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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
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Benzer, Ali Ihsan; Ünal, Suat – Journal of Baltic Science Education, 2021
This research examined articles about models and modelling in the context of science education in Turkey by using content analysis method. Two specific academic databases; one of which was Dergipark, a platform including the academic journals published in Turkey, and Scholar Google were examined in detail so that totally 71 articles on models and…
Descriptors: Foreign Countries, Science Education, Mathematical Models, Educational Research
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Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F. – International Journal of Testing, 2016
The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…
Descriptors: Achievement Tests, Foreign Countries, Elementary Secondary Education, Science Achievement
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Collins, Michael P. S.; Alexander, John J., Ed. – Journal of Chemical Education, 1979
Presents an undergraduate physical chemistry question and its acceptable solution. This question, presented to share exam questions with other teachers, shows the analogy between molecular kinetics and population dynamics. (HM)
Descriptors: Chemistry, College Science, Higher Education, Mathematical Models
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Wilson, Mark; Adams, Raymond J. – Journal of Educational Statistics, 1993
A marginal maximum likelihood estimation algorithm is presented for the ordered partition model of M. Wilson that does not require the set of available responses to be fully ordered. The model and its estimation algorithm are illustrated in a comparison of alternative scoring schemes for open-ended science items. (SLD)
Descriptors: Algorithms, Comparative Analysis, Elementary Secondary Education, Equations (Mathematics)