Pre-Training With Scientific Text Improves Educational Question Generation
December 07, 2022 ยท Declared Dead ยท ๐ AAAI Conference on Artificial Intelligence
"No code URL or promise found in abstract"
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Authors
Hamze Muse, Sahan Bulathwela, Emine Yilmaz
arXiv ID
2212.03869
Category
cs.CL: Computation & Language
Cross-listed
cs.AI,
cs.CY,
cs.IR,
cs.LG,
stat.ML
Citations
13
Venue
AAAI Conference on Artificial Intelligence
Last Checked
5 months ago
Abstract
With the boom of digital educational materials and scalable e-learning systems, the potential for realising AI-assisted personalised learning has skyrocketed. In this landscape, the automatic generation of educational questions will play a key role, enabling scalable self-assessment when a global population is manoeuvring their personalised learning journeys. We develop EduQG, a novel educational question generation model built by adapting a large language model. Our initial experiments demonstrate that EduQG can produce superior educational questions by pre-training on scientific text.
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