Collaborative Development of Modular Open Source Educational Resources for Natural Language Processing

MCML Authors

Matthias Aßenmacher

Dr.

→ Group Bernd Bischl
 Statistical Learning and Data Science

Leonie Weissweiler

* Former Member

→ Group Hinrich Schütze
 Computational Linguistics

Bernd Bischl

Prof. Dr.

Director

Statistical Learning and Data Science

Hinrich Schütze

Prof. Dr.

Principal Investigator

Computational Linguistics

Abstract

In this work, we present a collaboratively and continuously developed open-source educational resource (OSER) for teaching natural language processing at two different universities. We shed light on the principles we followed for the initial design of the course and the rationale for ongoing developments, followed by a reflection on the inter-university collaboration for designing and maintaining teaching material. When reflecting on the latter, we explicitly emphasize the considerations that need to be made when facing heterogeneous groups and when having to accommodate multiple examination regulations within one single course framework. Relying on the fundamental principles of OSER developments as defined by Bothmann et al. (2023) proved to be an important guideline during this process. The final part pertains to open-sourcing our teaching material, coping with the increasing speed of developments in the field, and integrating the course digitally, also addressing conflicting priorities and challenges we are currently facing.

inproceedings

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TeachingNLP @ACL 2024

6th Workshop on Teaching NLP at the 62nd Annual Meeting of the Association for Computational Linguistics. Bangkok, Thailand, Aug 11-16, 2024.

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Authors

M. Aßenmacher • A. Stephan • L. Weissweiler • E. Çano • I. Ziegler • M. Härttrich • B. Bischl • B. Roth • C. Heumann • H. Schütze

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Links

URL

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Research Areas

 A1 | Statistical Foundations & Explainability

 B2 | Natural Language Processing