The Bayesian Model Averaging (BMA) Approach for Determining the Factors Affecting the Achievement of Students with Low Socioeconomic Status

Derya Topdağ; Ebru Çağlayan Akay

Article Details

The Bayesian Model Averaging (BMA) Approach for Determining the Factors Affecting the Achievement of Students with Low Socioeconomic Status

Authors:

Derya Topdağ | Ebru Çağlayan Akay

Publisher:

Istanbul University

Main Topics:

Ekonometri (Diğer)

Journal:

EKOIST Journal of Econometrics and Statistics Issue 40, pp.1-11

Document Type:

Article

Publication Date:

6/2024

Document Language:

Turkish

Document ID (Org No.):

2001324473

pISSN:

2651-396X

Keywords:

Abstract:

 Analyzing the relationship between academic achievement and socioeconomic background is an important subject in educational research. Even though the percentage of students with low socioeconomic status in Türkiye is higher than the international average, these students average mathematics achievement scores can be shown to relatively higher than international average scores. This study aims to identify the variables that influence the mathematics achievement of students with low socioeconomic status in Türkiye using the small sample size and modeling flexibility provided by the Bayesian approach. Data were employed for this purpose from the 2019 International Survey of Mathematics and Science Trends TIMSS 8th-grade mathematics assessment. The study uses the Bayesian model averaging BMA approach to determine which variables should be included in the model when working with large-scale educational data and a large number of independent variables. According to the Bayesian model averaging results, the number of books at home, students academic expectations, sense of belonging to school, attitudes toward mathematics, absenteeism, and exposure to bullying are the strongest predictors of mathematics achievement. The findings from this study show the mathematics failure of students with low socioeconomic status to be closely associated with negative attitudes toward school and mathematics courses, exposure to bullying, and greater frequency of homework. Furthermore, the study has determined mothers educational level to have no influence on the mathematics achievement of students with low socioeconomic status, while gender does have an effect in terms of fathers education level. The results show students with low socioeconomic status to be impacted by the components of inequalities inside and outside of school. Consequently, education policies are expected to provide equitable opportunities for students with low socioeconomic status by taking socioeconomic inequalities into account.

 Analyzing the relationship between academic achievement and socioeconomic background is an important subject in educational research. Even though the percentage of students with low socioeconomic status in Türkiye is higher than the international average, these students average mathematics achievement scores can be shown to relatively higher than international average scores. This study aims to identify the variables that influence the mathematics achievement of students with low socioeconomic status in Türkiye using the small sample size and modeling flexibility provided by the Bayesian approach. Data were employed for this purpose from the 2019 International Survey of Mathematics and Science Trends TIMSS 8th-grade mathematics assessment. The study uses the Bayesian model averaging BMA approach to determine which variables should be included in the model when working with large-scale educational data and a large number of independent variables. According to the Bayesian model averaging results, the number of books at home, students academic expectations, sense of belonging to school, attitudes toward mathematics, absenteeism, and exposure to bullying are the strongest predictors of mathematics achievement. The findings from this study show the mathematics failure of students with low socioeconomic status to be closely associated with negative attitudes toward school and mathematics courses, exposure to bullying, and greater frequency of homework. Furthermore, the study has determined mothers educational level to have no influence on the mathematics achievement of students with low socioeconomic status, while gender does have an effect in terms of fathers education level. The results show students with low socioeconomic status to be impacted by the components of inequalities inside and outside of school. Consequently, education policies are expected to provide equitable opportunities for students with low socioeconomic status by taking socioeconomic inequalities into account.

 Analyzing the relationship between academic achievement and socioeconomic background is an important subject in educational research. Even though the percentage of students with low socioeconomic status in Türkiye is higher than the international average, these students average mathematics achievement scores can be shown to relatively higher than international average scores. This study aims to identify the variables that influence the mathematics achievement of students with low socioeconomic status in Türkiye using the small sample size and modeling flexibility provided by the Bayesian approach. Data were employed for this purpose from the 2019 International Survey of Mathematics and Science Trends TIMSS 8th-grade mathematics assessment. The study uses the Bayesian model averaging BMA approach to determine which variables should be included in the model when working with large-scale educational data and a large number of independent variables. According to the Bayesian model averaging results, the number of books at home, students academic expectations, sense of belonging to school, attitudes toward mathematics, absenteeism, and exposure to bullying are the strongest predictors of mathematics achievement. The findings from this study show the mathematics failure of students with low socioeconomic status to be closely associated with negative attitudes toward school and mathematics courses, exposure to bullying, and greater frequency of homework. Furthermore, the study has determined mothers educational level to have no influence on the mathematics achievement of students with low socioeconomic status, while gender does have an effect in terms of fathers education level. The results show students with low socioeconomic status to be impacted by the components of inequalities inside and outside of school. Consequently, education policies are expected to provide equitable opportunities for students with low socioeconomic status by taking socioeconomic inequalities into account.

 Akademik başarı ve sosyoekonomik arka plan arasındaki ilişkinin analizi, eğitim araştırmalarında önemli konulardan biridir. Türkiyede düşük sosyoekonomik statüye sahip öğrenci yüzdesinin uluslararası ortalamanın üstünde olmasına rağmen, bu öğrencilerin özellikle ortalama matematik başarı puanlarının uluslararası ortalama puanına göre nispeten yüksek olduğu görülmektedir. Bu makalenin amacı, Türkiyede düşük sosyoekonomik statüye sahip öğrencilerin matematik başarısını etkileyen değişkenleri Bayesyen yaklaşımın sunduğu küçük örneklem boyutu ve modelleme esnekliğinden yararlanarak belirlemektir. Çalışmanın verileri Uluslararası Matematik ve Fen Eğilimleri Araştırması TIMSS 2019 sekizinci sınıf matematik değerlendirmesinden elde edilmiştir. Çalışmada, çok sayıda bağımsız değişken içeren büyük ölçekli eğitim verileriyle çalışırken hangi değişkenlerin modele dahil edilmesi gerektiğini belirlemek için Bayesyen model ortalama BMA yaklaşımı kullanılmıştır. Bayesyen model ortalama sonuçlarına göre, evdeki kitap sayısı, öğrencinin akademik beklentisi, okula ait hissetme, matematiğe karşı tutum, devamsızlık ve zorbalığa maruz kalma, matematik performansının en önemli açıklayıcıları olarak tespit edilmiştir. Düşük sosyoekonomik statüye sahip öğrencilerin matematik başarısızlığının okula ve matematik dersine karşı olumsuz tutumlar, zorbalığa maruz kalma ve artan ödev sıklığı ile yakından ilişkili olduğu belirlenmiştir. Ayrıca düşük sosyoekonomik statüye sahip öğrencilerin matematik başarısında annenin eğitim seviyesi ve cinsiyetin etkisi olmadığı tespit edilmiştir. Sonuçlar düşük sosyoekonomik statüye sahip öğrencilerin okul içinde ve okul dışındaki eşitsizlik unsurlarından etkilendiğini göstermektedir. Sonuç olarak, eğitim politikalarının sosyoekonomik eşitsizlikleri dikkate alarak düşük sosyoekonomik statüye sahip öğrenciler için fırsat eşitliği sunması beklenmektedir.

Article Details

The Bayesian Model Averaging (BMA) Approach for Determining the Factors Affecting the Achievement of Students with Low Socioeconomic Status

Authors:

Derya Topdağ | Ebru Çağlayan Akay

Publisher:

Istanbul University

Main Topics:

Ekonometri (Diğer)

Journal:

EKOIST Journal of Econometrics and Statistics Issue 40, pp.1-11

Document Type:

Article

Publication Date:

6/2024

Document Language:

Turkish

Document ID (Org No.):

2001324473

pISSN:

2651-396X

Bayesian model averaging

BMA

TIMSS

mathematics achievement

low socioeconomic statusBayesyen Model Ortalama (BMA)

TIMSS

Matematik Başarısı

Düşük Sosyoekonomik Statü (low-SES)

Issues

Article Details

Authors: Derya Topdağ | Ebru Çağlayan Akay

Publisher: Istanbul University

Main Topics: Ekonometri (Diğer)

Journal: EKOIST Journal of Econometrics and Statistics Issue 40, pp.1-11

Document Type: Article

Publication Date: 6/2024

Document Language: Turkish

Document ID (Org No.): 2001324473

pISSN: 2651-396X

Issues

Authors:

Derya Topdağ | Ebru Çağlayan Akay

Publisher:

Istanbul University

Main Topics:

Ekonometri (Diğer)

Journal:

EKOIST Journal of Econometrics and Statistics Issue 40, pp.1-11

Document Type:

Article

Publication Date:

6/2024

Document Language:

Turkish

Document ID (Org No.):

2001324473

pISSN:

2651-396X