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Bezek Güre, Özlem; Sevgin, Hikmet; Kayri, Murat – International Journal of Contemporary Educational Research, 2023
The research aims to determine the factors affecting PISA 2018 reading skills using the Random Forest and MARS methods and to compare their prediction abilities. This study used the information from 5713 students, 2838 (49.7%) male and 2875 (50.3%) female, in the PISA 2018 Turkey. The analysis shows the MARS method performed better than the Random…
Descriptors: Achievement Tests, International Assessment, Secondary School Students, Foreign Countries
Tao Jiang; Hai Feng Qian; Fu Qiang Li; Tai Jun Wang – International Journal of Science Education, 2025
The education system strives to help students from low-income families achieve academic success. Academic resilience is related to not only individuals but also classrooms and schools. This study aimed to construct a comprehensive resilience model in science domains that presents the image of resilient students and describes the mechanisms by…
Descriptors: Classification, Secondary School Students, Resilience (Psychology), Academic Achievement
Bernardo, Allan B. I.; Cordel, Macario O., II; Lucas, Rochelle Irene G.; Teves, Jude Michael M.; Yap, Sashmir A.; Chua, Unisse C. – Education Sciences, 2021
Filipino students ranked last in reading proficiency among all countries/territories in the PISA 2018, with only 19% meeting the minimum (Level 2) standard. It is imperative to understand the range of factors that contribute to low reading proficiency, specifically variables that can be the target of interventions to help students with poor…
Descriptors: Foreign Countries, English (Second Language), Reading Ability, Artificial Intelligence
Simsek, Mertkan – International Journal of Technology in Education, 2022
Considering the large volume of PISA data, it is expected that data mining will often be assisted in making PISA data more meaningful. Studies show that different dimensions of ICT may reveal different relationships for mathematics achievement. The purpose of this article is to evaluate the success of the decision tree classification algorithms in…
Descriptors: Predictor Variables, Mathematics Achievement, Achievement Tests, Foreign Countries
Bilican-Demir, Safiye – International Online Journal of Education and Teaching, 2021
The purpose of the study was to determine the characteristics of teachers who were effective in classifying low- and high-performing schools in PISA 2012 for Singapore. The TALIS 2013 teacher survey was used to identify the variables, and the data were obtained from the OECD official website. All schools participating in the PISA 2012 were ranked…
Descriptors: Teacher Characteristics, Teacher Effectiveness, School Effectiveness, Academic Achievement
Karadavut, Tugba; Cohen, Allan S.; Kim, Seock-Ho – International Journal of Assessment Tools in Education, 2019
Covariates have been used in mixture IRT models to help explain why examinees are classed into different latent classes. Previous research has considered manifest variables as covariates in a mixture Rasch analysis for prediction of group membership. Latent covariates, however, are more likely to have higher correlations with the latent class…
Descriptors: Item Response Theory, Classification, Correlation, International Assessment
Avci, Süleyman – International Journal of Contemporary Educational Research, 2022
The 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,…
Descriptors: Individual Characteristics, Academic Achievement, Achievement Gap, Socioeconomic Status
Aksu, Gokhan; Reyhanlioglu Keceoglu, Cigdem – Eurasian Journal of Educational Research, 2019
Purpose: In this study, Logistic Regression (LR), CHAID (Chi-squared Automatic Interaction Detection) analysis and data mining methods are used to investigate the variables that predict the mathematics success of the students. Research Methods: In this study, a quantitative research design was employed during the data collection and the analysis…
Descriptors: Regression (Statistics), Data Collection, Information Retrieval, Predictor Variables
Yalcin, Seher – International Journal of Progressive Education, 2018
In this study, it is aimed to distinguish the reading skills of students participating in PISA 2015 application into multi-level latent classes at the student and country level. Furthermore, it is aimed to examine how the clusters emerged at country-level is predicted by variables as students have the information and communication technology (ICT)…
Descriptors: Reading Achievement, Reading Skills, Classification, Information Technology
Poder, Kaire; Kerem, Kaie; Lauri, Triin – Journal of School Choice, 2013
We seek out the good institutional features of the European choice policies that can enhance both equity and efficiency at the system level. For causality analysis we construct the typology of 28 European educational systems by using fuzzy-set analysis. We combine five independent variables to indicate institutional features of school choice…
Descriptors: School Choice, Predictor Variables, Incentives, Classification
Castejón, Alba; Zancajo, Adrián – European Educational Research Journal, 2015
This article focuses on analysing the effect of educational differentiation policies of OECD educational systems on socioeconomically disadvantaged students, based on data from PISA 2009. The analysis is conducted on the basis of a definition of two subgroups of disadvantaged students: those that achieve high scores, and those obtaining scores…
Descriptors: Disadvantaged, Educational Policy, Educational Practices, Individualized Programs
Eliciting Engagement in the High School Classroom: A Mixed-Methods Examination of Teaching Practices
Cooper, Kristy S. – American Educational Research Journal, 2014
This case study analyzes how and why student engagement differs across 581 classes in one diverse high school. Factor analyses of surveys with 1,132 students suggest three types of engaging teaching practices--connective instruction, academic rigor, and lively teaching. Multilevel regression analyses reveal that connective instruction predicts…
Descriptors: Teaching Methods, High School Students, Learner Engagement, Regression (Statistics)
National Centre for Vocational Education Research (NCVER), 2010
The Longitudinal Surveys of Australian Youth (LSAY) is a research program that tracks young people as they move from school into further study, work and other destinations. This "User guide" has been developed for users of the LSAY data. The guide endeavours to consolidate existing technical documentation and other relevant information…
Descriptors: Longitudinal Studies, Youth, Foreign Countries, Guides
Perry, Laura – European Education, 2009
This article examines equity in national systems of education in terms of differences in student outcomes, as measured by mathematics achievement scores on Programme for International Student Assessment (PISA) 2003. The author uses four measures for assessing equity in student outcomes: (1) the strength of the relationship between student…
Descriptors: Privatization, Equal Education, School Choice, Mathematics Achievement