Call for Papers on "Bridging the Gap between Machine Learning and Psychological Measurement"

Behaviormetrika announces a special issue on the integration of machine learning with classification methods in psychological and behavioral measurement. Despite the seemingly opposing goals of classification and scaling, this issue explores their compatibility in various measurement contexts. The aim is to guide the effective use of classification methodology for measurement purposes, given the rapid advancements in classification methods in machine learning. Researchers from diverse fields are invited to contribute original research in areas such as integrating machine learning with diagnostic classification models, Bayesian classification methods, confirmatory deep learning approaches for psychological assessment, item response theory combined with machine learning, computerized adaptive testing with machine learning, interdisciplinary applications in educational and behavioral measurement, innovative psychometric approaches using machine learning, and ethical considerations in machine learning for psychological and behavioral classification. The focus is on approaches aligned with confirmatory measurement, excluding purely exploratory or unsupervised methods.


Important Dates

  • Manuscript submission deadline: February 1, 2024
  • First round of reviews: May 1, 2024
  • Revisions due: July 1, 2024