Abstract
Learning management systems (LMS) in the online education sector have led to a huge amount of data from the interaction between the student and the student environment that generates a lot of digital traces. This colossal amount of data cannot be processed by traditional learning analytics. This has led to the insertion of Big Data technologies and tools in education to handle the large amount of data involved. The process of collecting, analyzing, and intelligently using this learner-generated data to understand and help the learner is called Learning Analytics. LA is a new lens through which teachers can address the needs of individual learners to a greater extent. This work examines and explores the concepts of big data and learning analytics. In particular, this study aims to conduct a systematic review of big data and LA technologies in education to explore trends, categorize research topics, and highlight the contributions of these technologies in online education.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Djouad, T.: Ingénierie des indicateurs d’activités à partir de traces modélisées pour un Environnement Informatique d’Apprentissage Humain (Doctoral dissertation, Université Claude Bernard-Lyon I; Université Mentouri-Constantine) (2011)
Mezzanzanica, M., Mercorio, F. : Big Data Pour Les Systèmes D’information/De Renseignement Sur Le Marché Du Travail
Siemens, G., Gasevic, D.: Guest editorial-learning and knowledge analytics. J. Educ. Technol. Soc. 15(3), 1–2 (2012)
Dowell, N.M., et al.: Modeling learners’ social centrality and performance through language and discourse. Int. Educ. Data Min. Soc. (2015)
Clow, D.: The learning analytics cycle: closing the loop effectively. In: Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, pp. 134–138 (2012, April)
Saqr, M.: Using learning analytics to understand and support collaborative learning (Doctoral dissertation, Department of Computer and Systems Sciences, Stockholm University) (2018)
Gašević, D., Kovanović, V., Joksimović, S.: Piecing the learning analytics puzzle: A consolidated model of a field of research and practice. Learn. Res. Pract. 3(1), 63–78 (2017)
Chatti, M.A., Dyckhoff, A.L., Schroeder, U., Thüs, H.: A reference model for learning analytics. Int. J. Technol. Enhanced Learn. 4(5–6), 318–331 (2012)
Pence, H.E.: What is big data and why is it important? J. Educ. Technol. Syst. 43(2), 159–171 (2014)
Manyika, J., Lund, S., Bughin, J.: Digital Globalization: The New Era Global Flows. McKinsey Global Institute (2016)
Manyika, J., et al.: Big data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute (2011)
Kitchin, R., McArdle, G.: What makes big data, big data? exploring the ontological characteristics of 26 datasets. Big Data Soc. 3(1), 2053951716631130 (2016)
Adam, K., Bakar, N.A.A., Fakhreldin, M.A.I., Majid, M.A.: Big data and learning analytics: a big potential to improve e-learning. Adv. Sci. Lett. 24(10), 7838–7843 (2018)
Dahdouh, K., Dakkak, A., Oughdir, L., Ibriz, A.: Improving online education using big data technologies. Role Technol. Educ. (2020)
Sin, K., Muthu, L.: Application of big data in education data mining and learning analytics--a literature review. ICTACT J. Soft Comput. 5(4), 1035–1049 (2015)
Venant, R.: Les learning analytics pour promouvoir l’engagement et la réflexion des apprenants en situation d’apprentissage pratique (Doctoral dissertation, Université Paul Sabatier-Toulouse III) (2017)
Stéphane, T.: Data mining et statistique décisionnelle : l’intelligence des données. Editions Technip (2012)
Moharm, K., Eltahan, M.: The role of big data in improving e-learning transition. In: IOP Conference Series: Materials Science and Engineering, vol. 885, no. 1, p. 012003. IOP Publishing (July 2020)
Bomatpalli, T.: Learning analytics and big data in higher education. Int. J. Eng. Res. Technol. 3(1), 3377–3383 (2014)
Chihab, L., El Mhouti, A., Massar, M.: Using learning analytics techniques to calculate learner’s interaction indicators from their activity traces data. In: Ben Ahmed, M., Abdelhakim, B.A., Ane, B.K., Rosiyadi, D. (eds.) Emerging Trends in Intelligent Systems & Network Security. NISS 2022. Lecture Notes on Data Engineering and Communications Technologies, vol. 147, pp. 504–511. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-15191-0_48
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Chihab, L., El Mhouti, A., Massar, M., Hamdane, K. (2023). Learning Analytics and Big Data: Huge Potential to Improve Online Education. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2023. Lecture Notes in Networks and Systems, vol 668. Springer, Cham. https://doi.org/10.1007/978-3-031-29857-8_41
Download citation
DOI: https://doi.org/10.1007/978-3-031-29857-8_41
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-29856-1
Online ISBN: 978-3-031-29857-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)