Work-in-progress. Data Science Challenge-X. self-directed, competence-based, project-based learning
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Author (Corporation)
Publication date
28.03.2022
Typ of student thesis
Course of study
Collections
Type
04B - Conference paper
Editor (Corporation)
Supervisor
Parent work
Proceedings of the IEEE Global Engineering Education Conference (EDUCON 2022). Digital Transformation for Sustainable Engineering Education
Special issue
DOI of the original publication
Link
Series
Series number
Volume
Issue / Number
Pages / Duration
2033-2036
Patent number
Publisher / Publishing institution
IEEE
Place of publication / Event location
Tunis
Edition
Version
Programming language
Assignee
Practice partner / Client
Keywords
Event
2022 IEEE Global Engineering Education Conference (EDUCON)
Exhibition start date
Exhibition end date
Conference start date
28.03.2022
Conference end date
31.03.2022
Date of the last check
ISBN
978-1-6654-4434-7
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
Closed
License
Citation
Benites, F., Schlatter, M., Messerli, M., & Custer, R. (2022). Work-in-progress. Data Science Challenge-X. self-directed, competence-based, project-based learning. In M. Jemni, I. Kallel, & A. Akkari (Eds.), Proceedings of the IEEE Global Engineering Education Conference (EDUCON 2022). Digital Transformation for Sustainable Engineering Education (pp. 2033–2036). IEEE. https://doi.org/10.1109/educon52537.2022.9766710