Introduction of unfolding IRT models with applications in rater-mediated assessments

报告人：王珏

报告地点：腾讯会议ID:500-574-179

报告时间：2023年9月22日星期五10:00-11:00

邀请人：孟祥斌

报告摘要：

In item response theory (IRT) modeling for categorical data, two response processes are typically characterized: the cumulative process and the unfolding process. Most of IRT models, also called dominance models, deal with a cumulative response process, where the probability of a positive response is a monotonic function of the relevant parameters on the continuum. The unfolding IRT model finds an ideal-point of person location on the underlying continuum, creating a single-peaked and symmetric item response function curve. Recent research indicated the potential use of unfolding models for examining rater preference and accuracy in scoring tasks -- unfolding models can reveal more information than dominance models in reflecting individual differences among human raters. This talk will introduce the unfolding IRT models and illustrate its applications in examining rater-mediated assessments.

主讲人简介：

王珏，博士，中国科学技术大学心理学系，特任研究员，博士生导师；曾任美国迈阿密大学（University of Miami）教育心理学系助理教授及系副主任、美国教育研究协会 Rasch SIG主席；现任中国现场统计教育统计与管理分会理事、安徽省社会心理学理事；入选安徽省海外引才创新项目，荣获美国教育研究协会Georg William Rasch Early Career Award。研究方向包括主观测评中评分者效应的检验，项目反应理论模型（优势模型和展开模型）在教育与心理测评中的开发和应用。在Educational Psychology Review, Psychology of Aesthetics, Creativity, and the Arts, Educational and Psychological Measurement, Journal of Educational Measurement, and Assessing Writing等国际期刊发表文章30余篇；出版一本Rasch测量理论的学术专著，收录于SAGE的“小绿皮书”系列（Quantitative Applications in the Social Sciences series）；主持美国Pearson国际教育研究项目、教育部人文社科规划基金项目，作为课题骨干参与科技部重点专项。