TY  - JOUR
T1  - Hybrid Regression Analysis of Predictors of Teachers' ICT Use in Teaching Practices: Evidence from ICILS
AU  - Irmak, Şeyma
AU  - Batı, Kaan
PY  - 2025
DA  - August
Y2  - 2025
DO  - 10.30900/kafkasegt.1627835
JF  - e-Kafkas Journal of Educational Research
JO  - e-KJER
PB  - Kafkas University
WT  - DergiPark
SN  - 2148-8940
SP  - 412
EP  - 427
VL  - 12
IS  - 2
LA  - en
AB  - 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.
KW  - ICILS
KW  - ICT
KW  - multiple linear regression
KW  - random forest
KW  - teachers
KW  - UTAUT
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UR  - https://doi.org/10.30900/kafkasegt.1627835
L1  - https://dergipark.org.tr/en/download/article-file/4556040
ER  -