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Flexible and Contextualized Cloud Applications for Mobile Learning Scenarios

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Mobile, Ubiquitous, and Pervasive Learning

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 406))

Abstract

This chapter describes our research efforts related to the design of mobile learning (m-learning) applications in cloud-computing (CC) environments. Many cloud-based services can be used/integrated in m-learning scenarios, hence, there is a rich source of applications that could easily be applied to design and deploy those within the context of cloud-based services. Here, we present two cloud-based approaches—a flexible framework for an easy generation and deployment of mobile learning applications for teachers, and a flexible contextualization service to support personalized learning environment for mobile learners. The framework provides a flexible approach that supports teachers in designing mobile applications and automatically deploys those in order to allow teachers to create their own m-learning activities supported by mobile devices. The contextualization service is proposed to improve the content delivery of learning objects (LOs). This service allows adapting the learning content and the mobile user interface (UI) to the current context of the user. Together, this leads to a powerful and flexible framework for the provisioning of potentially ad hoc mobile learning scenarios. We provide a description of the design and implementation of two proposed cloud-based approaches together with scenario examples. Furthermore, we discuss the benefits of using flexible and contextualized cloud applications in mobile learning scenarios. Hereby, we contribute to this growing field of research by exploring new ways for designing and using flexible and contextualized cloud-based applications that support m-learning.

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Notes

  1. 1.

    https://itunes.apple.com/en/app/star-walk-5-stars-astronomy/id295430577?mt=8.

  2. 2.

    https://itunes.apple.com/us/app/chemcalc/id499955745?mt=8.

  3. 3.

    https://swiftkey.com/en/.

Abbreviations

CC:

Cloud computing

GPS:

Global positioning system

ICT:

Information and communication technologies

LO:

Learning object

m-learning:

Mobile learning

MVSM:

Multi-dimensional vector space model

RCM:

Rich context model

TEL:

Technology enhanced learning

UI:

User interface

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Author information

Authors and Affiliations

  1. LNU: Linnaeus University, 351 95, Växjö, Sweden

    Alisa Sotsenko, Janosch Zbick, Marc Jansen & Marcelo Milrad

  2. University of Applied Sciences Ruhr West, Dümptener Str. 45, 45476, Mülheim an der Ruhr, Germany

    Marc Jansen

Authors
  1. Alisa Sotsenko
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  2. Janosch Zbick
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  3. Marc Jansen
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  4. Marcelo Milrad
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Corresponding author

Correspondence to Alisa Sotsenko .

Editor information

Editors and Affiliations

  1. Artificial Intelligence on Education Lab, WOLNM:, Ciudad de México, Mexico

    Alejandro Peña-Ayala

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Sotsenko, A., Zbick, J., Jansen, M., Milrad, M. (2016). Flexible and Contextualized Cloud Applications for Mobile Learning Scenarios. In: Peña-Ayala, A. (eds) Mobile, Ubiquitous, and Pervasive Learning. Advances in Intelligent Systems and Computing, vol 406. Springer, Cham. https://doi.org/10.1007/978-3-319-26518-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-26518-6_7

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  • Publisher Name: Springer, Cham

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