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Autor/inAvci, Süleyman
TitelInvestigation of the Individual Characteristics that Predict Academic Resilience
QuelleIn: International Journal of Contemporary Educational Research, 9 (2022) 3, S.543-556 (15 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationORCID (Avci, Süleyman)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
SchlagwörterIndividual Characteristics; Academic Achievement; Achievement Gap; Socioeconomic Status; Disadvantaged; Resilience (Psychology); Foreign Countries; Achievement Tests; Secondary School Students; International Assessment; Reading Achievement; Classification; Grade Repetition; Metacognition; Learning Strategies; Recreational Reading; Student Attitudes; Competition; Self Efficacy; Occupational Aspiration; Predictor Variables; Turkey; Program for International Student Assessment
AbstractThe percentage of students with 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 and 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, focusing on the PISA Turkey results. In line with the OECD criteria, an equal number of academically resilient (N=214) and academically disadvantaged (N=214) students participated in the study. Students whose economic, social, and cultural index values are amongst the bottom 25% were considered to be disadvantaged, and those who performed at 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. A binary logistic regression analysis was used in the analysis of the data. The regression model created in line with the findings predicted 67 percent of the variance in academic resilience and made an accurate classification of 85 percent. In order of their power, the predictors of academic resilience 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. (As Provided).
AnmerkungenInternational Journal of Contemporary Educational Research. e-mail: ijceroffice@gmail.com; Web site: http://ijcer.net
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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