Assessment Strategies in Robotics Courses: An Analysis of Methodology and Learning Outcomes

This study investigates the implementation of robotics classes in five schools, targeting both elementary and high school students. The classes, designed according to Fink's Significant Learning Taxonomy and integrating the National Common Curricular Base (BNCC) into subjects like mathematics and sciences, included practical activities, teamwork, and reflections on technology's societal impact. An assessment method based on Fink's Taxonomy was previously developed to validate these courses. Two evaluations were conducted at different phases to measure the development of competencies such as problem-solving, teamwork, and technical skills. This paper presents a structured literature review, detailed analysis of the methodology, application, and results, aiming to understand the actual impact of the robotics course and identify areas for future improvement. Analysis of theoretical questions revealed lower success rates in programming-related questions, suggesting the need for a rotation of functions among students. Despite some challenges, the self-assessment responses showed increased student interest and reduced difficulties over time.