SCAECH: Tool based on artificial intelligence for the evaluation of learning in constructionist environments

被引:0
|
作者
Giuliano, Hector Gustavo [1 ]
Abate, Stella Maris [2 ]
机构
[1] Pontificia Univ Catol Argentina, Fac Ingn Ciencias Agrarias, Buenos Aires, Argentina
[2] Univ Nacl La Plata, Fac Ingn, La Plata, Argentina
来源
REVISTA EDUCACION EN INGENIERIA | 2023年 / 18卷 / 35期
关键词
  Artificial intelligence; constructionism; homology; learning analytics; abelian groups; evaluation;
D O I
10.26507/rei.v18n35.1248
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents the product of a research whose objective was the construction and implementation of an automatic learning characterization system in constructionist environments with artificial intelligence, learning analytics and homology; a quasi-experimental research design was carried out where the subjects were part of predefined groups. The research is exploratory and focused on capturing the behavior of individuals in constructionist environments with specific materials, the methodological design is pre-experimental, and the intervention was done with all eleventh-grade students of three different courses of a public education institution in Colombia in the context of the SARS-COV2 pandemic. It was concluded that the system characterizes the learning structures of individuals in a constructionist environment via homology and the dynamics of building a model in a constructionist environment can be reconstructed.
引用
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页数:9
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