The Potential of Machine Learning Methods in Psychological Assessment and Test Construction

The goal of this editorial is to provide a brief overview of the potential of machine learning (ML) methods in psychological assessment and test construction. In the following, the authors focus on three applications they believe more research is needed on and which the European Journal of Psychological Assessment ( EJPA) would welcome: (1) automated item generation, (2) automated test assembly, which both focus on test construction, and (3) clinical decision support systems, which address questions relevant to the psychological assessment and diagnosis of individuals. In addition, the authors (re-)introduce the technique of cross-validation. The authors end with noting some benefits, but also problems, of ML, highlighting open questions, and identifying future directions for the field of psychological assessment and test construction. (PsycInfo Database Record (c) 2024 APA, all rights reserved)