Dataset with anonymous non-aggregated data accompanying SEFI paper: Educating Future Robotics Engineers In Multidisciplinary Approaches In Robot Software Design

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<br><br>

本数据集收录配套于欧洲工程教育学会（SEFI，European Society for Engineering Education）会议论文《面向机器人软件设计多学科方法的未来机器人工程师培养（Educating Future Robotics Engineers In Multidisciplinary Approaches In Robot Software Design）》的非聚合定性问卷结果数据，文件格式为.xlsx。本研究的目标为：针对2023-2024学年理学硕士机器人学专业开设的多学科项目，于2023年6月至7月通过实施问卷的方式调研学生参与该项目的体验。核心研究问题为：从学生针对该课程学习目标与整体运行情况的反馈与认知中，可以汲取哪些经验启示？本研究通过Qualtrics在线调查平台采集数据，同步收集了学生对课程各模块满意度等定性与定量数据。

该研究成果已发表于如下会议论文：Van Der Niet, A., Claij, C., & Saunders-Smits, G. (2023). Educating Future Robotics Engineers In Multidisciplinary Approaches In Robot Software Design. 欧洲工程教育学会（SEFI）. DOI: 10.21427/W6WB-Z113