Details
| Original language | English |
|---|---|
| Title of host publication | Teaching Machine Learning Workshop at ECML 2022 |
| Number of pages | 6 |
| Publication status | E-pub ahead of print - 28 Jul 2022 |
Abstract
Keywords
- cs.CY, cs.LG
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Teaching Machine Learning Workshop at ECML 2022. 2022.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Developing Open Source Educational Resources for Machine Learning and Data Science
AU - Bothmann, Ludwig
AU - Strickroth, Sven
AU - Casalicchio, Giuseppe
AU - Rügamer, David
AU - Lindauer, Marius
AU - Scheipl, Fabian
AU - Bischl, Bernd
N1 - 6 pages
PY - 2022/7/28
Y1 - 2022/7/28
N2 - Education should not be a privilege but a common good. It should be openly accessible to everyone, with as few barriers as possible; even more so for key technologies such as Machine Learning (ML) and Data Science (DS). Open Educational Resources (OER) are a crucial factor for greater educational equity. In this paper, we describe the specific requirements for OER in ML and DS and argue that it is especially important for these fields to make source files publicly available, leading to Open Source Educational Resources (OSER). We present our view on the collaborative development of OSER, the challenges this poses, and first steps towards their solutions. We outline how OSER can be used for blended learning scenarios and share our experiences in university education. Finally, we discuss additional challenges such as credit assignment or granting certificates.
AB - Education should not be a privilege but a common good. It should be openly accessible to everyone, with as few barriers as possible; even more so for key technologies such as Machine Learning (ML) and Data Science (DS). Open Educational Resources (OER) are a crucial factor for greater educational equity. In this paper, we describe the specific requirements for OER in ML and DS and argue that it is especially important for these fields to make source files publicly available, leading to Open Source Educational Resources (OSER). We present our view on the collaborative development of OSER, the challenges this poses, and first steps towards their solutions. We outline how OSER can be used for blended learning scenarios and share our experiences in university education. Finally, we discuss additional challenges such as credit assignment or granting certificates.
KW - cs.CY
KW - cs.LG
M3 - Conference contribution
BT - Teaching Machine Learning Workshop at ECML 2022
ER -