Towards the Readiness of Learning Analytics Data for Micro Learning

  • Jiayin LinEmail author
  • Geng SunEmail author
  • Jun ShenEmail author
  • Tingru CuiEmail author
  • Ping YuEmail author
  • Dongming XuEmail author
  • Li LiEmail author
  • Ghassan BeydounEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11515)


With the development of data mining and machine learning techniques, data-driven based technology-enhanced learning (TEL) has drawn wider attention. Researchers aim to use established or novel computational methods to solve educational problems in the ‘big data’ era. However, the readiness of data appears to be the bottleneck of the TEL development and very little research focuses on investigating the data scarcity and inappropriateness in the TEL research. This paper is investigating an emerging research topic in the TEL domain, namely micro learning. Micro learning consists of various technical themes that have been widely studied in the TEL research field. In this paper, we firstly propose a micro learning system, which includes recommendation, segmentation, annotation, and several learning-related prediction and analysis modules. For each module of the system, this paper reviews representative literature and discusses the data sources used in these studies to pinpoint their current problems and shortcomings, which might be debacles for more effective research outcomes. Accordingly, the data requirements and challenges for learning analytics in micro learning are also investigated. From a research contribution perspective, this paper serves as a basis to depict and understand the current status of the readiness of data sources for the research of micro learning.


Micro learning Learning analytics Machine learning Data mining Data insufficiency 



This research has been carried out with the support of the Australian Research Council Discovery Project, DP180101051, and Natural Science Foundation of China, no. 61877051, and UGPN RCF 2018-2019 project between University of Wollongong and University of Surrey.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Computing and Information TechnologyUniversity of WollongongWollongongAustralia
  2. 2.Research Lab of Electronics, Department of EE and CSMassachusetts Institute of TechnologyCambridgeUSA
  3. 3.UQ Business SchoolThe University of QueenslandBrisbaneAustralia
  4. 4.Faculty of Computer and Information ScienceSouthwest UniversityChongqingChina
  5. 5.School of Information System and ModellingUniversity of Technology SydneySydneyAustralia

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