2018 ASEE Annual Conference &Amp; Exposition Proceedings
DOI: 10.18260/1-2--30798
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Measuring Student Learning of Crystal Structures Using Computer-based Visualizations

Abstract: In her current position at UC Davis, she is integrating computational modules into the undergraduate and graduate materials curriculum. She is specifically interested in students' computational literacy and life-long learning of computational materials science tools.

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“…Many studies to find out students' understanding and find the best strategy or model to teach the concept of crystal geometry have been conducted. However, the results showed that students had a low understanding of the concepts of crystal lattice and crystal symmetry, covalent bonds, metallic and ionic bonds, non-covalent bonds, molecular bonds, and crystal structures (Brock & Lingafelter, 1980;Gentry et al, 2018;Jones, 2018;Kelly et al, 2010;Steve Krause & Waters, 2012;Milenković et al, 2016;Politzer & Murray, 2017). These concepts are abstract concepts because they relate to very small particles.…”
Section: Introductionmentioning
confidence: 99%
“…Many studies to find out students' understanding and find the best strategy or model to teach the concept of crystal geometry have been conducted. However, the results showed that students had a low understanding of the concepts of crystal lattice and crystal symmetry, covalent bonds, metallic and ionic bonds, non-covalent bonds, molecular bonds, and crystal structures (Brock & Lingafelter, 1980;Gentry et al, 2018;Jones, 2018;Kelly et al, 2010;Steve Krause & Waters, 2012;Milenković et al, 2016;Politzer & Murray, 2017). These concepts are abstract concepts because they relate to very small particles.…”
Section: Introductionmentioning
confidence: 99%