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Titre
Recommender system to identify students with learning deficiencies in assessments
Autor(es)
Sujet
Learning assessment
Decision making
Data visualization
Recommender system
Excel VBA
Fecha de publicación
2016
Éditeur
Ediciones Universidad de Salamanca (España)
Citación
Ibarra, Manuel J; Serrano, Cristhian; Navarro, Ángel F.; Bastidas,Micaela; Arguedas, Jose Maria. Recommender system to identify students with learning deficiencies in assessments. En García-Peñalvo, Francisco José; Mendes, António José (eds.). Simposio Internacional de Informática Educativa (18º. 2016. Salamanca). Salamanca: Ediciones Universidad de Salamanca, 2016, p.275-280.
Serie / N.º
Aquilafuente;222
Resumen
[EN] Find areas and indicators of achievement where
students need to reinforce their knowledge is a difficult task for
teachers in schools. This article presents a decision-making
support system that allows teachers to identify students with poor
academic performance. The strategy is a Matrix Based
Recommender System to rate assessments and share the results
using statistical graphs. To validate this proposal we used focus
group and daily meetings methodologies. The proposed strategy
was tested in UGEL07-Lima-Perú with 135 schools and 25491
students in evaluation process. The evaluation results show that
teachers agree with the proposed strategy, because it allows them
to have assessment information everywhere and at every time. The
results also highlight that using the tool users can have visual
information in real time. Furthermore, the information shared
through the application improves decision-making on corrective
actions for poor academic performance in evaluated areas.
URI
ISBN
978-84-9012-630-1
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