Using Learning Analytics for Adaptive Exercise Generation

Tanja Heck, Detmar Meurers


Abstract
Single Choice exercises constitute a central exercise type for language learning in a learner’s progression from mere implicit exposure through input enhancement to productive language use in open exercises. Distractors that support learning in the individual zone of proximal development should not be derived from static analyses of learner corpora, but rely on dynamic learning analytics based on half-open exercises. We demonstrate how a system’s error diagnosis module can be re-used for automatic and dynamic generation and adaptation of distractors, as well as to inform exercise generation in terms of relevant learning goals and reasonable chunking in Jumbled Sentences exercises.
Anthology ID:
2023.bea-1.4
Volume:
Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Ekaterina Kochmar, Jill Burstein, Andrea Horbach, Ronja Laarmann-Quante, Nitin Madnani, Anaïs Tack, Victoria Yaneva, Zheng Yuan, Torsten Zesch
Venue:
BEA
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
44–56
Language:
URL:
https://aclanthology.org/2023.bea-1.4
DOI:
10.18653/v1/2023.bea-1.4
Bibkey:
Cite (ACL):
Tanja Heck and Detmar Meurers. 2023. Using Learning Analytics for Adaptive Exercise Generation. In Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023), pages 44–56, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Using Learning Analytics for Adaptive Exercise Generation (Heck & Meurers, BEA 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.bea-1.4.pdf