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Assessing the demands of science tasks in education is an area of intense research. One way of ensuring beneficial learning is using tasks with proper cognitive demand (CD). While there are multiple frameworks examining CD in science education, these frameworks use product data and do not consider cognitive process data. As neurocognitive tools to assess CD make their way into education, understandings of how to use these tools becomes important. The intent of this study is to examine a current task-based framework, Task Analysis Guide in Science (TAGS) using neurocognitive data. Analysis of neurological data from 60 ninth grade students using mixture models illustrates a mismatch between neurocognitive data and traditional Task Analysis i.e. TAGS when assessing CD.
Richard Lamb, East Carolina University
Troy D. Sadler, University Of North Carolina at Chapel Hill
Knut Neumann, Leibniz Institute for Science and Mathematics Education
David L. Fortus, Weizmann Institute of Science
Pasha Antonenko, University of Florida
Amanda Kavner, East Carolina University
Douglas Hoston, Buffalo State College – SUNY