Since 2000, Michelle Boyer has supported countries, states, and local educational authorities in the design and implementation of large-scale assessments. She has supported statewide summative and end-of-course assessment programs with assessment design, implementation, peer-review, research studies, and standard setting in Alabama, Arizona, Florida, Indiana, Kentucky, Missouri, New York, Pennsylvania, West Virginia, Wisconsin, and the Smarter Balanced Assessment Consortium. She has also supported the country of Qatar with the design and development of its large-scale summative testing program, and a pilot of a school level Programme for International Student Assessment (PISA) in the United States, United Kingdom, and Canada. This pilot led to her work on the inaugural implementation of the OECD Test for Schools in the United States.
COVID-19 Response Assessment Accountability
Implications of School Closures on Assessment Needs
Michelle Boyer March 24, 2020
According to Education Week, “as of March 23, 2020, 7:31 p.m. ET: 46 states have decided to close schools. Combined with district closures in other states, at least 123,000 U.S. public and private schools are closed, are scheduled to close, or were closed and later reopened, affecting at least 54.8 million students”.
Educational Assessment Scoring Automated Scoring Validity Test Score Reliability Assessment
Rater Monitoring with Inter-Rater Reliability may Not be Enough for Next-Generation Assessments
Michelle Boyer January 28, 2020
Testing experts know a lot about how to conduct scoring of students’ written responses to assessment items. Raters are trained under strict protocols to follow scoring rules accurately and consistently. To verify that raters did their job well, we use a few basic score quality measures that center on how well two or more raters agree. These measures of agreement are called inter-rater reliability (IRR) statistics, and they are widely used, perhaps in part because they are easy to understand and apply.
Understanding How Machine Scoring Can Be Used Now, and What We Need to Do to Expand Its Usefulness for the Future
Michelle Boyer July 29, 2019
Without a doubt, the public is skeptical about using machine scoring for examinees’ written responses. This skepticism makes sense because we know that machines do not score all elements of writing equally well. Machines do not “understand” creativity, irony, humor, allegory, and other literary techniques, opening them to criticism for their insufficiency in evaluating some of these more subtle qualities of writing.
Using Advances in Technology to Improve the Quality of Educational Assessment
Michelle Boyer June 25, 2019
Earlier this month, the Center for Assessment held its 15th annual colloquium, the first named in honor of Center co-founder, Brian Gong. The Brian Gong Colloquium is a two-day meeting arranged by the Center for Assessment to discuss select topics of importance in testing and accountability with recognized experts.
The 2019 meeting focused on the present and future use of learning analytics, machine learning, and artificial intelligence in educational assessment, and highlighted topics including:
