Shared Tasks as Tutorials: A Methodical Approach
Abstract
In this paper, we discuss the benefits and challenges of shared tasks as a teaching method. A shared task is a scientific event and a friendly competition to solve a research problem, the task. In terms of linking research and teaching, shared-task-based tutorials fulfill several faculty desires: they leverage students' interdisciplinary and heterogeneous skills, foster teamwork, and engage them in creative work that has the potential to produce original research contributions. Based on ten information retrieval (IR) courses at two universities since 2019 with shared tasks as tutorials, we derive a domain-neutral process model to capture the respective tutorial structure. Meanwhile, our teaching method has been adopted by other universities in IR courses, but also in other areas of AI such as natural language processing and robotics.
Cite
Text
Elstner et al. "Shared Tasks as Tutorials: A Methodical Approach." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I13.26877Markdown
[Elstner et al. "Shared Tasks as Tutorials: A Methodical Approach." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/elstner2023aaai-shared/) doi:10.1609/AAAI.V37I13.26877BibTeX
@inproceedings{elstner2023aaai-shared,
title = {{Shared Tasks as Tutorials: A Methodical Approach}},
author = {Elstner, Theresa and Loebe, Frank and Ajjour, Yamen and Akiki, Christopher and Bondarenko, Alexander and Fröbe, Maik and Gienapp, Lukas and Kolyada, Nikolay and Mohr, Janis and Sandfuchs, Stephan and Wiegmann, Matti and Frochte, Jörg and Ferro, Nicola and Hofmann, Sven and Stein, Benno and Hagen, Matthias and Potthast, Martin},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2023},
pages = {15807-15815},
doi = {10.1609/AAAI.V37I13.26877},
url = {https://mlanthology.org/aaai/2023/elstner2023aaai-shared/}
}