Automated item generation with recurrent neural networks

DOI10.1007/S11336-018-9608-YzbMath1422.62360OpenAlexW2791246286WikidataQ52658950 ScholiaQ52658950MaRDI QIDQ2318843

Matthias von Davier

Publication date: 16 August 2019

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11336-018-9608-y

zbMATH Keywords

neural networksmachine learningdeep learningautomatic item generation

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural nets and related approaches to inference from stochastic processes (62M45) Applications of statistics to psychology (62P15)

Related Items (1)

Transformer-based deep neural language modeling for construct-specific automatic item generation

Uses Software

• TensorFlow
• Adam
• GitHub

Cites Work

• Prediction functions for categorical panel data
• Conditional Log-Linear Models for Analyzing Categorical Panel Data
• 23 Automatic Item Generation and Cognitive Psychology
• Elicitation of Personal Probabilities and Expectations
• Approximation by superpositions of a sigmoidal function
• Unnamed Item

This page was built for publication: Automated item generation with recurrent neural networks