Master's Thesis
Enhancing resilience in education: An econometric study of pedagogical strategies
— 2024
Key information
Authors:
Supervisors:
Published in
July 9, 2024
Abstract
This study investigates the impact of various teaching strategies on student resilience while focusing on socioeconomically disadvantaged students, first-generation immigrants, and second-generation immigrants, using data from the PISA 2018 and TALIS 2018 databases. Employing multiple regression models, the study evaluates the significance of teaching approaches — Teacher Directed Learning, Cognitive Activation, Formative Assessment, and Student-Oriented Approaches — across four academic subjects: Mathematics, Reading, Science, and a composite Global measure. The results reveal that the Formative Assessment Approach positively influences resilience across all student groups, particularly first-generation immigrants, indicating its potential to promote equity in education. Conversely, the Cognitive Activation Approach shows a strong negative effect on the resilience of socioeconomically disadvantaged students, suggesting it is unsuitable for this demographic. The Teacher-Directed Learning Approach positively impacts the mathematics resilience of socioeconomically disadvantaged students, highlighting the need for targeted strategies. The study also identifies that the Student-Teacher Ratio is statistically irrelevant in explaining resilience, while socioeconomic status (ESCS) consistently proves to be a significant determinant across all models. Despite these findings, the study acknowledges several limitations, including the cross-sectional nature of the data, potential multicollinearity, and the constraints of variable selection. Overall, this research contributes to understanding how different teaching strategies can either mitigate or exacerbate educational inequities, offering insights for policymakers and educators aiming to foster more inclusive educational environments. Future research should address the identified limitations and expand the scope to include longitudinal data and additional contextual variables.
Publication details
Authors in the community:
Gabriel Gioia Ávila Oliveira
ist1101754
Supervisors of this institution:
Miguel Alves Pereira
ist176052
Fields of Science and Technology (FOS)
other-engineering-and-technologies - Other engineering and technologies
Publication language (ISO code)
eng - English
Rights type:
Embargo lifted
Date available:
April 18, 2025
Institution name
Instituto Superior Técnico