Call for Papers: Psychometrika, Applications and Case Studies (ACS)

Psychometrika is seeking submissions for a forthcoming Special Section on Leveraging AI to Empower Development and Application of Diagnostic Statistical Models.

Diagnostic statistical models are largely used in behavioral, educational, psychological, and health related applications to provide fine-grained information that can inform subsequent actions, such as instructions or interventions. These types of models are broadly defined, encompassing both latent class models and latent variable models, among others. Several decades of research have contributed to the development of various statistical models serving a variety of data types (e.g., binary, polytomous, continuous, etc.) and measurement scenarios (e.g., cross-sectional, longitudinal, large-scale, small-scale classroom assessment, etc.). In parallel, vast theoretical work has been conducted to establish model identification, and different algorithms have been developed to enable fast model estimation. Now, with the advancement of AI, such as large language models, it is expected that the diagnostic statistical models can be further expanded to accommodate high-dimensional data types (e.g., multimodal data, or process data) and be scaled up for real time feedback (e.g., adaptive learning platform).

In this special section, we invite authors to submit papers to advance integration of AI and diagnostic statistical models. Potential topics of interest include the following:

• Use of AI techniques (e.g., NLP, machine learning, Bayesian neural networks) to extract and validate Q-matrices or model latent attributes
• Hybrid models combining cognitive diagnostic models (CDMs) or multidimensional item response theory models (MIRTs) with deep learning, particularly for open-ended responses or process data
• Case studies showing how AI improves scalability, real-time diagnostics, or interpretability of CDMs or MIRTs in operational settings, such as in intelligent tutoring or adaptive learning systems
• Novel expansive applications of CDM in other domains, such as evaluating large language models (LLM) that are widely used in social and behavioral domains

This list is by no means exhaustive. We invite submissions on development and applications at the intersection of latent class models and AI. To be considered for this special section, manuscripts should have solid real data applications in psychological, educational, or social sciences. We especially encourage junior scholars to submit their research projects related to this topic.

The submission deadline is October 31st, 2025. Please see the following file for the full announcement, including all submission details for this call: 

Guest editors for this special issue are: Dr. Chia-Yi Chiu (cc5010@tc.columbia.edu) and Dr. Chun Wang (wang4066@uw.edu).