Deep Item Response Theory as a Novel Test Theory Based on Deep Learning

已完结 10 由 FN[QV 发布于 2024/10/29 9:36:48

DOI:10.3390/ELECTRONICS10091020
作者：E. Tsutsumi,?Ryo Kinoshita,?M. Ueno
文献类型：期刊论文
补充材料：只需要正文
文献链接：https://doi.org/10.3390/ELECTRONICS10091020

MDPI

Abstract：Item Response Theory (IRT) evaluates, on the same scale, examinees who take different tests. It requires the linkage of examinees’ ability scores as estimated from different tests. However,

应助信息

1天前

亮露

bc95a124959711efb9fd34735aa3bc31.pdf 已采纳

1天前

Book学术机器人

2024/10/29 9:36:48 未找到该文献，机器人已退出，请等待人工下载

2024/10/29 9:36:48 Book学术AI机器人收到请求，开始寻找文献

2024/10/29 9:36:48 已向机器人发送请求

1天前

FN[QV 发布求助

上一个求助:其它数据库Naturally Fractured Carbonate Reservoir Characterization: A Case Study of a Mature High-Pour Point Oil Field in Hungary 下一个求助:其它数据库Estimation of multidimensional item response theory models with correlated latent variables using variational autoencoders