CategoriesConference article

New pub: Are rubrics all you need? Towards rubric-based automatic short answer scoring

The latest paper led by Sebastian Gombert has been published in the Proceedings of the LAK26: 16th International Learning Analytics and Knowledge Conference (LAK26).

"Are rubrics all you need? Towards rubric-based automatic short answer scoring via guided rubric-answer alignment"

In educational assessment, rubrics are central because they define clear criteria for evaluating learner responses and specify what counts as relevant evidence. Yet, most automatic short answer scoring approaches make little to no explicit use of rubrics, or treat them only as additional side information. This paper turns that around and asks what happens if rubrics themselves become the primary scoring reference for automated systems.

The authors introduce the task of rubric-based automatic short-answer scoring, in which the model uses the scoring rubric as an explicit anchor rather than relying solely on large sets of labelled student responses. To implement this idea, they propose a guided rubric–answer alignment, in which each student's answer is aligned directly with rubric criteria and level descriptors rather than with other answers.

Building on this concept, the paper presents two new transformer-based architectures, GRAASP and ToLeGRAA, which use attention mechanisms to focus on the most relevant rubric information when predicting scores. These architectures aim to make scoring more transparent and more faithful to the assessment design, and they promise greater robustness when tasks change because the scoring logic is driven by the rubric rather than solely by historical training data.

This work aligns with a broader agenda in our group: designing AI systems that are tightly coupled with pedagogical artefacts such as rubrics, feedback guidelines, and learning objectives, instead of treating AI as a detached black box. By placing rubrics at the centre of the modelling process, this research opens a path towards more interpretable, educator-aligned automatic assessment tools that can better support teaching and learning.

Check it here (Open Access PDF via ACM):

Gombert, S., Sun, Z., Zehner, F., Lossjew, J., Wyrwich, T., Czinczel, B. K., Bednorz, D., Kubsch, M., Di Mitri, D., Neumann, K., & Drachsler, H. (2026). Are rubrics all you need? Towards rubric-based automatic short answer scoring via guided rubric-answer alignment. Proceedings of the LAK26: 16th International Learning Analytics and Knowledge Conference, 272–282. https://dl.acm.org/doi/10.1145/3785022.3785064

Published by Daniele Di Mitri

Daniele Di Mitri is a professor of Multimodal Learning Technologies at the German University of Digital Science. At the German UDS, he leads the research group "Augmented Feedback" and coordinates the master's in Advanced Digital Realities.  He is an associated researcher at the DIPF - Leibniz Institute for Research and Information in Education and a lecturer at the Goethe University of Frankfurt, Germany. Daniele Di Mitri received his PhD in Learning Analytics and Wearable Sensor Support from the Open University of the Netherlands. His current research focuses on developing AI-driven, multimodal learning technologies to enhance digital education. It aims to create innovative, responsible solutions that improve learning experiences through advanced feedback systems and ethical integration of technology. He is a "Johanna Quandt Young Academy" fellow and was elected "AI Newcomer 2021" at the KI Camp by the German Informatics Society. He is a member of the CrossMMLA, a special interest group of the Society for Learning Analytics Research, and the chair of the special interest group on AI for Education of the European Association for Technology-Enhanced Learning.

Leave a Reply

Your email address will not be published. Required fields are marked *