© 2017 by ALTISSIA International s.a.

CEFR-ASAG CORPUS

This dataset contains a number of short texts written by non-native speakers of English. Each participant was asked to provide a short answer to an open-ended question which targeted the proficiency level in which he/she was placed. Each question is therefore labelled with a particular proficiency level, as defined by the Common European Framework of Reference for Languages (CEFR).

Moreover, 299 of the collected answers were also labelled using the CEFR, by a panel of three CEFR-certified examiners. Their labels, as well as a majority-vote label, have been added to each one of these texts.

All texts are encoded in a TEI format.

More information can be found in the following paper. When using the data in your research or publication, please cite this work as well.

@inproceedings{tack-etal-2017-human,
    title = {Human and Automated {CEFR}-based Grading of Short Answers},
    author = {Tack, Ana{\"\i}s and Fran{\c{c}}ois, Thomas and Roekhaut, Sophie and Fairon, C{\'e}drick},
    booktitle = {Proceedings of the 12th Workshop on Innovative Use of {NLP} for Building Educational Applications},
    month = sep,
    year = {2017},
    address = {Copenhagen, Denmark},
    publisher = {Association for Computational Linguistics},
    url = {https://aclanthology.org/W17-5018},
    doi = {10.18653/v1/W17-5018},
    pages = {169--179}
}

Authors

• ALTISSIA International s.a. - www.altissia.com
• Center for Natural Language Processing (CENTAL), Université catholique de Louvain (UCL, Belgium) - cental@uclouvain.be

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

You should have received a copy of the license along with this work. If not, see http://creativecommons.org/licenses/by-nc-sa/4.0/.

See LICENSE.txt for more details.

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[1.0.1] - 2017-10-16

Fixed

• All personal details have been anonymized using the following tags:
  • {name}: first or full names
  • {initial}: name initials
  • {number}: phone numbers

[1.0.0] - 2017-09-08

Added

• First release of the dataset