Exploring the relation between socio-economic status and reading achievement in PISA 2009 through an intercepts-and-slopes-as-outcomes paradigm

Jehangir, Khurrem; Glas, Cornelis A.W.; Berg, Stéphanie Martine van den

doi:10.1016/j.ijer.2015.02.002

Cited by 25 publications

(18 citation statements)

References 25 publications

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“…At school-level, private schools scored higher in reading literacy. This finding is consistent with other studies conducted on the effects of school type on students' achievements (Jehangir, Glas, & van den Berg, 2015). Not a surprising result to the context of Jordan (this is also applicable to many other countries in the region).…”

Section: Discussionsupporting

confidence: 92%

Reading Literacy and Learning Strategies in First Language Learning: A Multilevel Approach

Alhabahba¹,

Rabadi²,

Mahfoodh³

2017

IJEL

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This study documents an investigation of multilevel data from the 2009 Program for International Student Assessment to examine the reading literacy of 5,944 15-year-old students in Jordanian schools. A multilevel model was employed to examine the factors linked to students' reading literacy from both students' and schools' levels. At students' level, the study revealed that metacognition, elaboration, memorization, structuring, and scaffolding strategies were significant predictors of students' reading literacy. At schools' level, the study showed that school type, extracurricular activities, and teachers' behaviour were significant predictors of students' reading literacy. Practical implications and recommendations to research community at local and international levels are provided in this study.

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Section: Discussionsupporting

confidence: 92%

Reading Literacy and Learning Strategies in First Language Learning: A Multilevel Approach

Alhabahba¹,

Rabadi²,

Mahfoodh³

2017

IJEL

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“…In this model, about 41 per cent of the variance was attributed to between-school differences and 59 per cent to within-school differences. This means that apart from the student characteristics that shaped mathematics achievement, there was a sizeable portion of the total variance in mathematics achievement at the school level, something that many authors have previously stressed, suggesting remarkable differences in students' performance between schools (Jehangir et al, 2015;Martins & Veiga, 2010).…”

Section: Interpretation Of the Final Modelmentioning

confidence: 97%

“…However, when SES is evaluated at school-level, results should not be interpreted as if they represented individual SES, hence measures should be taken to avoid an ecological fallacy, the transfer of individual-level inferences to the school-level, assuming that findings at the individual-level can depict between-school relationships (Jehangir, Glas, & van den Berg, 2015;Sirin, 2005). For the purposes of this study, multilevel analysis is used, because it can simultaneously estimate the complexity of student-and school-level effects, thereby preventing this ecological fallacy (Jehangir et al, 2015;Snijders & Bosker, 2012).…”

Section: Ses At the School Levelmentioning

confidence: 99%

The role of students' self-beliefs, motivation and attitudes in predicting mathematics achievement: A multilevel analysis of the Programme for International Student Assessment data

Pitsia

Biggart

Karakolidis

2017

Learning and Individual Differences

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Non-cognitive factors have been considered as particularly important aspects in shaping students' academic achievement. The current study aimed to examine a number of these factors in relation to the prediction of mathematics achievement among a representative sample of students in Greece. The sample consisted of 5,125 15-year-old students who participated in the Programme for International Student Assessment (PISA) 2012. The study considered the extent to which students' mathematics self-beliefs, motivation towards mathematics and attitudes towards school contributed to the prediction of their mathematics achievement. Multilevel modelling assessed both individual and school level variation, revealing that students' mathematics self-efficacy, anxiety, self-concept, instrumental motivation and attitudes towards school were statistically significant predictors of their mathematics achievement, even after controlling for their gender and school socioeconomic status (SES). Moreover, students were found to differ in the levels of their self-beliefs, motivation and attitudes based on their gender.

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“…These include studies from the US (Alexander & Aaron, 1985;Gamoran, 1996;Levin, 1998;C. Lubienski & Lubienski, 2014; S. T. Lubienski & Lubienski, 2006;Witte, 1992Witte, , 1998, the UK (Gorard, 2006), as well as cross-national studies (Benito et al, 2014;Jehangir, Glas, & van den Berg, 2015;Mostafa, 2010).…”

Section: Introductionmentioning

confidence: 99%

How do learning environments vary by school sector and socioeconomic composition? Evidence from Australian students

Perry

Lubienski

Ladwig

2016

Australian Journal of Education

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We examine how students’ perspectives of their learning environments vary between private and public schools in Australia. Previous research has shown that educational outcomes do not vary by school sector in most countries after controlling for student social background. Little is known, however, about the ways in which different students’ educational experiences vary across sectors. Australia is a good case study for examining this question, because it has one of the largest private school sectors in the world. We used a large and nationally representative dataset to compare sector differences across five measures of learning environments while accounting for the average socioeconomic composition of the school. Very few differences large enough to be considered educationally substantive were found between sectors. On two measures, however, student perspectives varied substantially within sectors and across school socioeconomic contexts. Overall, classroom disciplinary climate varied the most across school sectors and socioeconomic contexts, and teacher scaffolding and structuring strategies varied the least.

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Exploring the relation between socio-economic status and reading achievement in PISA 2009 through an intercepts-and-slopes-as-outcomes paradigm

Cited by 25 publications

References 25 publications

Reading Literacy and Learning Strategies in First Language Learning: A Multilevel Approach

Reading Literacy and Learning Strategies in First Language Learning: A Multilevel Approach

The role of students' self-beliefs, motivation and attitudes in predicting mathematics achievement: A multilevel analysis of the Programme for International Student Assessment data

How do learning environments vary by school sector and socioeconomic composition? Evidence from Australian students

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