Investigation of the Individual Characteristics that Predict Academic Resilience

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  • Süleyman AVCI



Academic Resilience, PISA, Individual Characteristics


The percentage of students who have lower academic achievement than their peers due to their socio-economical disadvantages is globally accepted as an indicator of inequality. Some students, despite their disadvantages, are as successful as their advantaged peers. The family and individual characteristics, as well as academic experiences, of these students, who are referred to as academically resilient, provide useful information to the institutions that work to increase the academic success levels of other disadvantaged students. Accordingly, this study aims to determine the individual characteristics of academically resilient students with a focus on the PISA Turkey results. In line with the OECD criteria, an equal number of academically resilient (N = 214) and academically disadvantaged students participated in the study. Students who’s economic, social, and cultural index values are amongst the bottom 25% were considered to be disadvantaged, and those who performed level 3 and above in reading proficiency were regarded to be successful. Eighteen individual characteristics measured within the scope of PISA research were included in the study as independent variables. Binary logistic regression analysis was used in the analysis of the data. The regression model created in line with the findings was found to predict 67 percent of the variance in academic resilience and make an accurate classification of 85 percent. The predictors of academic resilience, in order of their power, are grade repetition, use of metacognitive learning strategies (understanding, summarizing, evaluating credibility), reading for enjoyment, attitude towards academic competition, self-efficacy, and the desired occupation.

Author Biography

Süleyman AVCI

Corresponding Author: Süleyman Avcı,

Süleyman AVCI


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How to Cite

AVCI, S. (2022). Investigation of the Individual Characteristics that Predict Academic Resilience. International Journal of Contemporary Educational Research, 9(3), 543–556.