department, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia

Abstract


In recent years, there has been widespread use of the Internet, the Internet of things, mobile devices, networks, and applications. All this usage produces daily huge data that cannot be processed using existing database management techniques and tools because of the size, the volume, the heterogeneity, and the unstructured nature of the data. This has led many sectors like healthcare, business, education, and so forth to start using Big Data technologies to analyze, process, decision making and performance. Big Data is “datasets which could not be captured, managed, and processed by general computers within an acceptable scope” [1].Education sectors are one of the most important sectors that use information and communication technology (ICT).However, the education sector in Saudi Arabia is still behind other developed countries in terms of the adopting and implementation of Big Data techniques. The aim of this study is to develop an integrated framework to utilize Big Data for higher educational institutes in Saudi Arabia and to support decision making and improve performance. While many studies look at data mining and Big Data in the education sector, there are few studies that touch on this issue in Saudi education, especially in universities. The study collected data through self-administered surveys as a principal quantitative method and through semi structured in depth interviews as the follow-up qualitative method. The study used SPSS software to analyze the data from surveys and used manual analysis to analyze the interview data. This study’s major contribution addresses issues related to the development of a research framework that presents factors affecting the adoption and implementation of Big Data.

Keywords


Big Data, Education, Data Mining, Saudi Arabia, Riyadh, Factors, Adoption.

References