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Data-Driven Personalization of Student Learning Support in Higher Education

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Learning Analytics: Fundaments, Applications, and Trends

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 94))

Abstract

Despite the explosion of interest in big data in higher education and the ensuing rush for catch-all predictive algorithms, there has been relatively little focus on the pedagogical and pastoral contexts of learning. The provision of personalized feedback and support to students is often generalized and decontextualized, and examples of systems that enable contextualized support are notably absent from the learning analytics landscape. In this chapter we discuss the design and deployment of the Student Relationship Engagement System (SRES), a learning analytics system that is grounded primarily within the unique contexts of individual courses. The SRES, currently in use by teachers from 19 departments, takes a holistic and more human-centric view of data—one that puts the relationship between teacher and student at the center. Our approach means that teachers’ pedagogical expertise in recognizing meaningful data, identifying subgroups of students for a range of support actions, and designing and deploying these actions, is facilitated by a customizable technology platform. We describe a case study of the application of this human-centric approach to learning analytics, including its impacts on improving student engagement and outcomes, and debate the cultural, pedagogical, and technical aspects of learning analytics implementation.

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Abbreviations

EDM:

Educational data mining

EWS:

Early warning system

LA:

Learning analytics

LMS:

Learning management system

SRES:

Student Relationship Engagement System

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Acknowledgements

The authors wish to thank the many teaching and support staff who have patiently implemented the SRES in their units of study, supported its use, and provided valuable feedback.

Author information

Authors and Affiliations

  1. Faculty of Science, The University of Sydney, Sydney, NSW, 2006, Australia

    Danny Yen-Ting Liu & Adam J. Bridgeman

  2. Quality and Analytics Group, The University of Sydney, Sydney, NSW, 2006, Australia

    Kathryn Bartimote-Aufflick

  3. Faculty of Engineering and Information Technology, The University of Sydney, Sydney, NSW, 2006, Australia

    Abelardo Pardo

Authors
  1. Danny Yen-Ting Liu
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  2. Kathryn Bartimote-Aufflick
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  3. Abelardo Pardo
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  4. Adam J. Bridgeman
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Corresponding author

Correspondence to Abelardo Pardo .

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Editors and Affiliations

  1. Instituto Politécnico Nacional, WOLNM & Escuela Superior de Ingeniería,Mecánica y Eléctrica, Zacatenco, México DF, Mexico

    Alejandro Peña-Ayala

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Liu, D.YT., Bartimote-Aufflick, K., Pardo, A., Bridgeman, A.J. (2017). Data-Driven Personalization of Student Learning Support in Higher Education. In: Peña-Ayala, A. (eds) Learning Analytics: Fundaments, Applications, and Trends. Studies in Systems, Decision and Control, vol 94. Springer, Cham. https://doi.org/10.1007/978-3-319-52977-6_5

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  • DOI: https://doi.org/10.1007/978-3-319-52977-6_5

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  • Online ISBN: 978-3-319-52977-6

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