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Documents authored by Ramos, Vinicius Faria Culmant


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Short Paper
Data Visualization for Learning Analytics Indicators in Programming Teaching (Short Paper)

Authors: Ranieri Alves dos Santos, Dalner Barbi, Vinicius Faria Culmant Ramos, and Fernando Alvaro Ostuni Gauthier

Published in: OASIcs, Volume 112, 4th International Computer Programming Education Conference (ICPEC 2023)


Abstract
Learning Analytics (LA) has the potential to transform the way we learn, work and live our lives. To reach its potential, it must be clearly defined, incorporated into institutional teaching-learning strategies and processes and practices. The main goal of this study is to list indicators to be used in learning analytics in programming teaching and how to expose their views. For the development of the indicator model, this study based on a qualitative analysis, using data visualization and business intelligence tools, in projects focused on Learning Analytics. As a result, four main indicators were mapped: accesses to the system, resources accessed, activities carried out and, performance in activities.

Cite as

Ranieri Alves dos Santos, Dalner Barbi, Vinicius Faria Culmant Ramos, and Fernando Alvaro Ostuni Gauthier. Data Visualization for Learning Analytics Indicators in Programming Teaching (Short Paper). In 4th International Computer Programming Education Conference (ICPEC 2023). Open Access Series in Informatics (OASIcs), Volume 112, pp. 10:1-10:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{dossantos_et_al:OASIcs.ICPEC.2023.10,
  author =	{dos Santos, Ranieri Alves and Barbi, Dalner and Ramos, Vinicius Faria Culmant and Gauthier, Fernando Alvaro Ostuni},
  title =	{{Data Visualization for Learning Analytics Indicators in Programming Teaching}},
  booktitle =	{4th International Computer Programming Education Conference (ICPEC 2023)},
  pages =	{10:1--10:7},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-290-7},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{112},
  editor =	{Peixoto de Queir\'{o}s, Ricardo Alexandre and Teixeira Pinto, M\'{a}rio Paulo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2023.10},
  URN =		{urn:nbn:de:0030-drops-185069},
  doi =		{10.4230/OASIcs.ICPEC.2023.10},
  annote =	{Keywords: learning analytics, data visualization, learning indicators}
}
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