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Joe Olsen; Amy Adair; Janice Gobert; Michael Sao Pedro; Mariel O'Brien – Grantee Submission, 2022
Many national science frameworks (e.g., Next Generation Science Standards) argue that developing mathematical modeling competencies is critical for students' deep understanding of science. However, science teachers may be unprepared to assess these competencies. We are addressing this need by developing virtual lab performance assessments that…
Descriptors: Mathematical Models, Intelligent Tutoring Systems, Performance Based Assessment, Data Collection
Kent, Shawn C.; Wanzek, Jeanne; Yun, Joonmo – Grantee Submission, 2019
This study examined the predictive validity and classification accuracy of individual and group-administered screening measures relative to student performance on a year-end state reading assessment in two states. A sample of 321 students were assessed in the areas of word-level and text fluency, as well as reading comprehension in the fall of…
Descriptors: Screening Tests, Grade 4, Elementary School Students, At Risk Students
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Sao Pedro, Michael A.; Gobert, Janice D.; Betts, Cameron G. – Grantee Submission, 2014
There are well-acknowledged challenges to scaling computerized performance-based assessments. One such challenge is reliably and validly identifying ill-defined skills. We describe an approach that leverages a data mining framework to build and validate a detector that evaluates an ill-defined inquiry process skill, designing controlled…
Descriptors: Performance Based Assessment, Computer Assisted Testing, Inquiry, Science Process Skills