Exploring the intentions of science teacher candidates to implement computational thinking in their future classroom: A case study

The education system across countries is evolving as students and teachers are increasingly exposed to relevant technologies and innovative pedagogies through both plugged and unplugged activities to promote computational thinking. This paper examines the factors influencing preservice teachers' intentions to integrate computational thinking into their future teaching practices. A total of 164 preservice teachers from the University of Education in Southern Nigeria participated in the research. The analysis employed partial least squares structural equation modeling to explore the relationships among six latent variables identified in this study: perceived usefulness, ease of use, attitude toward computational thinking, behavioral control, subjective norm, and behavioral intention. The findings indicate that the proposed model explains 74.4% of the variance in preservice teachers' intentions to teach computational thinking in their classrooms. Additionally, the results demonstrate that attitude toward computational thinking, perceived behavioral control, ease of use, and usefulness significantly and positively influence preservice teachers' intentions to adopt computational thinking in their future educational practices. However, subjective norms did not significantly predict the intention of teacher candidates to apply computational thinking to their planned teaching practices. The authors discuss these results in the context of integrating computational thinking into educational settings and recommend directions for future research.