Research on Intelligent Assessment Methods of Digital Classroom Questioning Abilities for Primary and Secondary School Teachers Based on Item Response Theory
Year: 2024
Type: conference-paper
Abstract: Teachers' questioning abilities significantly influence the quality of digital classroom teaching as well as the depth and breadth of classroom interaction. Domestic research has primarily focused on the content and form of classroom questions, but few studies involve the teachers' questioning abilities and the development of related training systems due to the absence of direct evidence-based data correlations. Herein, we employed Item Response Theory (IRT) to assess teachers' real-world classroom questioning abilities based on the "latent trait theory." IRT shifted the focus of ability assessment to the functional relationship between the probability of effective questioning behavior and the level of questioning ability. The intelligent assessment for primary-school teachers' digital classroom questioning abilities was realized through the following steps: categorical analysis of digital classroom questioning behaviors—ability parameter estimation based on the maximum likelihood method—validation of the fitting process—construction of the item characteristic curve model. Additionally, the validity of the IRT was demonstrated by conducting various practical case studies. In future research and practical exploration, this study provides insights toward the further investigation and improvement on the methodological approaches and standards of IRT, with a goal of optimizing the teachers' questioning behaviors and enhancing their classroom questioning abilities.
Authors: Xin Hong, Haiguang Fang, Yang Deng, Zeyu Li
Institution: Capital Normal University
Language: English
Field: Decision Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4406025690