Dashboard proposal implemented according to an analysis developed on the KNIME platform

Jhon Edwar Ninasivincha-Apfata, Ricardo Carlos Quispe-Figueroa, Manuel Alejandro Valderrama-Solis, Benjamin Maraza-Quispe

Research output: Contribution to journalArticlepeer-review


The objective of the research is to develop a methodology to analyse a set of data extracted from a learning management system, in order to implement a dashboard, which can be used by teachers to make timely and relevant decisions to improve the teaching-learning processes. The methodology used consisted of analysing 9, 257 records extracted through simple random sampling from a population of 100, 000 records. The indicators analysed were number of accesses, course grades, time spent, number of courses enrolled and number of activities developed. The results show that the data analysis was carried out on the (o Konstanz Information Miner (KNIME) data mining analysis platform, and the model was implemented in five phases: requirements definition, model design, development, implementation and evaluation of results. The results are taken as a recommendation to design and implement a customised dashboard for teachers to identify observable behavioural patterns that allow them to make decisions to improve the teaching-learning processes of students.

Original languageEnglish
Pages (from-to)816-837
Number of pages22
JournalWorld Journal on Educational Technology: Current Issues
Issue number4
StatePublished - 2021

Bibliographical note

Funding Information:
This research was made possible with the support of the National University of San Agustin de Arequipa

Publisher Copyright:
© 2021 Birlesik Dunya Yenilik Arastirma ve Yayincilik Merkezi.


  • Analytics
  • Dashboard
  • KNIME learning
  • Personalised
  • Teaching


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