Understand, develop and enhance the learning process with big data
| DOI | https://doi.org/10.1108/IDD-09-2018-0043 |
| Published date | 01 March 2019 |
| Date | 01 March 2019 |
| Pages | 2-16 |
| Author | Soraya Sedkaoui,Mounia Khelfaoui |
| Subject Matter | Library & information science,Library & information services,Lending,Document delivery,Collection building & management,Stock revision,Consortia |
Understand, develop and enhance the learning
process with big data
Soraya Sedkaoui
Universite de Khemis Miliana, Algeria, and SRY Consulting, Montpellier, France, and
Mounia Khelfaoui
Universite de Khemis Miliana, Khemis Miliana, Algeria
Abstract
Purpose –With the advent of the internet and communication technology, the penetration of e-learning has increased. The digital data being
created by the educational and research institutions is also on the ascent. The growing interest in recent years toward big data, educational data
mining and learning analytics has motivated the development of new analytical ways and approaches and advancements in learning setti ngs. The
need for using big data to handle, analyze this large amount of data is prime. This trend has started attracting the interest of educational institutions
which have an important role in the development skills process and the preparation of a new gener ation of learners. “A real revolution for
education,”it is based on this kind of terms that many articles have paid attention to big data for learning. How can analytics techniques and tools
be so efficient and become a great prospect for the learning process? Big data analytics, when applied into teaching and learning processes, might
help to improvise as well as to develop new paradigms. In this perspective, this paper aims to investigate the most promising applications and issues
of big data for the design of the next-generation of massive e-learning. Specifically, it addresses the analytical tools and approaches for enhancing
the future of e-learning, pitfalls arising from the usage of large data sets. Globally, this paper focuses on the possible application of big data
techniques on learning developments, to show the power of analytics and why integrating big data is so important for the learning context.
Design/methodology/approach –Big data has in the recent years been an area of interest among innovative sectors and has become a major priority for
many industries, and learning sector cannot escape to this deluge. This paper focuses on the different methods of big data able to be used in learning context
to understand the benefits it can bring both to teaching and learning process, and identify its possible impact on the future of this sector in general. This paper
investigates the connection between big data and the learning context. This connection can be illustrated by identifying the several main analytics approaches,
methods and tools for improving the learning process. This can be clearer by the examination of the different ways and solutions that contribute to making a
learning process more agile and dynamic. The methods that were used in this research are mainly of a descriptive and analytical nature, to establish howbig
data and analytics methods develop the learning process, and understand their contributions and impacts in addressing learning issues. To this end, authors
have collected and reviewed existing literature related to big data in education and the technology application in the learning context. Authors thenhavedone
the same process with dynamic and operational examples of big data for learning. In this context, the authors noticed that there are jigsaw bits that contained
important knowledge on the different parts of the research area. The process concludes by outlining the role andbenefit of the related actors and highlighting
the several directions relating to the development and implementation of an efficient learning process based on big data analytics.
Findings –Big data analytics, its techniques, tools and algorithms are important to improve the learning context. The findings in this paper suggest
that the incorporation of an approach based on big data is of crucial importance. This approach can improve the learning process, for this, its
implementation must be correctly aligned with educational strategies and learning needs.
Research limitations/implications –This research represents a reference to better understanding the influenceandtheroleofbigdataineducational
dynamic. In addition, it leads to improve existing literature about big data for learning. The limitations of the paper are given by its nature derived from a
theoretical perspective, and the discussed ideas can be empirically validated by identifying how big data helps in addressing learning issues.
Originality/value –Over the time, the process that leads to the acquisition of the knowledge uses and receives more technological tools and
components; this approach has contributed to the development of information communication and the interactive learning context. Technology
applications continue to expand the boundaries of education into an “anytime/anywhere”experience. This technology and its wide use in the
learning system produce a vast amount of different kinds of data. These data are still rarely exploited by educational practitioners. Its successful
exploitation conducts educational actors to achieve their full potential in a complex and uncertain environment. The general motivation for this
research is assisting higher educational institutions to better understand the impact of the big data as a success factor to develop their learning
process and achieve their educational strategy and goals. This study contributes to better understand how big data analytics solutions are turned
into operational actions and will be particularly valuable to improve learning in educational institutions.
Keywords E-learning, Higher education, Big data, Learning analytics, Learning process, Algorithm
Paper type Research paper
The current issue and full text archive of this journal is available on
Emerald Insight at: www.emeraldinsight.com/2398-6247.htm
Information Discovery and Delivery
47/1 (2019) 2–16
© Emerald Publishing Limited [ISSN 2398-6247]
[DOI 10.1108/IDD-09-2018-0043]
This paper forms part of the special section “Higher education information
discovery, analytics, and dissemination”, guest edited by Mounir Kehal
and Dr Justin Zhang.
Received 9 September 2018
Revised 1 October 2018
Accepted 12 October 2018
2
To continue reading
Request your trial