Luciana Cançado

Dr. Luciana Cançado is a Senior Research Scientist in Psychometrics at Curriculum Associates. In this role, Luciana provides leadership for the workstream of studies on the relationship between i-Ready Inform (formerly i-Ready Diagnostic) assessment results and state summative assessment performance. Luciana also conducts research in support of i-Ready Inform asessment growth, i-Ready Personalized Instruction, and has collaborated on research to understand the impact of the COVID-19 pandemic on student learning. She holds a Ph.D. in Educational Psychology with a concentration in Educational Statistics and Measurement from the University of Wisconsin-Milwaukee and an M.A. from Ohio University. Prior to pursuing the Ph.D. and joining CA, Luciana worked in information technology in various roles.

• Rome, L., & Cançado, L. (2021). Factors related to testing location during the 2020–2021 school year. Curriculum Associates.
• Porterfield, L., Nix, T., Cançado, L., & Linneman, N. (2019). Reshaping perceptions through experiences: Recruiting, promoting, and retaining high quality educators for urban districts. In C. R. Rinke & L. Mawhinney (Eds.), Opportunities and challenges in teacher recruitment and retention: Teachers' voices across the pipeline (pp. 229–257). Information Age Publishing.
• Cançado, L., Reisel, J. R., & Walker, C. M. (2018). Impact of first-year mathematics study groups on the retention and graduation of engineering students. International Journal of Mathematical Education in Science and Technology, 49(6), 856–866.
• Cançado, L., Reisel, J. R., & Walker, C. M. (2018). Impacts of a summer bridge program in engineering on student retention and graduation. Journal of STEM Education: Innovations and Research, 19, 26–31.

Academic Presentations

• Cañado, L., Xiong, J., & Rome, L. (2026, April). Comparing methods for estimating conditional growth percentiles for an interim assessment. Paper to be presented at the annual meeting of the National Council on Measurement in Education, Los Angeles, CA.
• Cañado, L., Valdivia Medinaceli, M., & Rome, L. (2026, April). Leveraging longitudinal data for comparability of interim assessment scores across administration conditions. Poster to be presented at the annual meeting of the National Council on Measurement in Education, Los Angeles, CA.
• Cañado, L., & Rome, L. (2023, April). Evaluating methods for predicting summative assessment performance from interim assessment results. Poster presented at the annual meeting of the National Council on Measurement in Education, Chicago, IL.
• Cañado, L., & Rome, L. (2022, April). Factors related to testing location during the 2020–2021 school year. In L. Rome (Chair), Issues in remote testing during the pandemic. Coordinated paper session presented at the annual meeting of the National Council on Measurement in Education, San Diego, CA.
• Cañado, L. (2020, April). Predicting summative assessment results from interim assessment performance using machine learning. Poster uploaded at the annual meeting of the National Council on Measurement in Education, held remotely.
• Cañado, L., & Azen, R. (2019, April). Predictor importance in multilevel longitudinal models: An empirical application of dominance analysis. Poster presented at the annual meeting of the National Council on Measurement in Education, Toronto, Canada.
• Cañado, L. (2018, October). Exploring the use of machine learning to predict summative assessment performance. In L. Rome (Chair), Where's my crystal ball?: Statistical methods for relating formative and summative assessments. Symposium conducted at the annual meeting of the Northeastern Educational Research Association, Trumbull, CT.
• Cañado, L., & Azen, R. (2018, July). Dominance analysis for determining predictor importance in longitudinal multilevel models. Paper presented at the International Meeting of the Psychometric Society, New York, NY.
• Azen, R., & Cañado, L. (2018, July). Measures of model fit for longitudinal multilevel models. Poster presented at the International Meeting of the Psychometric Society, New York, NY.
• Cañado, L., & Azen, R. (2018, April). Determining predictor relative importance in explanatory multilevel IRT models. Paper presented at the annual meeting of the National Council on Measurement in Education, New York, NY.
• Azen, R., & Cañado, L. (2016, July). Criticality analysis for multilevel model selection and predictor rankings. Poster presented at the International Meeting of the Psychometric Society, Asheville, NC.

National Council on Measurement in Education (NCME)