تقرير
Developing Open Source Educational Resources for Machine Learning and Data Science
| العنوان: | Developing Open Source Educational Resources for Machine Learning and Data Science |
|---|---|
| المؤلفون: | Bothmann, Ludwig, Strickroth, Sven, Casalicchio, Giuseppe, Rügamer, David, Lindauer, Marius, Scheipl, Fabian, Bischl, Bernd |
| المصدر: | Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 207:1-6, 2022 |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computers and Society, Computer Science - Machine Learning |
| الوصف: | 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. Comment: 6 pages |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2107.14330 |
| رقم الأكسشن: | edsarx.2107.14330 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |