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Intuitive Visualization of Complex Diagnostic Datasets to Improve Teachers’ Individual Support of Learners Based on Data Driven Decision Making

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HCI International 2021 - Posters (HCII 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1421))

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Abstract

Being able to read and write properly is an important aspect of social participation. There are 6.2 million adults living in Germany who are considered to have low literacy levels. However, supporting people with low literacy is very time-consuming and personnel-intensive. For teachers in literacy courses, we have developed a dashboard for automated diagnosis as well as individual support and tested and evaluated it in the context of UX studies. The goal is to develop a tool that uses visualizations to present complex competence diagnostics in such a way that teachers can intuitively derive profound and individualized support measures for learners.

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Authors and Affiliations

  1. University of Bremen, Bremen, Germany

    Imke A. M. Meyer & Karsten D. Wolf

Authors
  1. Imke A. M. Meyer
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  2. Karsten D. Wolf
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Correspondence to Imke A. M. Meyer .

Editor information

Editors and Affiliations

  1. University of Crete and Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Constantine Stephanidis

  2. Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Margherita Antona

  3. Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Stavroula Ntoa

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Meyer, I.A.M., Wolf, K.D. (2021). Intuitive Visualization of Complex Diagnostic Datasets to Improve Teachers’ Individual Support of Learners Based on Data Driven Decision Making. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2021 - Posters. HCII 2021. Communications in Computer and Information Science, vol 1421. Springer, Cham. https://doi.org/10.1007/978-3-030-78645-8_13

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  • DOI: https://doi.org/10.1007/978-3-030-78645-8_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78644-1

  • Online ISBN: 978-3-030-78645-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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