Examining the Effective Variables on Classification of School's Success through PISA 2012 Turkey Data

Özkan, Özer

doi:10.15345/iojes.2016.02.011

Cited by 4 publications

(7 citation statements)

References 23 publications

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“…When the results concerning the variables chosen at the school level are examined, it is seen that they are consistent with those reported in the field literature in terms of demonstrating the effect of the quality of school and educational resources (Acar and Öğretmen, 2012;Archibald, 2006;Nonoyama, 2005;Oral and Mcgivney, 2013;Özer-Özkan, 2016) on students" achievements. Hanushek (1997) examined 377 studies taking students" family features into consideration but did not find a strong and consistent relationship between student achievement and school resources.…”

Section: Discussion Conclusion and Suggestionssupporting

confidence: 79%

“…This situation underlines the necessity of considering the effect of school features on student success. In the literature regarding school features, it is confirmed that the quality of school and educational resources (Acar and Öğretmen, 2012;Archibald, 2006;Nonoyama, 2005;Oral and Mcgivney, 2013;Özer-Özkan, 2016) affect students" achievements. Hanushek (1997) conducted a meta-analysis of 377 studies and reported that taking family characteristics into consideration, there was no strong and consistent relationship between student achievement and school resources.…”

Section: Introductionmentioning

confidence: 95%

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Determining the Relationships between Selected Variables and Latent Classes in Students’ PISA Achievement

Yalçın¹

2017

International Journal of Research in Education and Science

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Section: Discussion Conclusion and Suggestionssupporting

confidence: 79%

Section: Introductionmentioning

confidence: 95%

Determining the Relationships between Selected Variables and Latent Classes in Students’ PISA Achievement

Yalçın¹

2017

International Journal of Research in Education and Science

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“…Nevertheless, student behaviours hindering learning decreased reading literacy; teacher behaviours hindering learning increased reading literacy. Findings related to negative relationship between student behaviours hindering learning were parallel to the literature (Özer- Özkan, 2016;Üstün, Özdemir, Cansız, & Cansız, 2019). On the other hand, findings related to positive relationship between teacher behaviour hindering learning served blur in the literature since the literature has studies showing positive relation, negative relation, and no relation.…”

Section: Discussionsupporting

confidence: 70%

Examination of Turkey’s PISA 2018 reading literacy scores within student-level and school-level variables

Ertem

2021

Participatory Educational Research

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The purpose of the current study was to investigate both student-level and school-level factors influencing reading literacy of students in Turkey by using PISA 2018 data. The study focused on reading literacy since the main subject of PISA 2018 was selected as reading literacy. The design of the study is a correlational research examining the relationship between student and school variables and reading literacy. The stratified random sample consisted of 6890 15-year students from 186 different schools. Data coming from PISA 2018 dataset were analysed by Hierarchical Linear Modelling (HLM) at student and school levels. Student-level variables of disciplinary climate in test language lessons, enjoyment of reading, information and community technologies (ICT) competence, parental emotional support, perceived discriminating climate, and perceived cooperation significantly predicted reading literacy, while reading literacy was also predicted by school-level variables of proportion of parents involved in the school, shortage of educational material, student behaviour hindering learning, and teacher behaviour hindering learning. Fifty-seven percent of variance between reading literacy scores of the students were caused by differences between schools. Student-level variables which are disciplinary climate in test language lessons, enjoyment of reading, ICT competence, parental emotional support, perceived discriminating climate, and perceived cooperation significantly predicted reading literacy. On the other hand, school-level variables predicting reading literacy significantly were proportion of parents involved in the school, shortage of educational material, student behaviour hindering learning, and teacher behaviour hindering learning. By considering results of the current study, collaboration between school stakeholders is recommended to increase performance of the students.

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“…Öğrenciyle ilişkili faktörlerin matematik okuryazarlığını yüksek düzeyde ve pozitif etkilediği saptanmıştır. Bu sonuç literatürdeki diğer çalışmalarla tutarlıdır (Özer Özkan, 2016;Liu, Damme, Gielen ve Noortgate, 2015;Özkan, 2015;İş Güzel, 2014;Yıldırım, 2012;Alacacı ve Erbaş, 2010;Marks, Cresswell ve Ainley, 2007;Wöbmann, 2003;Kurul Tural, 2002). Ancak bazı ülkelerde farklı sonuçların elde edildiği de görülmektedir.…”

Section: Sonuç Ve öNeri̇lerunclassified

“…Literatürde de öğretmenlerin öğrencileri ile ilgilenerek, öğrencilerinin başarısına olan pozitif etkisinin belirlendiği çalışmalar da bu araştırmanın sonucunu desteklemektedir (Yılmaz 2006;Miller, 2000). Ancak literatürdeki bazı çalışmalarda okul iklimini etkileyen öğretmenle ilişkili faktörlerin PISA matematik okuryazarlığı üzerinde manidar bir etkisinin olmadığı (Özer Özkan, 2016;Liu, Damme, Gielen ve Noortgate, 2015;Areepattamannil, 2014;Huang ve Sebastian, 2014) veya negatif yönde etkilediği (İş Güzel, 2014;Huang ve Sebastian, 2014;Polidano, Hanel ve Buddelmeyer, 2013) görülmektedir.…”

Section: Sonuç Ve öNeri̇lerunclassified

PISA 2012 Türkiye Örnekleminde Okul Özelliklerinin Matematik Okuryazarlığına Etkisi

Yildirim¹,

Şahin²,

BAŞARAN³

2017

İlköğretim Online

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ÖZ. Bu araştırmanın amacı okul iklimi (öğretmenin odağı ve morali, okul iklimini etkileyen öğrenciyle ve öğretmenle ilişkili faktörler)ve kaynaklarının (okulun eğitimsel kaynaklarının kalitesi, fiziksel altyapının kalitesi) Türkiye'deki 15 yaş grubu öğrencilerin PISA 2012 matematik okuryazarlığına etkisini incelemektir ve araştırma ilişkisel bir araştırmadır. Araştırmanın çalışma grubunu PISA 2012'ye Türkiye'den katılan 170 okul ve 4848 öğrenci oluşturmaktadır. Araştırma, PISA 2012 Türkiye uygulaması kapsamında 15 yaş grubundaki öğrencilere uygulanan matematik okuryazarlığı testi ve okul yöneticilerine uygulanan okul anketinden elde edilen veriler üzerinden yürütülmüştür. Veri analizinde robust maximum likelihood parametre kestirim yöntemine dayalı yol analizi ve LISREL 8.8 programı kullanılmıştır. Kurulan modelde en yüksek yol katsayının okul iklimiyle ilişkili öğretmen faktörleri indeksi ve okul iklimiyle ilişkili öğrenci faktörleri indeksi arasında olduğu; en düşük katsayının ise öğretmenin odağı indeksi ve okul iklimini etkileyen öğretmen faktörleri indeksi arasında olduğu gözlenmiştir ve tüm yol katsayıları pozitif ve anlamlı bulunmuştur. Ayrıca bu yol katsayılarının orta ve yüksek etki büyüklüğüne sahip olduğu görülmüştür. Modele ilişkin uyum indeksleri mükemmel uyuma işaret etmektedir. Bu bağlamda modele dayalı olarak okul iklimi ve okul kaynakları indekslerinin matematik okuryazarlığında etkili olduğu sonucuna varılmıştır. Anahtar Sözcükler: Yol Analizi, PISA 2012, Okul İklimi, Okul Kaynakları, Matematik Okuryazarlığı ABSTRACT. The aim of this paper was to examine the impact of school climate (teacher's focus and morale, student and teacher-related factors affecting school climate) and resources (quality of the school's educational resources, the quality of physical infrastructure) in the PISA 2012 mathematics literacy for 15 years-old students in Turkey and this paper was correlational research. Research group was consisted of 170 schools and 4848 students, which constitutes PISA 2012 from Turkey. The research was conducted mathematics literacy test, which was administered to 15-years-old students and school questionnaires, which was administered to school administrators in context of PISA 2012 Turkey. LISREL 8.8 computer program and path analysis method with robust maximum likelihood parameter estimation method was used in the data analysis. It was observed that the highest path coefficient was between school climate related teacher factors index and school climate related student factors index and the lowest coefficient between teachers focus index and school climate related teacher factor index was observed. All path coefficient in the model was founded positively and significantly. Thesecoefficients had been medium and high effect size. In addition, the fit indices for the model was shown that the model had perfect fit. In this context, it was concluded that school climate and school resources index was effective in mathematics literacy. Keywords: Path Analysis, PISA 2012, Schools Resources, School ...

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Examining the Effective Variables on Classification of School's Success through PISA 2012 Turkey Data

Cited by 4 publications

References 23 publications

Determining the Relationships between Selected Variables and Latent Classes in Students’ PISA Achievement

Determining the Relationships between Selected Variables and Latent Classes in Students’ PISA Achievement

Examination of Turkey’s PISA 2018 reading literacy scores within student-level and school-level variables

PISA 2012 Türkiye Örnekleminde Okul Özelliklerinin Matematik Okuryazarlığına Etkisi

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