Python Programming in the Sort-of Flipped Physical Chemistry Classroom
Abstract
For many chemistry students, physical chemistry represents their most challenging course within the major. The integration of topics covered in calculus, physics, and previous chemistry courses leaves many students feeling overwhelmed and under prepared when they walk in on the first day of class. The material presented in physical chemistry courses is abstract and multidimensional which can make it difficult for students to comprehend the concepts. In order to overcome these hurdles we have developed a series of Python-based, guided-inquiry assignments which facilitate student engagement in the physical chemistry classroom. As part of the assignments the students watch YouTube videos and read handouts related to the task prior to coming to class. In class, they work independently to both edit pre-written and write new code, which they apply to answer conceptual and numerical questions. The advantage of these assignments over traditional lecture approaches is that they can be used to (1) readily produce 3-D surface plots which allow the students to visualize the interdependence of physical variables, (2) remove some of the mathematical burden by performing numeric and symbolic integration and differentiation, and (3) introduce experimental date in conjunction with simplified model systems. Additionally, these assignments introduce valuable computational skills to a cohort of undergraduate STEM majors who rarely take computer science courses.
Session
Session 3B: Blended Approaches to Teaching Computational Skills
Location
Dalton 119
Start Date
5-20-2015 3:15 PM
End Date
5-20-2015 4:30 PM
Python Programming in the Sort-of Flipped Physical Chemistry Classroom
Dalton 119
For many chemistry students, physical chemistry represents their most challenging course within the major. The integration of topics covered in calculus, physics, and previous chemistry courses leaves many students feeling overwhelmed and under prepared when they walk in on the first day of class. The material presented in physical chemistry courses is abstract and multidimensional which can make it difficult for students to comprehend the concepts. In order to overcome these hurdles we have developed a series of Python-based, guided-inquiry assignments which facilitate student engagement in the physical chemistry classroom. As part of the assignments the students watch YouTube videos and read handouts related to the task prior to coming to class. In class, they work independently to both edit pre-written and write new code, which they apply to answer conceptual and numerical questions. The advantage of these assignments over traditional lecture approaches is that they can be used to (1) readily produce 3-D surface plots which allow the students to visualize the interdependence of physical variables, (2) remove some of the mathematical burden by performing numeric and symbolic integration and differentiation, and (3) introduce experimental date in conjunction with simplified model systems. Additionally, these assignments introduce valuable computational skills to a cohort of undergraduate STEM majors who rarely take computer science courses.