Approaches to learning does matter to predict academic achievement

Meta-analyses show that the correlations of approaches to learning with academic achievement are low. However, only one study has controlled these correlations in the presence of intelligence. Our study investigates the incremental validity of the surface and deep approaches taking cognitive abilit...

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Main Authors: Cristiano Mauro Assis Gomes, Heitor Blesa Farias, Enio Galinkin Jelihovschi
Format: Article
Language:Spanish
Published: Pontificia Universidad Católica del Perú 2022-07-01
Series:Revista de Psicología
Subjects:
Online Access:https://revistas.pucp.edu.pe/index.php/psicologia/article/view/25502
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author Cristiano Mauro Assis Gomes
Heitor Blesa Farias
Enio Galinkin Jelihovschi
author_facet Cristiano Mauro Assis Gomes
Heitor Blesa Farias
Enio Galinkin Jelihovschi
author_sort Cristiano Mauro Assis Gomes
collection DOAJ
description Meta-analyses show that the correlations of approaches to learning with academic achievement are low. However, only one study has controlled these correlations in the presence of intelligence. Our study investigates the incremental validity of the surface and deep approaches taking cognitive abilities as control and applied the multiple linear regression and CART regression tree method in a diversified sample of high school students from Minas Gerais, Brazil. We found a prediction of 20.37% and 35.20% of the outcome variance, through the linear regression and CART, respectively. Our results show that although cognitive abilities are more important than students’ approaches, the approaches have incremental validity and important roles as predictors of academic achievement.
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spelling doaj.art-26a8cf85baa14807a7eb247eea8da3fb2022-12-22T02:43:21ZspaPontificia Universidad Católica del PerúRevista de Psicología0254-92472223-37332022-07-01402Approaches to learning does matter to predict academic achievementCristiano Mauro Assis GomesHeitor Blesa FariasEnio Galinkin Jelihovschi Meta-analyses show that the correlations of approaches to learning with academic achievement are low. However, only one study has controlled these correlations in the presence of intelligence. Our study investigates the incremental validity of the surface and deep approaches taking cognitive abilities as control and applied the multiple linear regression and CART regression tree method in a diversified sample of high school students from Minas Gerais, Brazil. We found a prediction of 20.37% and 35.20% of the outcome variance, through the linear regression and CART, respectively. Our results show that although cognitive abilities are more important than students’ approaches, the approaches have incremental validity and important roles as predictors of academic achievement. https://revistas.pucp.edu.pe/index.php/psicologia/article/view/25502Students’ approaches to learningAchievementIntelligenceIncremental validityCART algorithm
spellingShingle Cristiano Mauro Assis Gomes
Heitor Blesa Farias
Enio Galinkin Jelihovschi
Approaches to learning does matter to predict academic achievement
Revista de Psicología
Students’ approaches to learning
Achievement
Intelligence
Incremental validity
CART algorithm
title Approaches to learning does matter to predict academic achievement
title_full Approaches to learning does matter to predict academic achievement
title_fullStr Approaches to learning does matter to predict academic achievement
title_full_unstemmed Approaches to learning does matter to predict academic achievement
title_short Approaches to learning does matter to predict academic achievement
title_sort approaches to learning does matter to predict academic achievement
topic Students’ approaches to learning
Achievement
Intelligence
Incremental validity
CART algorithm
url https://revistas.pucp.edu.pe/index.php/psicologia/article/view/25502
work_keys_str_mv AT cristianomauroassisgomes approachestolearningdoesmattertopredictacademicachievement
AT heitorblesafarias approachestolearningdoesmattertopredictacademicachievement
AT eniogalinkinjelihovschi approachestolearningdoesmattertopredictacademicachievement