Natalie Jorion is a psychometrician interested in the scoring and validation of innovative item types, text mining, and learning analytics.  She has developed Shiny apps for DIF panels and Standard Settings. She is currently working on designing and validating assessments to measure organizational cybersecurity resilience.

She has a PhD in learning sciences from the University of Illinois at Chicago with a specialization in measurement and assessment, and an MA from Northwestern University.  For her dissertation, she designed an evidence-based diagnostic assessment of conceptual understanding and common misunderstandings in statistics. She has peer reviewed papers for Journal of Engineering Education, International Journal of STEM Education, Special Interest Group on Computer-Human Interaction, and the National Council of Measurement in Education Conference.

In 2016, she was awarded an NSF data science fellowship to create visualizations of learner interactions in informal multimodal STEM games.