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Permanent URI for this collectionhttps://repositorio.grial.eu/handle/123456789/34

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Author: search.filters.author.García-Holgado, A.Subject: search.filters.subject.Data visualization

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    Following up the progress of doctoral students and advisors’ workload through data visualizations: a case study in a PhD program
    (CEUR-WS.org, 2021-07-07) Vázquez-Ingelmo, A.; García-Holgado, A.; Hernández-Payo, H.; García-Peñalvo, F. J.; Therón, R.
    One of the most important aspects to consider during the development of a PhD is the students’ progress, both for their advisors and the students themselves. However, several achievements of different natures are involved during a PhD (research stays, publications, seminars, research plans, etc.). For these reasons, we propose a set of data visualizations to support decision-making processes in a PhD program. A preliminary requirement elicitation process was carried out to obtain a design basis for the implementation and integration of these tools in the PhD portal. Once the visualizations were implemented, a usability study was performed to measure the perceived usability of the newly added PhD portal functionalities. This paper presents the design process and usability study outcomes of applying data visualizations to the learning outcomes of the PhD Programme in Education in the Knowledge Society at the University of Salamanca.
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    A Meta-modeling Approach to Take into Account Data Domain Characteristics and Relationships in Information Visualizations
    (Springer, 2021-03-30) Vázquez-Ingelmo, A.; García-Holgado, A.; García-Peñalvo, F. J.; Therón, R.
    Visual explanations are powerful means to convey information to large audiences. However, the design of information visualizations is a complex task, because a lot of factors are involved (the audience profile, the data domain, etc.). The complexity of this task can lead to poor designs that could make users reach wrong conclusions from the visualized data. This work illustrates the process of identifying features that could make an information visualization confusing or even misleading with the goal of arranging them into a meta-model. The meta-model provides a powerful resource to automatically generate information visu-alizations and dashboards that take into account not only the input data, but also the audience’s characteristics, the available data domain knowledge and even the data context.