Educational robotics is an opportunity that offers teachers to develop several students’ skills in a creative way and to explore valuable concepts and relations in a constructionist way. In addition to getting acquainted with basic information from STEAM subjects, students can learn to program, develop soft skills, or implement interdisciplinary projects and thus build knowledge in context. Despite the undeniable advantages, the integration of educational robotics into the direct teaching process proves to be challenging. There are several reasons for this. In this article, we want to deal with only one of them, and that is to set the right learning objectives from cognitive domain. During the teaching of educational robotics, we found several inconsistencies. If we created the tasks based on Bloom’s taxonomy and then compared them with the real difficulty of the tasks, the gradation of the cognitive difficulty of the tasks did not correspond to reality. And that regardless of whether he is a beginner or an advanced student of robotics. In this paper, we want to answer the questions we have begun to ask ourselves, namely: How to properly set learning objectives for the use of educational robotic kits in computer science lessons? Are commonly used taxonomies also suitable for educational robotics? If not, what levels should cognitive taxonomy for educational robotics have? In this article we present the results of our research - cognitive taxonomy for educational robotics, which were created based on qualitative research and reflect our experiences.
Cognitive Taxonomy and Task Gradation in Educational Robotics – Preliminary Results
Lect. Notes in Networks, Syst.
Iberian Robotics conference ; 2022 ; Zaragoza, Spain November 23, 2022 - November 25, 2022
2022-11-19
11 pages
Article/Chapter (Book)
Electronic Resource
English
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