BEA 2026 Shared Task on Rubric-based Short Answer Scoring for German

Are you a researcher in AI in education and/or natural language processing? Do you like shared tasks and machine learning competitions like the yearly SemEval tasks or Kaggle competitions? Then you might consider participating in the BEA 2026 Shared Task on Rubric-based Short Answer Scoring for German, co-organized by us and colleagues from IPN – Leibniz-Institut für die Pädagogik der Naturwissenschaften und Mathematik.

For this shared task, we look at the natural language understanding task of rubric-based short answer scoring, a task for which models must score short answers to open-ended assessment questions with the help of provided textual scoring rubrics. The dataset we provide for this was collected in authentic German school contexts and scored by domain experts as part of the ALICE project funded by the Leibniz-Gemeinschaft. As this suggests, the dataset is in German and therfore contributes to the body of non-English NLP benchmarks.

All participants will get the chance to publish a system description paper as part of the proceedings of the Association for Computational Linguistics SIGEDU 21st Workshop on Innovative Use of NLP for Building Educational Applications that will be part of the ACL 2026 conference held in San Diego.

Since this is an open shared task, you are free to use whatever method you find suitable, including, but not limited to, LLMs, PLMs, neuro-symbolic methods, or statistical learners.

Further information on the timeline and the registration form can be found here: link