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

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



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Author Details

Ranieri Alves dos Santos
  • Graduate Program in Knowledge Engineering and Management, UFSC, Florianópolis, Brazil
Dalner Barbi
  • Graduate Program in Knowledge Engineering and Management, UFSC, Florianópolis, Brazil
Vinicius Faria Culmant Ramos
  • Graduate Program in Knowledge Engineering and Management, UFSC, Florianópolis, Brazil
Fernando Alvaro Ostuni Gauthier
  • Graduate Program in Knowledge Engineering and Management, UFSC, Florianópolis, Brazil

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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)
https://doi.org/10.4230/OASIcs.ICPEC.2023.10

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.

Subject Classification

ACM Subject Classification
  • Information systems → Data analytics
Keywords
  • learning analytics
  • data visualization
  • learning indicators

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References

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