Exploring the Design and Implementation of a Robotic-Coding Camp in Teacher Education

This study focused on a bachelor- university-level course that aims to design and implement a robotic-coding camp to train pre-service teachers. Seventeen pre-service teachers participated in this study conducted in the Computational Empowerment Lab at the Center of Teacher Education at the University of Vienna. The researchers aimed to identify specific improvement strategies for in-service and pre-service teachers to enhance their pedagogical practices in designing a robotic-coding camp by promoting student critical thinking, computational thinking, and problem-solving competencies. Additionally, the study proposed to identify the relevant features of the camp's design and implementation that can promote practitioners' engagement and address the challenges they face. The course was offered during the summer semester of 2023. For the procedure of the study, pre-service teachers thought about a problem or situation using the phenomena-based learning method and explained the problem using mediating tools, including educational robots, 3D printers, laser-cutting, and creative Lego boxes, among others. At the end of the course, students developed their project, designed a prototype of a robotic-coding camp, and created digital stories as real-world basis problem statements for their project. Students' assignments and group work interactions, including forum discussions in Moodle, reflection papers, and hands-on activities, were used as data sources. Data collected and analyzed by qualitatively. Participatory action research was used as a research method. The results provide guidelines for how to design and implement robotic coding camps and digital stories for teachers who might want to implement a robotic camp in their future careers. In addition, the results suggest improvement strategies for designing robotic coding activities, including four action steps: (1) phenomenon-based problem statement, (2) visualizing the problem as a digital story, (3) finding a pattern in the problem and (4) creating the learning environment and coding. The most challenging part was the third step, in which participant had difficulty finding a pattern within the problem.