Work

Difficulty-Controllable Multiple-Choice Question Generation for Reading Comprehension Using Item Response Theory

Year: 2024

Type: conference-paper

Source: Communications in computer and information science

DOI: 10.1007/978-3-031-64315-6_27

Authors: Yuto Tomikawa, Masaki Uto

Institution: University of Electro-Communications

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: closed

OpenAlex ID: W4400187305

FWCI: 1.155

Cites: 12

Cited by: 4

Related to: 10