Bringing Computer Science Concepts into the Language Classroom: A Case Study on Teachers? and Students? Perception of Modeling to Teach Computational Thinking
Sprache des Vortragstitels:
LACCEI International Multi-Conference for Engineering, Education and Technolgy 2022
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Abstract? Computational thinking for everyone! Since Jeanette Wing's proposal in 2006 of computational thinking (CT) as a fundamental skill such as reading or arithmetics, CT has gained popularity all over the world. CT is a strategy that is needed to tackle problems in the field of computer science and includes elements such as pattern recognition, decomposition, abstraction, generalization, and algorithmic thinking. To be able to systematically tackle linguistic tasks, the language learner needs a set of problem-solving skills, too. In foreign language acquisition, the learner faces different linguistic learning problems, and thus, learning and mastering different problem-solving skills could reduce linguistic complexity and facilitate the learning process. To benefit from CT skills in language teaching and learning, the authors use an innovative method: modeling. In computer science, models, such as the entity-relationship diagram or UML (Unified Modeling Language) like activity diagrams are used to analyze and visualize complex tasks. Due to the many implementation options that these diagrams offer, they also prove to be useful in other areas. The authors especially focus on the field of language learning and investigate the use of computer science models as a teaching and learning strategy for students of all age groups. Employing a mixed-methods approach, this case study explores teachers? and students? views on the integration of modeling in language learning activities. Results demonstrated that there was a remarkable difference in students? learning performance as well as a positive attitude towards modeling as a teaching and learning strategy.