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.
%0 Journal Article
%1 Elstner2023-uo
%A Elstner, Theresa
%A Loebe, Frank
%A Ajjour, Yamen
%A Akiki, Christopher
%A Bondarenko, Alexander
%A Fröbe, Maik
%A Gienapp, Lukas
%A Kolyada, Nikolay
%A Mohr, Janis
%A Sandfuchs, Stephan
%A Wiegmann, Matti
%A Frochte, Jörg
%A Ferro, Nicola
%A Hofmann, Sven
%A Stein, Benno
%A Hagen, Matthias
%A Potthast, Martin
%D 2023
%I Association for the Advancement of Artificial Intelligence (AAAI)
%J Proc. Conf. AAAI Artif. Intell.
%K topic_language topic_knowledge
%N 13
%P 15807--15815
%T Shared tasks as tutorials: A methodical approach
%V 37
%X 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.
@article{Elstner2023-uo,
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.},
added-at = {2024-09-10T10:41:24.000+0200},
author = {Elstner, Theresa and Loebe, Frank and Ajjour, Yamen and Akiki, Christopher and Bondarenko, Alexander and Fr{\"o}be, Maik and Gienapp, Lukas and Kolyada, Nikolay and Mohr, Janis and Sandfuchs, Stephan and Wiegmann, Matti and Frochte, J{\"o}rg and Ferro, Nicola and Hofmann, Sven and Stein, Benno and Hagen, Matthias and Potthast, Martin},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/2d4a6045a0d645423d0ff217741117c2e/scadsfct},
interhash = {0944fd4d365d709522931a8f216ff7f0},
intrahash = {d4a6045a0d645423d0ff217741117c2e},
journal = {Proc. Conf. AAAI Artif. Intell.},
keywords = {topic_language topic_knowledge},
month = jun,
number = 13,
pages = {15807--15815},
publisher = {Association for the Advancement of Artificial Intelligence (AAAI)},
timestamp = {2024-11-28T17:41:20.000+0100},
title = {Shared tasks as tutorials: A methodical approach},
volume = 37,
year = 2023
}
