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Towards the Readiness of Learning Analytics Data for Micro Learning

Journal Article


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Abstract


  • 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.

Publication Date


  • 2019

Citation


  • Lin, J., Sun, G., Shen, J., Cui, T., Yu, P., Xu, D., Li, L. & Beydoun, G. (2019). Towards the Readiness of Learning Analytics Data for Micro Learning. Lecture Notes in Computer Science, 11515 66-76. San Diego, United States International Conference on Services Computing

Ro Full-text Url


  • https://ro.uow.edu.au/cgi/viewcontent.cgi?article=3848&context=eispapers1

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/2838

Number Of Pages


  • 10

Start Page


  • 66

End Page


  • 76

Volume


  • 11515

Place Of Publication


  • Germany

Abstract


  • 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.

Publication Date


  • 2019

Citation


  • Lin, J., Sun, G., Shen, J., Cui, T., Yu, P., Xu, D., Li, L. & Beydoun, G. (2019). Towards the Readiness of Learning Analytics Data for Micro Learning. Lecture Notes in Computer Science, 11515 66-76. San Diego, United States International Conference on Services Computing

Ro Full-text Url


  • https://ro.uow.edu.au/cgi/viewcontent.cgi?article=3848&context=eispapers1

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/2838

Number Of Pages


  • 10

Start Page


  • 66

End Page


  • 76

Volume


  • 11515

Place Of Publication


  • Germany