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Learning Analytics in Mobile Applications Based on Multimodal Interaction

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Software Data Engineering for Network eLearning Environments

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 11))

Abstract

One of the most valuable skills for teachers is the ability to produce their own digital solutions, translating teaching concepts into end-user computer systems. This often requires the involvement of computing specialists. As a result, the development of educational programming environments remains a challenge. Learning experiences based multimodal interaction applications (gesture interaction, voice recognition or artificial vision) are becoming commonplace in education because they motivate and involve students. This chapter analyses the state-of-the-art in LA techniques and user-friendly authoring tools. It presents a tool to support the creation of multimodal interactive applications equipped with non-intrusive monitoring and analytics capabilities. This tool enables teachers with no programming skills to create interactive LA-enriched learning scenarios. To this end, several components that manage LA activities are included in the tool, they range from automatically capturing users’ interaction with mobile applications, to querying data and retrieving metrics, to visualising tables and charts.

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Notes

  1. 1.

    https://solaresearch.org/.

  2. 2.

    https://www.adlnet.gov/xAPI.

  3. 3.

    https://www.imsglobal.org/activity/caliper.

  4. 4.

    http://appinventor.mit.edu/explore/.

  5. 5.

    http://scratch.mit.edu.

  6. 6.

    http://code.org.

  7. 7.

    https://www.vuforia.com/.

  8. 8.

    http://www.jpct.net/.

  9. 9.

    https://vr.google.com/intl/en_en/cardboard/developers/.

  10. 10.

    https://wwww.google.com/fusiontables.

  11. 11.

    http://www.eclipse.org/aspectj.

  12. 12.

    https://developers.google.com/chart.

  13. 13.

    https://developers.google.com/cloud-messaging/.

  14. 14.

    https://play.google.com/store/apps/details?id=appinventor.ai_vedils.TheChineseWhispers.

  15. 15.

    http://vedils.uca.es/web/index.html#portfolio.

  16. 16.

    https://fusiontables.google.com/data?docid=1rTpotc_7XWof8mIGrDeZ_Ia1nrdNc0Ilq4zDIbnD#rows:id=1.

  17. 17.

    https://www.mongodb.com.

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Author information

Authors and Affiliations

  1. University of Cádiz, Avenida de la Universidad de Cádiz, 10, Puerto Real, Cádiz, Spain

    José Miguel Mota, Iván Ruiz-Rube, Juan Manuel Dodero & Tatiana Person

  2. School of Computer Science and Statistics, Trinity College, Dublin, Ireland

    Inmaculada Arnedillo-Sánchez

Authors
  1. José Miguel Mota
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  2. Iván Ruiz-Rube
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  3. Juan Manuel Dodero
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  4. Tatiana Person
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  5. Inmaculada Arnedillo-Sánchez
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Corresponding author

Correspondence to José Miguel Mota .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science, Multimedia and Telecommunications, Universitat Oberta de Catalunya, Barcelona, Spain

    Santi Caballé

  2. Faculty of Computer Science, Multimedia and Telecommunications, eHealth Center Universitat Oberta de Catalunya, Barcelona, Spain

    Jordi Conesa

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Mota, J.M., Ruiz-Rube, I., Dodero, J.M., Person, T., Arnedillo-Sánchez, I. (2018). Learning Analytics in Mobile Applications Based on Multimodal Interaction. In: Caballé, S., Conesa, J. (eds) Software Data Engineering for Network eLearning Environments. Lecture Notes on Data Engineering and Communications Technologies, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-319-68318-8_4

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  • DOI: https://doi.org/10.1007/978-3-319-68318-8_4

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