Abstract
AbstractEducational robotics (ER) has the potential to be a novel approach to teaching geohazards such as earthquakes at the college level. ER, which provides learners with problem-solving settings, requires proficiency in content knowledge and practical application to address ill-defined problems, challenging learners to master problem-solving strategies. Despite several efforts in the existing literature, it is necessary to scaffold the problem-solving strategies comprehensively. This qualitative study investigated the problem-solving strategies of nine pre-service science teachers aligned with a coding scheme containing problem-solving strategies not previously documented together. The participants were assigned to construct a methane gas detector with Tinkercad to mitigate post-earthquake explosion risks for rescue teams in an online robotics-integrated earthquake professional development (PD) course. Qualitative data, including artifacts, observations, and interviews, were analyzed using deductive coding. The results indicated that participants predominantly employed trial and error, expert opinion, and case-based reasoning. They rarely utilized heuristics and intuition and did not use capacity evaluation, prediction, or sketching strategies. Furthermore, the study synthesized different problem-solving strategies into a comprehensive framework, which was used as a coding scheme. This framework helps to clarify problem-solving mechanisms in an ER context, offering a structured approach.
Funder
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Trabzon University
Publisher
Springer Science and Business Media LLC
Reference60 articles.
1. An, H., Sung, W., & Yoon, S. Y. (2022). Implementation of learning by design in a synchronized online environment to teach educational robotics to inservice teachers. Education Technology Research and Development, 70, 1473–1496. https://doi.org/10.1007/s11423-022-10134-8
2. Ardianto, D., Permanasari, A., Firman, H., & Ramalis, T.R. (2019). Analyzing higher education students’ understanding of earthquake-resistant buildings on stem learning. Journal of Engineering Science and Technology, Special Issue on AASEC2018, 47–57.
3. Auyelbek, M., Ybyraimzhanov, K., Andasbayev, E., Abdykerimova, E., & Turkmenbayev, A. (2022). Analysis of studies in the literature on educational robotics. Journal of Turkish Science Education, 19(4), 1267–1290.
4. Aydin, M., & Ozcan, I. (2022). Evaluating the content accuracy of augmented reality applications on the Solar System. Physics Education, 57(3), 035009. https://doi.org/10.1088/1361-6552/ac50a4
5. Barak, M., & Assal, M. (2018). Robotics and STEM learning: Students’ achievements in assignments according to the P3 task taxonomy—practice, problem solving, and projects. International Journal of Technology and Design Education, 28(1), 121–144. https://doi.org/10.1007/s10798-016-9385-9