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Travis T. Fuchs; Mike Arsenault – School Science Review, 2017
Students, as well as teachers, often learn what makes sense to them, even when it is wrong. These misconceptions are a problem. The authors sought a quick, quantitative way of identifying student misconceptions in secondary science. Using the University of Toronto's National Biology Competition test data, this article presents a method of quickly…
Descriptors: Science Education, Secondary School Science, Misconceptions, Scientific Concepts
Kalas, Pamela; O'Neill, Angie; Pollock, Carol; Birol, Gulnur – CBE - Life Sciences Education, 2013
We have designed, developed, and validated a 17-question Meiosis Concept Inventory (Meiosis CI) to diagnose student misconceptions on meiosis, which is a fundamental concept in genetics. We targeted large introductory biology and genetics courses and used published methodology for question development, which included the validation of questions by…
Descriptors: Scientific Concepts, Misconceptions, Genetics, Introductory Courses
Nagy, Philip – 1978
This study assessed the construct validity of a cognitive structure interpretation of multidimensional scaling solutions of concept similarity data. Using high school subjects, convergent validity was assessed through correspondence of scaling solutions of three similarity rating tasks; word association, similarity judgment, and semantic…
Descriptors: Cognitive Development, Cognitive Measurement, Cognitive Style, Data Analysis