ix
Foreword
I work in what is called educational measurement: some applications, some methods, some theory. My applications have focused on capabilities people develop in
school, work, and recreation (what Herb Simon called “semantically rich domains”),
such as standardized tests in science and reading comprehension, and less familiar
assessments with studio art portfolios and simulations for troubleshooting computer
networks and dental hygienists’ procedures. The methods are mainly latent variable
models such as item response theory (IRT; more about this later). My theoretical
work has been on task design, validity, cognition and assessment, and, our reason
for gathering together, measurement. It is from this belvedere, dear reader, that I
offer my thoughts on Luca Mari, Mark Wilson, and Andrew Maul’s Measurement
Across the Sciences: Developing a Shared Concept System for Measurement.
1
By
reflecting on how this system both strengthens and challenges the inquiries of those
of us in educational measurement, I hope to share what I find interesting, important,
and energizing across any and all disciplines.
Educational Assessment and Educational Measurement
I say that I work in “what is called educational measurement” because most of what
most of us do, most of the time, is applications and methods. Millions of assessments are done every year, producing scores that affect individuals and institutions
1 I have not cited sources rigorously in this more informal preface. I have drawn on Kuhn, T.S.
(1961). The function of measurement in modern physical science. Isis, 52(2), 161–193; Markus,
K.A., & Borsboom, D. (2013). Frontiers of test validity theory: Measurement, causation, and
meaning. New York: Routledge; Michell, J. (1999). Measurement in psychology: A critical history
of a methodological concept. Cambridge: Cambridge University Press; Porter, T.M. (2020). Trust
in numbers: the pursuit of objectivity in science and public life. Princeton University Press;
Wilbrink, B. (1997). Assessment in historical perspective. Studies in Educational Evaluation, 23,
31–48; and others, including the references that appear in Mislevy, Robert J. (2018). Sociocognitive
foundations of educational measurement. New York/London: Routledge.
Foreword
I work in what is called educational measurement: some applications, some methods, some theory. My applications have focused on capabilities people develop in
school, work, and recreation (what Herb Simon called “semantically rich domains”),
such as standardized tests in science and reading comprehension, and less familiar
assessments with studio art portfolios and simulations for troubleshooting computer
networks and dental hygienists’ procedures. The methods are mainly latent variable
models such as item response theory (IRT; more about this later). My theoretical
work has been on task design, validity, cognition and assessment, and, our reason
for gathering together, measurement. It is from this belvedere, dear reader, that I
offer my thoughts on Luca Mari, Mark Wilson, and Andrew Maul’s Measurement
Across the Sciences: Developing a Shared Concept System for Measurement.
1
By
reflecting on how this system both strengthens and challenges the inquiries of those
of us in educational measurement, I hope to share what I find interesting, important,
and energizing across any and all disciplines.
Educational Assessment and Educational Measurement
I say that I work in “what is called educational measurement” because most of what
most of us do, most of the time, is applications and methods. Millions of assessments are done every year, producing scores that affect individuals and institutions
1 I have not cited sources rigorously in this more informal preface. I have drawn on Kuhn, T.S.
(1961). The function of measurement in modern physical science. Isis, 52(2), 161–193; Markus,
K.A., & Borsboom, D. (2013). Frontiers of test validity theory: Measurement, causation, and
meaning. New York: Routledge; Michell, J. (1999). Measurement in psychology: A critical history
of a methodological concept. Cambridge: Cambridge University Press; Porter, T.M. (2020). Trust
in numbers: the pursuit of objectivity in science and public life. Princeton University Press;
Wilbrink, B. (1997). Assessment in historical perspective. Studies in Educational Evaluation, 23,
31–48; and others, including the references that appear in Mislevy, Robert J. (2018). Sociocognitive
foundations of educational measurement. New York/London: Routledge.