Linguistically-Driven Strategy for Concept Prerequisites Learning on Italian
Alessio Miaschi, Chiara Alzetta, Franco Alberto Cardillo, Felice Dell’Orletta
Abstract
We present a new concept prerequisite learning method for Learning Object (LO) ordering that exploits only linguistic features extracted from textual educational resources. The method was tested in a cross- and in- domain scenario both for Italian and English. Additionally, we performed experiments based on a incremental training strategy to study the impact of the training set size on the classifier performances. The paper also introduces ITA-PREREQ, to the best of our knowledge the first Italian dataset annotated with prerequisite relations between pairs of educational concepts, and describe the automatic strategy devised to build it.- Anthology ID:
- W19-4430
- Volume:
- Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Helen Yannakoudakis, Ekaterina Kochmar, Claudia Leacock, Nitin Madnani, Ildikó Pilán, Torsten Zesch
- Venue:
- BEA
- SIG:
- SIGEDU
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 285–295
- Language:
- URL:
- https://aclanthology.org/W19-4430
- DOI:
- 10.18653/v1/W19-4430
- Cite (ACL):
- Alessio Miaschi, Chiara Alzetta, Franco Alberto Cardillo, and Felice Dell’Orletta. 2019. Linguistically-Driven Strategy for Concept Prerequisites Learning on Italian. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 285–295, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Linguistically-Driven Strategy for Concept Prerequisites Learning on Italian (Miaschi et al., BEA 2019)
- PDF:
- https://preview.aclanthology.org/add_acl24_videos/W19-4430.pdf