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Big Data Assignment: Reforms in the Education System Using IT

s The research questions are presented to state the specific issue or problems related to the topic. The following research questions demonstrate exactly what is discussed so far. How big data with technological development is bringing changes? What is the importance of big data in academics? How hard it is to implement big data in academic institutions? What are the key challenges of implementing big data? What are the resources needed to implement big data in academics for educational reform? Hypothesis Hypothesis 1: Big Data can bring a lot of changes and reforms into the academics Hypothesis 2: Greater challenges is associated with implementing big data. What are the assumptions made on this research on big data assignment? Assumptions are what is assumed to be true and assumptions can be risky in terms of big data (Williamson, 2017). Some of the key assumptions that are taken as true are listed below: The availability of the needful resources An easy and nonchalant complicated process Unanimous Privacy policies Strong security systems These above-mentioned assumptions are the core points that everyone wishes to be true since only then the big data technology can be implemented all over the globe that will lead to better educational performance. Conclusion The research paper developed in this big data assignment has demonstrated big data technology and its impact on the educational system in the technologically driven world. The paper has reflected the significant importance in educational institutions and identified the factors that act as a barrier for implementing big data in academic institutions. The paper made a literary review on the key reforms that the big data could bring starting from digital learning to quick data processing. The paper also demonstrated some key research questions and research problems relevant to the topic and also outlined the key aims and objectives of this research. The paper concluded by discussing the hypothesis and listed some key assumptions that are important to be true for making the project successful. References List He, Z., He, Y., Liu, F. and Zhao, Y., (2019). Big data-oriented product infant failure intelligent root cause identification using associated tree and fuzzy DEA. IEEE Access, 7, pp.34687-34698. Huda, M., Anshari, M., Almunawar, M.N., Shahrill, M., Tan, A., Jaidin, J.H., Daud, S. and Masri, M., (2016). Big data assignment Innovative teaching in higher education: the big data approach. TOJET. Huda, M., Maseleno, A., Shahrill, M., Jasmi, K.A., Mustari, I. and Basiron, B., (2017). Exploring adaptive teaching competencies in big data era. International Journal of Emerging Technologies in Learning (iJET), 12(03), pp.68-83. Lei, W., (2018). The Path Analysis of Modern Educational Technology Promoting Education Development under the Background of Big Data. Mikalef, P., Pappas, I.O., Krogstie, J. and Giannakos, M., (2018). Big data analytics capabilities: a systematic literature review and research agenda. Information Systems and e-Business Management, 16(3), pp.547-578. Mourtzis, D., Vlachou, E. and Milas, N.J.P.C., (2016). Industrial Big Data as a result of IoT adoption in manufacturing. Procedia cirp, 55, pp.290-295. Nalini, C. and Arunachalam, A.R., (2017). A study on privacy preserving techniques in big data analytics. International Journal of Pure and Applied Mathematics, 116(10), pp.281-286. Pereira, C.K., Siqueira, S.W.M., Nunes, B.P. and Dietze, S., (2017). Linked data in Education: a survey and a synthesis of actual research and future challenges. IEEE Transactions on Learning Technologies, 11(3), pp.400-412. Raja, R. and Nagasubramani, P.C., (2018). Impact of modern technology in education. Journal of Applied and Advanced Research, 3(1), pp.33-35. Torabi Asr, F. and Taboada, M., (2019). Big Data and quality data for fake news and misinformation detection. Big Data & Society, 6(1), p.2053951719843310. Williamson, B., (2017). Who owns educational theory? Big data, algorithms, and the expert power of education data science. E-learning and Digital Media, 14(3), pp.105-122. Yaqoob, I., Hashem, I.A.T., Gani, A., Mokhtar, S., Ahmed, E., Anuar, N.B. and Vasilakos, A.V., (2016). Big data: From beginning to future. Big data assignment International Journal of Information Management, 36(6), pp.1231-1247.


Subject Name: Information Technology

Level: Diploma


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