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International Afro-European Conference for Industrial Advancement

AECIA 2016: Proceedings of the Third International Afro-European Conference for Industrial Advancement — AECIA 2016 pp 209–217Cite as

Learning with Big Data Technology: The Future of Education

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 565))

Abstract

The use of Big Data systems in the field of education allows to envisage new approaches and new learning contexts. Indeed, the rapid emergence of the new e-learning platforms have been presented in many interests. However, the quality of the teaching service rendered depends on the capacity of the learning approaches to be provided to learners, content and learning path tailored to their needs. In this paper, we will present how Big Data helps to solve education issues through reaching the objective of learning. Then, we will introduce some opportunities of Big Data analytics to develop the efficiency and effectiveness of students learning and maximize their knowledge retention. Finally, our research method show that students can generate personalized activities and offer academic advising. Big Data can expose the capabilities of learners, predict their future performances and offer assistance for educational organizations to make strategic decisions.

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References

  1. Gantz, J., Reinsel, D.: Extracting value from chaos. IDC iView 1142, 9–10 (2011)

    Google Scholar 

  2. Barnes, T., Desmarais, M., Romero, C., Ventura, S.: Educational data mining. In: Proceedings of 2nd International Conference on Educational Data Mining. Cordoba, Spain (2009)

    Google Scholar 

  3. Pinnell, C., Paulmani, G., Kumar, V.: Curricular and learning analytics: a big data perspective. In: Ben, K.D. (ed.) Big Data and Learning Analytics in Higher Education, pp. 125–145. Springer, New York (2016)

    Google Scholar 

  4. Bernard, J., Chang, T.-W., Popescu, E., Graf, S.: Using artificial neural networks to identify learning styles. In: 17th International Conference, AIED 2015, Madrid, pp. 541–544, 22–26 June 2015

    Google Scholar 

  5. Zotou, M., Tambouris, E.: Data-driven blended problem based learning towards enhancing transversal skills. In: 2014 IEEE 14th International Conference on Advanced Learning Technologies, pp. 762–764 (2014)

    Google Scholar 

  6. Schmidt, H.G.: Problem-based learning: rationale and description. Med. Educ. 17, 11–16 (1983)

    Article  Google Scholar 

  7. Vilajosana, I., et al.: Bootstrapping smart cities through a selfsustainable model based on big data flow. Commun. Mag. IEEE 51, 128–134 (2013)

    Article  Google Scholar 

  8. http://www.informationweek.com/education/datamanagement/big-data-helps-guide-colorados-public-sc/240159055

  9. http://www.edtechmagazine.com/k12/article/2013/08/coloradosbig-data-system-drives-education-reform

  10. http://www.qas.com/dataqualitynews/big_data_can_help_improve_education_system_9543.htm

  11. http://www.huffingtonpost.com/vineet-madan/big-data-has-cometo-educ_b_1625801.html

  12. http://goodereader.com/blog/digital-publishing/how-big-datahelps-the-education-system

  13. Raghunathan, S., Kaur, A.: Assessment of online interaction pattern using the Q-4R framework. In: The International Lifelong Learning Conference (2011)

    Google Scholar 

  14. Aggarwal, A.: Identification of quality parameters associated with 3V’s of Big Data. In: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), pp. 1135–1140, March 2016

    Google Scholar 

  15. Chawda, R.K., Thakur, G.: Big data and advanced analytics tools. In: 2016 Symposium on Colossal Data Analysis and Networking (CDAN), March 2016

    Google Scholar 

  16. Apache Software Foundation: Apache Hadoop. http://hadoop.apache.org/

  17. Dean, J., Ghemawat, S.: Mapreduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)

    Article  Google Scholar 

  18. Borthakur, D.: The Hadoop Distributed File System: Architecture and Design. 2007. http://www.hadoop.apache.org

  19. Mavroudi, A., Hadzilacos, T., Angeli, C.: An adaptive e-Learning strategy to overcome the inherent difficulties of the learning content. In: Verbert, K., Sharples, M., Klobučar, T. (eds.) Adaptive and Adaptable Learning, EC-TEL 2016. Lecture Notes in Computer Science, vol. 9891. Springer, Cham (2016)

    Google Scholar 

  20. MongoDB: Free and Open-Source Document-Oriented Database. http://www.mongodb.org/

  21. Weka: Machine Learning Group. http://www.cs.waikato.ac.nz/

  22. Apache Flume: https://blogs.apache.org/flume/

  23. Siemens, G., Baker, R.S.J.: Learning Analytics and Educational Data Mining: Towards Communication and Collaboration. Learning Analytics and Knowledge 2012. http://users.wpi.edu/~rsbaker/LAKs%20reformatting%20v2.pdf

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Author information

Authors and Affiliations

  1. LAROSERI Laboratory, Department of Computer Sciences, Faculty of Sciences, University of Chouaib Doukkali, El Jadida, Morocco

    Marouane Birjali & Abderrahim Beni-Hssane

  2. TIAD Laboratory, Department of Computer Sciences, Faculty of Sciences and Technologies, University of Sultan Moulay Slimane, Béni Mellal, Morocco

    Mohammed Erritali

Authors
  1. Marouane Birjali
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  2. Abderrahim Beni-Hssane
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  3. Mohammed Erritali
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Corresponding author

Correspondence to Marouane Birjali .

Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  2. Department of Mathematics and Computer, Faculty of Sciences and Techniques, Settat, Morocco

    Abdelkrim Haqiq

  3. Information Technology Department, Faculty of Computers and Information, Giza, Egypt

    Aboul Ella Hassanien

  4. VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Vaclav Snasel

  5. ENIS, University of Sfax, Sfax, Tunisia

    Adel M. Alimi

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Birjali, M., Beni-Hssane, A., Erritali, M. (2018). Learning with Big Data Technology: The Future of Education. In: Abraham, A., Haqiq, A., Ella Hassanien, A., Snasel, V., Alimi, A. (eds) Proceedings of the Third International Afro-European Conference for Industrial Advancement — AECIA 2016. AECIA 2016. Advances in Intelligent Systems and Computing, vol 565. Springer, Cham. https://doi.org/10.1007/978-3-319-60834-1_22

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  • DOI: https://doi.org/10.1007/978-3-319-60834-1_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60833-4

  • Online ISBN: 978-3-319-60834-1

  • eBook Packages: EngineeringEngineering (R0)

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