2022 Career Award for Lifetime Achievement
My 1994 Presidential Address “Evidence and inference in educational assessment” examined the interplay of probability-based reasoning and psychological perspectives in educational measurement through the lens of evidentiary reasoning (ER). Since that time there have been rapid developments in areas related to assessment—in technology, psychology, learning domains, and analytic methods. I begin here by recapping basic tenets of ER, its relationship to between-persons educational measurement models, and the complex adaptive sociocognitive systems view that can undergird assessment arguments. I then note insights and support that this framework provides for tackling current issues in educational assessment, such as the following:
- Assessments and measurement models in educational systems
- Assessment design
- Strengthening the connection between assessment and learning
- More complex forms of assessment such as those including simulations and interactivity
- Integrating psychometric and data-analytic concepts and methods in complex assessments
- Assessing high-level / 21st Century skills
- The situated meanings of models, variables, probabilities, and measurements
- The situated meanings of validity, reliability, comparability, generalizability, and fairness
About the Speaker
Robert Mislevy is Emeritus Professor at the University of Maryland and held the Frederic M. Lord Chair in Measurement and Statistics at Educational Testing Service from 2011 to 2021. He earned his Ph.D. in Methodology of Behavioral Research at the University of Chicago in 1981. His research interests apply developments in statistics, technology, and cognitive research to practical problems in educational assessment. His work has included a multiple-imputation approach for integrating sampling and test-theoretic models, an evidence-centered design framework for assessment, and psychometric methods for game- and simulation-based assessments. His publications include the Sociocognitive Foundations of Educational Measurement, Bayesian Psychometric Modeling (with Roy Levy), Bayesian Networks in Educational Assessment (with Almond, Steinberg, Yan, and Williamson), and Computational Psychometrics (co-edited with Alina von Davier and Jiangang Hao).
His honors and awards include AERA’s Lindquist Award, the National Council of Measurement’s Award for Career Contributions, and the National Council of Measurement in Education’s Annual Award for Significant Contributions to Educational Measurement (four times). He is a past president of the Psychometric Society, an AERA Fellow, a member of the National Academy of Education, and has served on National Academies of Science committees concerning assessment, instruction, and cognitive and sociocultural psychology.