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Elizabeth S. Thrall; Fernando Martinez Lopez; Thomas J. Egg; Seung Eun Lee; Joshua Schrier; Yijun Zhao – Journal of Chemical Education, 2023
Given the growing prevalence of computational methods in chemistry, it is essential that undergraduate curricula introduce students to these approaches. One such area is the application of machine learning (ML) techniques to chemistry. Here we describe a new activity that applies ML regression analysis to the common physical chemistry laboratory…
Descriptors: Chemistry, Physics, Science Laboratories, Scientific Concepts
Ronald Soong; Katelyn Downey; Arvin Moser; Pablo Monje; Amy Jenne; Rajshree Ghosh Biswas; Monica Bastawrous; Rudraksha Majumdar; Daniel Henryk Lysak; Antonio Adamo; Benjamin Goerling; Venita Decker; Falko Busse; Santiago Dominguez; Effiette Sauer; Svetlana Mikhaylichenko; Vivienne Luk; Andre´ J. Simpson – Journal of Chemical Education, 2022
The recent popularity of benchtop (BT) NMR systems has prompted its applications in undergraduate laboratories around the world. Owing to their low maintenance cost, due to the lack of a superconducting magnetic core, and simple operation, these BT NMR systems can fulfill many of the learning objectives outlined in the undergraduate organic…
Descriptors: Undergraduate Study, College Science, Science Laboratories, Computer Assisted Instruction
Joss, Lisa; Müller, Erich A. – Journal of Chemical Education, 2019
Recent advances in computer hardware and algorithms are spawning an explosive growth in the use of computer-based systems aimed at analyzing and ultimately correlating large amounts of experimental and synthetic data. As these machine learning tools become more widespread, it is becoming imperative that scientists and researchers become familiar…
Descriptors: Science Instruction, Science Laboratories, Chemical Engineering, Educational Technology
Akin, H. Levent; Meriçli, Çetin; Meriçli, Tekin – Computer Science Education, 2013
Teaching the fundamentals of robotics to computer science undergraduates requires designing a well-balanced curriculum that is complemented with hands-on applications on a platform that allows rapid construction of complex robots, and implementation of sophisticated algorithms. This paper describes such an elective introductory course where the…
Descriptors: Robotics, Computer Science Education, Undergraduate Study, Introductory Courses
Sunal, Cynthia Szymanski; Karr, Charles L.; Sunal, Dennis W. – School Science and Mathematics, 2003
Students' conceptions of three major artificial intelligence concepts used in the modeling of systems in science, fuzzy logic, neural networks, and genetic algorithms were investigated before and after a higher education science course. Students initially explored their prior ideas related to the three concepts through active tasks. Then,…
Descriptors: Cooperative Learning, Course Content, Genetics, Science Laboratories