Poster presented at the 2019 Annual International Dyslexia Association Conference. Portland, OR. Abstract: This study examines the validity of Lexplore, a new method for screening students for reading difficulties that uses eye tracking technology and machine learning models to assess oral and silent reading fluency. Lexplore was incorporated into the standard benchmark assessment battery at several elementary schools (N = 1,700 students) during the 2018– 2019 school year. Concurrent and predictive validity will be examined through correlational analyses, receiver operating characteristic (ROC) curve analyses, classification accuracy statistics, and logistic regression.

{"references": ["Benfatto, M. N., Seimyr, G. \u00d6., Ygge, J., Pansell, T., Rydberg, A., & Jacobson, C. (2016). Screening for Dyslexia Using Eye Tracking during Reading. PloS one, 11(12), e0165508."]}