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  4. Predicting Academic Performance in Psychology Students from Their Social Skills Using Classification Algorithms
 
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Predicting Academic Performance in Psychology Students from Their Social Skills Using Classification Algorithms

Journal
ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting
Date Issued
2023
Author(s)
Espinosa-Pinos C.A.
Vasco-Álvarez M.M.
Cisneros-Bedón J.L.
Labre Tarco, Verónica
Facultad de Ciencias Sociales y Humanas
Type
Conference Paper
DOI
10.1109/ETCM58927.2023.10309091
URL
https://cris.indoamerica.edu.ec/handle/123456789/8290
Abstract
The high academic performance of students is the result of several factors, one of them being the development of social skills. Social skills allow students to face different circumstances, such as academic, personal, or professional. Students who develop these skills can quickly adapt to stressful and conflictive situations, generating complete well-being that facilitates learning, reflected in their academic performance. This study is critical because it helps educators identify students at risk of poor academic performance and provide adequate academic support. The research aims to identify predictors of academic performance based on social skills through knowledge discovery in databases (KDD) to clean data using classification algorithms, specifically Random Forest. To collect the data, a sociodemographic form, and the Social Skills Scale (SSS) were applied to 93 students of General Psychology, face-to-face modality, at Indoamerica University. The research results indicate that academic performance predictors are linked to gender and social skills, such as the ability to say no and cut interactions and the expression of states or disagreement. These findings suggest structuring support programs, academic guidance, and social skills development to improve academic performance and future career success. In conclusion, the research provides a new perspective to work in student welfare departments to improve students' academic performance. © 2023 IEEE.
Subjects
  • Evaluation y Added va...

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Acquisition Date
May 24, 2025
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