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Towards Human-like Educational Question Generation with Small Language Models

Fawzi, Fares; Balan, Sarang; Cukurova, Mutlu; Yilmaz, Emine; Bulathwela, Sahan; (2024) Towards Human-like Educational Question Generation with Small Language Models. In: Olney, Andrew M and Chounta, Irene-Angelica and Liu, Zitao and Santos, Olga C and Bittencourt, Ig Ibert, (eds.) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky. (pp. pp. 295-303). Springer: Cham, Switzerland.

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Abstract

With the advent of Generative AI models, the automatic generation of educational questions plays a key role in developing online education. This work compares large-language model-based (LLM) systems and their small-language model (sLM) counterparts for educational question generation. Our experiments, quantitatively and qualitatively, demonstrate that sLMs can produce educational questions with comparable quality by further pre-training and fine-tuning.

Type: Proceedings paper
Title: Towards Human-like Educational Question Generation with Small Language Models
Event: 25th International Conference, AIED 2024
Location: Recife, Brazil
Dates: 12 Jul 2024 - 8 Jul 2024
ISBN-13: 978-3-031-64314-9
DOI: 10.1007/978-3-031-64315-6_25
Publisher version: https://doi.org/10.1007/978-3-031-64315-6_25
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Education
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10196728
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