Hybrid Regression Analysis of Predictors of Teachers' ICT Use in Teaching Practices: Evidence from ICILS

Kaan Batı; Şeyma Irmak

Makale detayları

Hybrid Regression Analysis of Predictors of Teachers' ICT Use in Teaching Practices: Evidence from ICILS

Yazarlar:

Kaan Batı | Şeyma Irmak

Yayıncı:

Kafkas University

Ana Başlıklar:

In-Service Training | Educational Technology and Computing | Learning Analytics | Teacher and Student Wellbeing

Dergi:

e-Kafkas Journal of Educational Research Vol.12 Issue 2, pp.412-427

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001354130

pISSN:

2148-8940

Anahtar kelimeler:

Özet:

 The effective integration of Information and Communication Technology ICT in education is crucial for student success in the digital age, and large-scale international assessments provide valuable data for understanding and improving these practices. This study investigates the factors influencing teachers ICT integration in teaching using the ICILS 2018 dataset. The study combines traditional methods, such as multiple linear regression, with machine learning techniques like the random forest algorithm, to comprehensively understand the factors driving teachers ICT use. The findings reveal that the models successfully explained a significant portion of the variance in teachers ICT practices. The random forest analysis identified country context as the most influential predictor, followed by teachers positive views on the benefits of ICT, teacher collaboration, ICT self-efficacy, and experience with online lessons. Factors such as experience in preparing online materials and teacher age had a moderate influence, while access to computer resources and gender showed minimal impact. The results encourage educators and policymakers to invest in modifiable factors, such as teacher collaboration, self-efficacy, and positive perceptions of ICT, to enhance teachers ICT integration.

 The effective integration of Information and Communication Technology ICT in education is crucial for student success in the digital age, and large-scale international assessments provide valuable data for understanding and improving these practices. This study investigates the factors influencing teachers ICT integration in teaching using the ICILS 2018 dataset. The study combines traditional methods, such as multiple linear regression, with machine learning techniques like the random forest algorithm, to comprehensively understand the factors driving teachers ICT use. The findings reveal that the models successfully explained a significant portion of the variance in teachers ICT practices. The random forest analysis identified country context as the most influential predictor, followed by teachers positive views on the benefits of ICT, teacher collaboration, ICT self-efficacy, and experience with online lessons. Factors such as experience in preparing online materials and teacher age had a moderate influence, while access to computer resources and gender showed minimal impact. The results encourage educators and policymakers to invest in modifiable factors, such as teacher collaboration, self-efficacy, and positive perceptions of ICT, to enhance teachers ICT integration.

 The effective integration of Information and Communication Technology ICT in education is crucial for student success in the digital age, and large-scale international assessments provide valuable data for understanding and improving these practices. This study investigates the factors influencing teachers ICT integration in teaching using the ICILS 2018 dataset. The study combines traditional methods, such as multiple linear regression, with machine learning techniques like the random forest algorithm, to comprehensively understand the factors driving teachers ICT use. The findings reveal that the models successfully explained a significant portion of the variance in teachers ICT practices. The random forest analysis identified country context as the most influential predictor, followed by teachers positive views on the benefits of ICT, teacher collaboration, ICT self-efficacy, and experience with online lessons. Factors such as experience in preparing online materials and teacher age had a moderate influence, while access to computer resources and gender showed minimal impact. The results encourage educators and policymakers to invest in modifiable factors, such as teacher collaboration, self-efficacy, and positive perceptions of ICT, to enhance teachers ICT integration.

 The effective integration of Information and Communication Technology ICT in education is crucial for student success in the digital age, and large-scale international assessments provide valuable data for understanding and improving these practices. This study investigates the factors influencing teachers ICT integration in teaching using the ICILS 2018 dataset. The study combines traditional methods, such as multiple linear regression, with machine learning techniques like the random forest algorithm, to comprehensively understand the factors driving teachers ICT use. The findings reveal that the models successfully explained a significant portion of the variance in teachers ICT practices. The random forest analysis identified country context as the most influential predictor, followed by teachers positive views on the benefits of ICT, teacher collaboration, ICT self-efficacy, and experience with online lessons. Factors such as experience in preparing online materials and teacher age had a moderate influence, while access to computer resources and gender showed minimal impact. The results encourage educators and policymakers to invest in modifiable factors, such as teacher collaboration, self-efficacy, and positive perceptions of ICT, to enhance teachers ICT integration.

Makale detayları

Hybrid Regression Analysis of Predictors of Teachers' ICT Use in Teaching Practices: Evidence from ICILS

Yazarlar:

Kaan Batı | Şeyma Irmak

Yayıncı:

Kafkas University

Ana Başlıklar:

In-Service Training | Educational Technology and Computing | Learning Analytics | Teacher and Student Wellbeing

Dergi:

e-Kafkas Journal of Educational Research Vol.12 Issue 2, pp.412-427

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001354130

pISSN:

2148-8940

ICILS

ICT

multiple linear regression

random forest

teachers

UTAUT

Sayı

Makale detayları

Hybrid Regression Analysis of Predictors of Teachers' ICT Use in Teaching Practices: Evidence from ICILS

Yazarlar: Kaan Batı | Şeyma Irmak

Yayıncı: Kafkas University

Ana Başlıklar: In-Service Training | Educational Technology and Computing | Learning Analytics | Teacher and Student Wellbeing

Dergi: e-Kafkas Journal of Educational Research Vol.12 Issue 2, pp.412-427

Belge Tipi: Makale

Yayın Tarihi: 8/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001354130

pISSN: 2148-8940

ICILS

ICT

multiple linear regression

random forest

teachers

UTAUT

Sayı

Yazarlar:

Kaan Batı | Şeyma Irmak

Yayıncı:

Kafkas University

Ana Başlıklar:

In-Service Training | Educational Technology and Computing | Learning Analytics | Teacher and Student Wellbeing

Dergi:

e-Kafkas Journal of Educational Research Vol.12 Issue 2, pp.412-427

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001354130

pISSN:

2148-8940