Factors That Predict K-12 Teachers' Ability to Apply Computational Thinking Skills

Background and Objective. Teacher assessment research suggests that teachers have good conceptual understanding of CT. However, to model CT-based problem-solving in their classrooms, teachers need to develop the ability to recognize when and how to apply CT skills. Does existing professional development (PD) equip teachers to know when and how to apply CT skills? What factors should PD providers consider while developing trainings for CT application skills? Method. This retrospective observational study used a binomial regression model to determine what factors predict teachers' probability of performing well on a CT application skills test. Participants. Participants of this study were 129 in-service K-12 teachers from a community of practice in India. Findings. Results show that teachers who have received at least one CT training, who have a higher teaching experience, and are currently teaching CT will have a higher probability of applying CT skills correctly to problems irrespective of the subject they teach and their educational backgrounds. However, receiving a higher number of CT PD trainings was a negative predictor of teachers' performance. Implications. Implications for school administrators, professional development providers, and researchers are discussed. Teachers need ample opportunity to teach CT in their teaching schedules. Continuous professional development does not necessarily result in improved CT application skills unless careful consideration is given to the pedagogies used and to the resolution of misconceptions that teachers may have developed in prior training. Mixing plugged and unplugged pedagogical approaches may be beneficial to encourage transfer of CT application skills across different types of problems. Last, there is a need to develop valid and reliable instruments that measure CT application skills of teachers.