This learning module (and associated instructor’s guide) was developed by CSAFE researcher and criminology, law, and society professor from University of California, Irvine Dr. Simon Cole. The educational opportunity uses latent print identification as a case study of the broader category of forensic pattern recognition evidence. This in turn reflects the interaction between science, law, and policy. The module has been explicitly designed for non-scientists from a variety of different backgrounds including law and public policy. Based on an active learning approach, the module is based on scientific and legal literature, policy documents, and court exhibits and opinions. Learn more and view the module on the National Academies of Sciences, Engineering, and Medicine website.
Forensic Pattern Recognition Evidence-An Educational Module
Related Resources
Forensic Footwear: A Retrospective of the Development of the MANTIS Shoe Scanning System
There currently are no shoe-scanning devices developed in the United States that can operate in a real-world, variable-weather environment in real-time. Forensics-focused groups, including the NIJ, expressed the need for…
A Quantitative Approach for Forensic Footwear Quality Assessment using Machine and Deep Learning
Forensic footwear impressions play a crucial role in criminal investigations, assisting in possible suspect identification. The quality of an impression collected from a crime scene directly impacts the forensic information…
Enhancing forensic shoeprint analysis: Application of the Shoe-MS algorithm to challenging evidence
Quantitative assessment of pattern evidence is a challenging task, particularly in the context of forensic investigations where the accurate identification of sources and classification of items in evidence are critical.…
Computational Shoeprint Analysis for Forensic Science
Shoeprints are a common type of evidence found at crime scenes and are regularly used in forensic investigations. However, their utility is limited by the lack of reference footwear databases…



