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An Architectural Perspective of Learning Analytics

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Machine Learning Paradigms

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 158))

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Abstract

Tools for learning analytics are becoming essential features of Learning Management Systems (LMS) and various course delivery platforms. These tools collect data from online learning platforms, analyze the collected data, and present the extracted information in a visually appealing manner. Representing the design-level concerns of such tools is one of the significant challenges faced by software developers. One way of overcoming this challenge is to adopt architectural perspectives which is a mechanism used by software architects to capture high-level design concerns. In this Chapter, we present an architectural perspective of such learning analytics tools and components. The primary objective of the chapter is to describe the functional elements and non-functional properties supported by such tools. Further, the chapter describes various techniques for realizing these functional and non-functional elements. Such an architectural perspective is useful in two different ways. First, the design knowledge represented through an architectural perspective is potentially useful to communicate the design and implementation of a learning analytics based system. Second, the architectural perspectives can also be used to evaluate the design of the tools in achieving their stated goals.

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Notes

  1. 1.

    www.coursera.com.

  2. 2.

    www.classroom.google.com.

  3. 3.

    https://www.w3.org/WAI/standards-guidelines/wcag/.

  4. 4.

    https://www.djangoproject.com/.

  5. 5.

    www.zoomdata.com.

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Authors and Affiliations

  1. Department of Computer Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, Raigad, 402103, India

    Arvind W. Kiwelekar, Manjushree D. Laddha, Laxman D. Netak & Sanil Gandhi

Authors
  1. Arvind W. Kiwelekar
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  2. Manjushree D. Laddha
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  3. Laxman D. Netak
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  4. Sanil Gandhi
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Corresponding author

Correspondence to Arvind W. Kiwelekar .

Editor information

Editors and Affiliations

  1. Department of Informatics, University of Piraeus, Piraeus, Greece

    Maria Virvou

  2. Department of Informatics, University of Piraeus, Piraeus, Greece

    Efthimios Alepis

  3. University of Piraeus, Pireas, Greece

    George A. Tsihrintzis

  4. Faculty of Science, Technology and Mathematics, University of Canberra, Canberra, SA, Australia

    Lakhmi C. Jain

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Kiwelekar, A.W., Laddha, M.D., Netak, L.D., Gandhi, S. (2020). An Architectural Perspective of Learning Analytics. In: Virvou, M., Alepis, E., Tsihrintzis, G., Jain, L. (eds) Machine Learning Paradigms. Intelligent Systems Reference Library, vol 158. Springer, Cham. https://doi.org/10.1007/978-3-030-13743-4_7

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