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

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

doi:10.4121/4b82dfc0-3fe4-40d6-9e32-3aef85cb44b2.v1

The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/4b82dfc0-3fe4-40d6-9e32-3aef85cb44b2

Datacite citation style:

Saunders-Smits, Gillian; Claij, Cilia; van der Niet, Astrid (2023): Dataset with anonymous non-aggregated data accompanying SEFI paper: Educating Future Robotics Engineers In Multidisciplinary Approaches In Robot Software Design. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/4b82dfc0-3fe4-40d6-9e32-3aef85cb44b2.v1

Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

usage stats

110

views

downloads

categories

keywords

Cooperative Education, Multidisciplinary Design, Project based Learning, Robotics, Student Experience

time coverage

2023

licence

CC BY-SA 4.0

collection

Dataset accompanying the SEFi 2023 paper: Educating Future Robotics Engineers In Multidisciplinary Approaches In Robot Software Design

export as...

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Gillian Saunders-Smits

, Cilia Claij , Astrid van der Niet

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., & 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

history