MCQGen: A Large Language Model-Driven MCQ Generator for Personalized Learning-Reference-Cited by-同舟云学术

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MCQGen: A Large Language Model-Driven MCQ Generator for Personalized Learning

Published:2024 Issue: Volume:12 Page:102261-102273
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hang Ching Nam¹^ORCID,Wei Tan Chee²^ORCID,Yu Pei-Duo³^ORCID

Affiliation:

1. Yam Pak Charitable Foundation School of Computing and Information Sciences, Saint Francis University, Hong Kong, China

2. College of Computing and Data Science, Nanyang Technological University, Jurong West, Singapore

3. Department of Applied Mathematics, Chung Yuan Christian University, Taoyuan, Taiwan

Funder

Nanyang Technological University (NTU) startup fund

EdeX

NTU Centre for Teaching, Learning and Pedagogy

National Science and Technology Council of Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10577164.pdf?arnumber=10577164

Reference31 articles.

1. Automatic generation of multiple choice questions using dependency-based semantic relations

2. PaLM 2 technical report;Anil,2023

3. Assessment of learning with multiple-choice questions

4. Language models are few-shot learners;Brown

5. Automatic Multiple Choice Question Generation From Text: A Survey

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