License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.ICPEC.2023.10
URN: urn:nbn:de:0030-drops-185069
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18506/
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dos Santos, Ranieri Alves ; Barbi, Dalner ; Ramos, Vinicius Faria Culmant ; Gauthier, Fernando Alvaro Ostuni

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

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OASIcs-ICPEC-2023-10.pdf (0.7 MB)

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.

BibTeX - Entry

@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.dagstuhl.de/opus/volltexte/2023/18506},
  URN =		{urn:nbn:de:0030-drops-185069},
  doi =		{10.4230/OASIcs.ICPEC.2023.10},
  annote =	{Keywords: learning analytics, data visualization, learning indicators}
}

Keywords: learning analytics, data visualization, learning indicators
Collection: 4th International Computer Programming Education Conference (ICPEC 2023)
Issue Date: 2023
Date of publication: 09.08.2023

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