This project addresses a critical need: updating the physics curriculum to bring our students’ learning in line with the way physics is practiced, and to expand their career prospects beyond academic research. The curriculum can benefit from many changes, but we are focusing on one. We are incorporating computational methods across all our courses, with two key goals: (1) our students will graduate feeling that computational techniques are a “normal” way to solve problems, and (2) that they will have the skills and confidence to put this into practice. These goals are important for many reasons. Computational methods are an essential skill in both traditional and non-traditional career paths for our students.
1. How can we create an environment in which our students adopt the attitudes and learn the skills we have identified?
2. How can we measure the results of our work?
3. How can we assure that our work is sustained in our own department, and disseminated broadly?
The primary deliverables of this work are curricular materials, assessment tools, and documentation of our departmental change process. We have disseminated our work, to date, in publications, conference talks, electronic resources, and webinars. This poster will provide readers with a summary of our efforts and links to our materials. We will emphasize our assessment efforts, particularly our development of a survey intended to measure students’ attitudes and self-efficacy with respect to key computational methods. Students complete the survey each semester that they take a physics course. This allows us to study, e.g., the points in the curriculum at which students gain confidence with specific methods or adopt more expert-like attitudes regarding computation in general. The outcomes to date include evidence supporting the validity and reliability of the instrument, and data showing that some aspects of students’ attitudes and self-efficacy develop steadily, while other aspects develop at specific points in the curriculum. We will also describe next steps for the project, including an effort to develop a two-tiered system of rubrics intended to support measurement of our student learning objectives.
Computational methods also expand the range of problems students can address. Rather than limiting students to analytically solvable questions, we can introduce students to a wide range of problems, enhancing the connections between their learning and “real world” issues. The impacts of this work go far beyond our students’ ability to solve physics problems. By giving students a richer set of tools to tackle large, complex problems, we enable our graduates to contribute to society in a variety of new ways. Rather than focusing on exactly solvable situations, they may be inspired and empowered to tackle challenges of sustainability, climate change, social disruption, epidemiology, neuroscience, and other areas that require computational approaches.
Gautam Vemuri, Indiana University Purdue University Indianapolis (IUPUI), Indianapolis, IN