Novel German dataset for analytic essay scoring with segmentation and topic-code labels¶
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Evidence · 2 claims (2 for) · 1 study (1 causal),q2· 0 of 1 report an effect size · 2 claims rest on one study
Description¶
A dataset created by Gombert et al. containing 698 German-language student essays segmented and multilabel-annotated for learning tips and lecture-topic connections to support analytic essay-scoring research.
Components¶
Claims¶
- Learning-tip-to-lecture-topic coding by seven coders reached an overall agreement of 0.87 (Cohen's Kappa) [+W]
- Sentence-to-learning-tip segmentation coding by three trained coders reached an average Cohen's Kappa of 0.96 [+W]
Related Products and Programmes¶
Key Sources¶
- Gombert, S., Fink, A., Giorgashvili, T., Jivet, I., Di Mitri, D., Yau, J., Frey, A., & Drachsler, H. (2024). From the Automated Assessment of Student Essay Content to Highly Informative Feedback: a Case Study. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-023-00387-6
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
novel-german-dataset-for-analytic-essay-scoring-with-segmentation-and-topic-code-labels |
title |
Novel German dataset for analytic essay scoring with segmentation and topic-code labels |
description |
A dataset created by Gombert et al. |
status |
review |
product_kind |
dataset |
generated |
by process:settle-candidates on 2026-10-28 |
trust |
unverified — no one has confirmed this page's content |
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