Using Computational Thinking to Facilitate Language Learning: A Survey of Students’ Strategy Use in Austrian Secondary Schools

Abstract

After Jeanette Wing in 2006 described computational thinking (CT) as a fundamental skill for everyone just like reading or arithmetic, it has become a widely discussed topic all over the world. Computational thinking is a problem-solving skill set that is used to tackle problems in computer science. However, these skills, such as pattern recognition, decomposition, abstraction, generalization, and algorithmic thinking, are useful in other domains, as well. This study focuses on the use of CT skills to approach complex linguistic learning tasks in the foreign language classroom. To foster these problem-solving skills, an innovative method is used. The authors take advantage of computer science (CS) models (e.g. Unified Modeling Language – UML) and transform them into a teaching and learning tool. This paper describes the design and implementation of a survey used to detect students’ use of learning strategies that are linked to computational thinking. This survey is an instrument used in a multiple-case study and was administered at the beginning of the interventions. The participants of the study were learners of English and Spanish (n=66) from two secondary schools. Results indicated that the students were medium to low users of learning strategies that demand problem-solving skills related to computational thinking. Differences by gender were also found, with females reporting higher use of learning strategies than males. To conclude, the study showed a low use of strategies among students and highlighted the importance of introducing students to learning strategies and fostering skills needed for future professional life.