Parametrizable exercise generation from authentic texts: Effectively targeting the language means on the curriculum

Tanja Heck, Detmar Meurers


Abstract
We present a parametrizable approach to exercise generation from authentic texts that addresses the need for digital materials designed to practice the language means on the curriculum in a real-life school setting. The tool builds on a language-aware searchengine that helps identify attractive texts rich in the language means to be practiced. Making use of state-of-the-art NLP, the relevant learning targets are identified and transformed intoexercise items embedded in the original context.While the language-aware search engine ensures that these contexts match the learner‘s interests based on the search term used, and the linguistic parametrization of the system then reranks the results to prioritize texts that richly represent the learning targets, for theexercise generation to proceed on this basis, an interactive configuration panel allows users to adjust exercise complexity through a range of parameters specifying both properties of thesource sentences and of the exercises.An evaluation of exercises generated from web documents for a representative sample of language means selected from the English curriculum of 7th grade in German secondary school showed that the ombination of language-aware search and exercise generationsuccessfully facilitates the process of generating exercises from authentic texts that support practice of the pedagogical targets.
Anthology ID:
2022.bea-1.20
Volume:
Proceedings of the 17th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2022)
Month:
July
Year:
2022
Address:
Seattle, Washington
Venues:
BEA | NAACL
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
154–166
Language:
URL:
https://aclanthology.org/2022.bea-1.20
DOI:
10.18653/v1/2022.bea-1.20
Bibkey:
Cite (ACL):
Tanja Heck and Detmar Meurers. 2022. Parametrizable exercise generation from authentic texts: Effectively targeting the language means on the curriculum. In Proceedings of the 17th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2022), pages 154–166, Seattle, Washington. Association for Computational Linguistics.
Cite (Informal):
Parametrizable exercise generation from authentic texts: Effectively targeting the language means on the curriculum (Heck & Meurers, BEA 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.bea-1.20.pdf