Numerical Problem Solving Across the Curriculum with Python and MATLAB Using Interactive Coding Templates: A Workshop for Chemical Engineering Faculty

With the fourth industrial revolution well underway, the proportion of occupations requiring "high" or "medium" digital skills has never been greater. Among those most in demand are engineers skilled in computing and advanced problem solving to support the ongoing digitalization, networking, and automation. A numerical analysis course in the core undergraduate engineering curriculum is a natural place for students to learn numerical methods for advanced problem solving across engineering applications. The use of computing across the entire chemical engineering curriculum also offers opportunities to hone students' abilities as computational thinkers and effective problem solvers to meet the current and future needs of an increasingly complex and digital industry and society. While the current chemical engineering curriculum includes computational training, there is a need to efficiently increase the exposure of students to computing within mathematical problem-solving contexts and develop their proficiency in computer programming, all while balancing demands to reduce credit hours. Some chemical engineering faculty interested in enhancing the computational nature of their courses face a barrier to doing so due to unfamiliarity with some modern computational educational resources that may not have been covered in their training or may not be used in their research areas. The authors developed a workshop to teach chemical engineering faculty to use and develop interactive coding templates (MATLAB Live Scripts and Jupyter Notebooks) and to equip faculty to incorporate these techniques across the undergraduate curriculum. The workshop was presented at the 2022 ASEE/AIChE Summer School for Engineering Faculty. The purpose of this paper is to disseminate the workshop resources, providing educators with a suite of interactive templates focused on chemical engineering-related case studies and with training to create and adapt their own related materials. The paper details the interactive coding templates provided during the workshop along with the relevant pedagogical background and some lessons learned for future related workshops. Educators who did not attend the workshop are also a target audience of this paper as it provides tips and access to the relevant materials for implementing computational thinking through interactive coding templates into their classroom practices.