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Psychometrics Lab (Haruhiko Mitsunaga)
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The lab is a psychometrics lab that applies test theory to improving actual tests and classroom teaching.
AboutAbout the lab
Test theory, applied to real tests and lessons.
In this lab, Associate Professor Haruhiko Mitsunaga specializes in psychometrics, educational measurement, and test theory.
The research themes are practical research on applying item response theory (IRT) to tests, and research on item response models and their application to actual tests.
Currently, the lab is examining a method that uses statistical techniques called cognitive diagnostic models to capture the fine-grained aspects of students' academic ability, so that teachers can use the results to improve their lessons.
Key terms
- Item response theory
- An analytical approach that expresses examinees' overall ability on a one-dimensional scale from their response data on a test. Also called IRT
- Cognitive diagnostic model
- A statistical method that specifies the skills (attributes) required for each question and estimates each individual's mastery from correct/incorrect response data
- Enemy items
- A pair of test questions in which the wording of one gives a hint for solving another question that appears later
ResearchResearch themes
The lab conducts research on applying test theory, such as item response theory (IRT), to actual tests. It analyzes data from academic achievement surveys and tests, and explores how to use the results to improve lessons and test administration.
Improving Lessons with Cognitive Diagnostic Models
In collaboration with researchers at other universities and elsewhere, the lab fits cognitive diagnostic models to data from students' academic achievement surveys to capture the fine-grained aspects of their ability, and is examining a method for teachers to use the results to improve lessons. In the first year, it identified the characteristics of where students at each grade level stumble, using arithmetic survey data.
Measuring the "Depth of Learning" in Arithmetic and Mathematics
In collaboration with researchers at other universities and elsewhere, the lab studied a method for judging each student's degree of depth of learning in elementary and junior high school arithmetic and mathematics. The method uses correct/incorrect response data on questions that ask whether each assessment aspect (attribute) is present. The lab also explored how teachers can use the results to improve their lessons.
Detecting Enemy Items in Language Tests
In large-scale computer-based tests, the lab developed a method that detects pairs of enemy items based on word similarity, in order to prevent the questions in a test from hinting at one another. The method was suggested to be effective for English and Japanese language tests.
MembersFaculty
- Associate ProfessorHaruhiko Mitsunaga
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