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Higman, Carolyn S.; Situ, Henry; Blacklin, Peter; Hein, Jason E. – Journal of Chemical Education, 2017
Advances in 3D printing technology over the past decade have led to its expansion into all subfields of science, including chemistry. This technology provides useful teaching tools that facilitate communication of difficult chemical concepts to students and researchers. Presented here is the use of 3D printing technology to create tangible models…
Descriptors: Undergraduate Study, College Science, Chemistry, Hands on Science
Makarevitch, Irina; Frechette, Cameo; Wiatros, Natalia – CBE - Life Sciences Education, 2015
Integration of inquiry-based approaches into curriculum is transforming the way science is taught and studied in undergraduate classrooms. Incorporating quantitative reasoning and mathematical skills into authentic biology undergraduate research projects has been shown to benefit students in developing various skills necessary for future…
Descriptors: Student Research, Research Projects, Data Analysis, Research Skills
Albert Y. Kim; Adriana Escobedo-Land – Journal of Statistics Education, 2015
We present a data set consisting of user profile data for 59,946 San Francisco OkCupid users (a free online dating website) from June 2012. The data set includes typical user information, lifestyle variables, and text responses to 10 essay questions. We present four example analyses suitable for use in undergraduate introductory probability and…
Descriptors: Statistics, Introductory Courses, Data, Educational Practices
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection