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Influence of Contextual Variables on Educational Performance: A Study Using Hierarchical Segmentation Trees

Author

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  • Jesús García-Jiménez

    (Department of Educational Research Methods and Diagnostics, Facultad de Ciencias de la Educación, Universidad de Sevilla, 41013 Sevilla, Spain)

  • Javier Rodríguez-Santero

    (Department of Educational Research Methods and Diagnostics, Facultad de Ciencias de la Educación, Universidad de Sevilla, 41013 Sevilla, Spain)

  • Juan-Jesús Torres-Gordillo

    (Department of Educational Research Methods and Diagnostics, Facultad de Ciencias de la Educación, Universidad de Sevilla, 41013 Sevilla, Spain)

Abstract

The general objective of this study is to explore the relationship between students’ contextual characteristics and their performance in mathematical reasoning (MR) and linguistic comprehension (LC) skills. The census data from the ESCALA ( ES critura, CA lculo y L ectura en A ndalucía) tests developed by Agencia Andaluza de Evaluación Educativa (AGAEVE) in 2017 were used. These tests are carried out in the second year of primary school in the Autonomous Community of Andalusia (Spain). These data have been analysed through the data mining technique known as segmentation trees, using the CRT (Classification and regression trees) algorithm for each of the skills. This has allowed the detection of the high influence of social and cultural status (ESCS) and familial expectations regarding academic performance in both tests. In addition, it allows us to point out that there are different interactions between contextual characteristics and their relationship to performance in MR and LC. These results have made it possible to establish groups of students who may be at risk of not reaching the minimum required levels. Some characteristics of at-risk students are low ESCS, low family expectations or being born in the last six months of the year. The detection of at-risk profiles could contribute to the optimisation of the performance of these groups by creating specific plans.

Suggested Citation

  • Jesús García-Jiménez & Javier Rodríguez-Santero & Juan-Jesús Torres-Gordillo, 2020. "Influence of Contextual Variables on Educational Performance: A Study Using Hierarchical Segmentation Trees," Sustainability, MDPI, vol. 12(23), pages 1-10, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:23:p:9933-:d:452331
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    References listed on IDEAS

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    1. Oecd, 2014. "Does Homework Perpetuate Inequities in Education?," PISA in Focus 46, OECD Publishing.
    2. Demetriou, Andreas & Kazi, Smaragda & Makris, Nikolaos & Spanoudis, George, 2020. "Cognitive ability, cognitive self-awareness, and school performance: From childhood to adolescence," Intelligence, Elsevier, vol. 79(C).
    3. Stoet, Gijsbert & Geary, David C., 2017. "Students in countries with higher levels of religiosity perform lower in science and mathematics," Intelligence, Elsevier, vol. 62(C), pages 71-78.
    4. Fernandes, Eduardo & Holanda, Maristela & Victorino, Marcio & Borges, Vinicius & Carvalho, Rommel & Erven, Gustavo Van, 2019. "Educational data mining: Predictive analysis of academic performance of public school students in the capital of Brazil," Journal of Business Research, Elsevier, vol. 94(C), pages 335-343.
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    Cited by:

    1. Carla Ortiz-de-Villate & Javier Rodríguez-Santero & Juan-Jesús Torres-Gordillo, 2021. "Contextual, Personal and Family Factors in Explaining Academic Achievement: A Multilevel Study," Sustainability, MDPI, vol. 13(20), pages 1-13, October.
    2. Inés Lucas-Oliva & Jesús García-Jiménez & Juan-Jesús Torres-Gordillo & Javier Rodríguez-Santero, 2022. "Equity and Parity in Primary Education: A Study on Performance in Language and Mathematics Using Hierarchical Linear Models," Sustainability, MDPI, vol. 14(19), pages 1-17, September.

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