scholarly journals DETERMINATION OF THE FACTORS AFFECTING STUDENTS’ SCIENCE ACHIEVEMENT LEVEL IN TURKEY AND SINGAPORE: AN APPLICATION OF QUANTILE REGRESSION MIXTURE MODEL

2020 ◽  
Vol 19 (2) ◽  
pp. 247-260
Author(s):  
Serpil Kiliç Depren
Keyword(s):  
Quantile Regression ◽  
Mixture Model ◽  
Science Achievement ◽  
International Student ◽  
Student Assessment ◽  
Finite Mixture ◽  
Achievement Level ◽  
Factors Affecting ◽  
International Student Assessment ◽  
Regression Mixture

In the last decade, the usage of advanced statistical models is growing rapidly in many different disciplines. However, the Quantile Regression Mixture Model (QRMIX), which is a developed approach of the Finite Mixture Model (FMM), is an applicable new method in the educational literature. The aim of the proposed study was to determine factors affecting students' science achievement using the QRMIX approach. To reach this aim, data of the Programme for International Student Assessment (PISA) survey, which has been conducted by the Organization Economic for Co-Operation and Development (OECD) every 3 years, was used. Dataset used in the research is composed of 6,115 students from Singapore, which is the top-performer country among the participant countries, and 5,895 students from Turkey. The results showed that the factors affecting students' science achievement and its importance on the achievement differentiated according to the achievement levels of the students. In conclusion, it was revealed that Turkish students with the lowest science achievement level should be supported with home possessions, perceived feedback, and environmental awareness and Singaporean students with the lowest achievement level should be supported with perceived feedback, enjoyment of science, and epistemological beliefs. Keywords: finite mixture models, Programme for International Student Assessment, quantile regression mixture models, science performance.

National Gross Domestic Product, Science Interest, and Science Achievement: A Direct Replication and Extension of the Tucker-Drob, Cheung, and Briley (2014) Study

2019 ◽  
Vol 30 (5) ◽  
pp. 776-788 ◽  
Author(s):  
Anqing Zheng ◽  
Elliot M. Tucker-Drob ◽  
Daniel A. Briley
Keyword(s):  
Gross Domestic Product ◽  
Low Socioeconomic Status ◽  
Science Achievement ◽  
International Student ◽  
Student Assessment ◽  
Domestic Product ◽  
Student Interest ◽  
Similar Data ◽  
Science Interest ◽  
International Student Assessment

We replicated the study by Tucker-Drob, Cheung, and Briley (2014), who found that the association between science interest and science knowledge depended on economic resources at the family, school, and national levels, using data from the 2006 Programme for International Student Assessment (PISA). In more economically prosperous families, schools, and nations, student interest was more strongly correlated with actual knowledge. Here, we investigated whether these results still held despite substantial changes to educational and economic systems over roughly a decade. Using similar data from PISA 2015 ( N = 537,170), we found largely consistent results. Students from more economically advantaged homes, schools, and nations exhibited a stronger link between interests and knowledge. However, these moderation effects were substantially reduced, and the main effect of science interest increased by nearly 25%, driven almost entirely by families of low socioeconomic status and nations with low gross domestic product. The interdependence of interests and resources is robust but perhaps weakening with educational progress.

scholarly journals PREDICTION OF STUDENTS’ SCIENCE ACHIEVEMENT: AN APPLICATION OF MULTIVARIATE ADAPTIVE REGRESSION SPLINES AND REGRESSION TREES

2018 ◽  
Vol 17 (5) ◽  
pp. 887-903 ◽  
Author(s):  
Serpil Kilic Depren
Keyword(s):  
Science Achievement ◽  
Student Assessment ◽  
Regression Trees ◽  
Machine Learning Algorithms ◽  
Multivariate Adaptive Regression Splines ◽  
Regression Splines ◽  
Factors Affecting ◽  
International Student Assessment ◽  
Adaptive Regression ◽  
Adaptive Regression Splines

Turkey is ranked at the 54th out of 72 countries in terms of science achievement in the Programme for International Student Assessment (PISA) survey conducted in 2015, which is a very big disappointment for that country. The aim of this research was to determine factors affecting Turkish students’ science achievements in order to identify the improvement areas using PISA 2015 dataset. To achieve this aim, Multivariate Adaptive Regression Splines (MARS) and Classification and Regression Trees (CART) approaches were used and these approaches were compared in terms of model accuracy statistics. Since Singapore was the top performer country in terms of science achievement in PISA 2015 survey, the analysis results of Turkey and Singapore were compared to each other to understand the differences. The results showed that MARS outperforms the CART in terms of measuring the prediction of students’ science achievement. Furthermore, the most important factors affecting science achievements were environmental optimism, home possessions and science learning time (minutes per week) for Turkey, while the index of economic, social and cultural status, environmental awareness and enjoyment of science for Singapore. Keywords: higher education, machine learning algorithms, PISA, science achievement.

scholarly journals Teacher-Directed Learning Approaches and Science Achievement: Investigating the Importance of Instructional Explanations in Australian Schools

2021 ◽  
Author(s):  
Dean Cairns ◽  
Shaljan Areepattamannil
Keyword(s):  
Science Achievement ◽  
International Student ◽  
Science Classroom ◽  
Student Assessment ◽  
Mediation Effect ◽  
Learning Approaches ◽  
Instructional Explanations ◽  
Significant Positive Association ◽  
International Student Assessment ◽  
Scientific Ideas

AbstractThis study investigated the relationships of teacher-directed approaches with science achievement in Australian schools. The data for this study were drawn from the Program for International Student Assessment (PISA) 2015 database and analysed using multilevel modelling (MLM). MLMs were estimated to test the contribution of each item to students’ science achievement scores and to estimate the mediation effect of teacher explanations on these relationships. Only explicit, teacher-directed practices demonstrated a significant, positive association with science achievement. The positive, significant nature of the item ‘the teacher explains scientific ideas’ (B = 29.61, p < 0.001) suggested that this practice should take place in all science lessons. In the mediation model, the explicit, teacher-directed approaches in the inquiry scale revealed a significant indirect effect on science achievement, through the process of the teacher explaining scientific ideas. This indicated that effective explanations also underpin other instructional approaches such as contextualised science learning. These findings, accompanied by an analysis of the teacher-directed items and their relationships to science outcomes, give teachers and policymakers clear guidance regarding the effective use of instructional explanations in the science classroom.

scholarly journals Examining Science Achievement in Chile: A Multilevel Model Approach

2021 ◽  
Vol 7 (2) ◽  
pp. 93-116
Author(s):  
Noelia Pacheco Diaz ◽  
Louis Rocconi
Keyword(s):  
Gender Gap ◽  
Science Achievement ◽  
International Student ◽  
School Administrators ◽  
Student Assessment ◽  
Occupational Status ◽  
Value Theory ◽  
Expectancy Value ◽  
International Student Assessment ◽  
And Performance

This study employed data from the 2015 Chilean sample of the Programme for International Student Assessment to examine the factors that influence science achievement and factors that may reduce the gender gap in science achievement. Our research was guided by Eccles’ Expectancy-Value Theory, which focused on motivational factors that influence gender differences in students’ achievement choices and performance. Our results indicate that socioeconomic status (SES), motivation, enjoyment of science, expected occupational status, school SES, and class size are related to higher science achievement. Also, anxiety was negatively associated with science achievement. Implications for Chilean policymakers and school administrators to improve Chilean girls’ science achievement are discussed.

scholarly journals A Partial Simulation Study of Phantom Effects in Multilevel Analysis of School Effects: The Case of School Socioeconomic Composition

2021 ◽  
pp. 004912412098619
Author(s):  
Hao Zhou ◽  
Xin Ma
Keyword(s):  
Academic Achievement ◽  
Hierarchical Linear Modeling ◽  
Science Achievement ◽  
International Student ◽  
Student Assessment ◽  
The United States ◽  
Linear Modeling ◽  
Real World Data ◽  
International Student Assessment ◽  
School Ses

Hierarchical linear modeling (HLM) is often used to estimate the effects of socioeconomic status (SES) on academic achievement at different levels of an educational system. However, if a prior academic achievement measure is missing in a HLM model, biased estimates may occur on the effects of student SES and school SES. Phantom effects describe the phenomenon in which the effects of student SES and school SES disappear once prior academic achievement is added to the model. In the present analysis, partial simulation (i.e., simulated data are used together with real-world data) was employed to examine the phantom effects of student SES and school SES on science achievement, using the national sample of the United States from the 2015 Programme for International Student Assessment. The results showed that the phantom effects of student SES and school SES are rather real. The stronger the correlation between prior science achievement and (present) science achievement, the greater the chance that the phantom effects occur.

Three Paradoxical Effects on Academic Self-Concept Across Countries, Schools, and Students

2019 ◽  
Vol 24 (3) ◽  
pp. 231-242 ◽  
Author(s):  
Herbert W. Marsh ◽  
Philip D. Parker ◽  
Reinhard Pekrun
Keyword(s):  
International Student ◽  
Student Assessment ◽  
Cross Cultural ◽  
Frame Of Reference ◽  
School Level ◽  
Self Concept ◽  
Positive Effects ◽  
International Student Assessment ◽  
Country Level ◽  
Starting School

Abstract. We simultaneously resolve three paradoxes in academic self-concept research with a single unifying meta-theoretical model based on frame-of-reference effects across 68 countries, 18,292 schools, and 485,490 15-year-old students. Paradoxically, but consistent with predictions, effects on math self-concepts were negative for: • being from countries where country-average achievement was high; explaining the paradoxical cross-cultural self-concept effect; • attending schools where school-average achievement was high; demonstrating big-fish-little-pond-effects (BFLPE) that generalized over 68 countries, Organisation for Economic Co-operation and Development (OECD)/non-OECD countries, high/low achieving schools, and high/low achieving students; • year-in-school relative to age; unifying different research literatures for associated negative effects for starting school at a younger age and acceleration/skipping grades, and positive effects for starting school at an older age (“academic red shirting”) and, paradoxically, even for repeating a grade. Contextual effects matter, resulting in significant and meaningful effects on self-beliefs, not only at the student (year in school) and local school level (BFLPE), but remarkably even at the macro-contextual country-level. Finally, we juxtapose cross-cultural generalizability based on Programme for International Student Assessment (PISA) data used here with generalizability based on meta-analyses, arguing that although the two approaches are similar in many ways, the generalizability shown here is stronger in terms of support for the universality of the frame-of-reference effects.

Are There Test Administrator Effects in Large-Scale Educational Assessments?

Methodology ◽  
2007 ◽  
Vol 3 (4) ◽  
pp. 149-159 ◽  
Author(s):  
Oliver Lüdtke ◽  
Alexander Robitzsch ◽  
Ulrich Trautwein ◽  
Frauke Kreuter ◽  
Jan Marten Ihme
Keyword(s):  
Large Scale ◽  
International Student ◽  
Student Assessment ◽  
Student Groups ◽  
Mathematics Scores ◽  
International Student Assessment ◽  
Sample Attrition ◽  
Educational Assessments ◽  
Test Administrator ◽  
Practical Implications

Abstract. In large-scale educational assessments such as the Third International Mathematics and Sciences Study (TIMSS) or the Program for International Student Assessment (PISA), sizeable numbers of test administrators (TAs) are needed to conduct the assessment sessions in the participating schools. TA training sessions are run and administration manuals are compiled with the aim of ensuring standardized, comparable, assessment situations in all student groups. To date, however, there has been no empirical investigation of the effectiveness of these standardizing efforts. In the present article, we probe for systematic TA effects on mathematics achievement and sample attrition in a student achievement study. Multilevel analyses for cross-classified data using Markov Chain Monte Carlo (MCMC) procedures were performed to separate the variance that can be attributed to differences between schools from the variance associated with TAs. After controlling for school effects, only a very small, nonsignificant proportion of the variance in mathematics scores and response behavior was attributable to the TAs (< 1%). We discuss practical implications of these findings for the deployment of TAs in educational assessments.

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