TY - DATA
T1 - Dataset with anonymous non-aggregated data accompanying SEFI paper: Educating Future Robotics Engineers In Multidisciplinary Approaches In Robot Software Design
PY - 2023/12/21
AU - Gillian Saunders-Smits
AU - Cilia Claij
AU - Astrid van der Niet
UR -
DO - 10.4121/4b82dfc0-3fe4-40d6-9e32-3aef85cb44b2.v1
KW - Robotics
KW - Project based Learning
KW - Cooperative Education
KW - Student Experience
KW - Multidisciplinary Design
N2 - This dataset contains the non-aggregated data accompanying the SEFI Paper: Educating Future Robotics Engineers In Multidisciplinary Approaches In Robot Software Design in .xlsx format of the qualitative questionnaire results. The research objective for the study was: To investigate the student experience in the Multi-Disciplinary Project in the MSc Robotics in the academic year 2023-2024 using a questionnaire which was fielded in June and July 2023. The main research question was: What can be learned from student feedback and perceptions regarding the course’s Learning Objectives and the overall running of the course? The data was collected using a Qualtrics online survey and both qualitative and quantitative data such as student satisfaction with course components were collected. The work was reported in a conference paper: Van Der Niet, A., Claij, C., &amp; Saunders-Smits, G. (2023). Educating Future Robotics Engineers In Multidisciplinary Approaches In Robot Software Design. European Society for Engineering Education (SEFI). DOI: 10.21427/W6WB-Z113 
ER -