Uso de la comprensión lectora para la construcción de un modelo predictivo del éxito de estudiantes de 4º de Primaria cuando resuelven problemas verbales en un sistema inteligente
This work presents a dynamic mathematical model designed to predict fourth grade primary students’ (9-10 years-old) achievement in the arithmetic solving of word problems. The work is organized into two parts. In the first part, we analyzed the variables that will be eventually included into the mod...
| Autores: | , , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2019 |
| País: | España |
| Recursos: | Universidad de Castilla-La Mancha |
| Repositório: | RUIdeRA. Repositorio Institucional de la UCLM |
| OAI Identifier: | oai:ruidera.uclm.es:10578/39154 |
| Acesso em linha: | https://hdl.handle.net/10578/39154 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Comprensión lectora Educación Primaria Intelligent tutoring systems K-BIT PIRLS Primary Education Problem solving Problemas verbales Reading comprehension Resolución de problemas Sistemas tutoriales inteligentes Word problems |
| Resumo: | This work presents a dynamic mathematical model designed to predict fourth grade primary students’ (9-10 years-old) achievement in the arithmetic solving of word problems. The work is organized into two parts. In the first part, we analyzed the variables that will be eventually included into the model, the relationships between them and the effect on the predicted outcome variable. The model takes into consideration variables related to subjects’ features: prior proficiency in solving word problems, level of reading comprehension, and the ability to solve reasoning problems through figurative and abstract visual stimuli (also called fluid intelligence). Additionally, the model employs a variable that describes the task difficulty using the semantic category of the statements as a criterion of complexity. Sixty-four fourth-grade students took part in the experiment. For each student data were gathered by using three different instruments: a PIRLS reading comprehension test, the matrix subtest from the Kaufman test, and an intelligent tutorial system, which was used by participants to solve 26 word problems. All variables showed a strong statistical correlation with the dependent variable (the students’ achievement in word problems), except for fluid intelligence. The presented model reveals that reading comprehension has a significant relevance when it comes to predicting primary students’ performance in word problems. In addition, this model offers better behaviour in comparison to similar alternatives presented in the literature. Keywords: reading comprehension, PIRLS, problem solving, intelligent tutoring systems, K-BIT, word problems, Primary Education. |
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