Discipline: Biological Sciences
Subcategory: STEM Science and Mathematics Education
Tandabany Dinadayalane - Clark Atlanta University
Co-Author(s): Nathan J. Bowen , Clark Atlanta University
Computation is now regarded as an equal and essential element along with theory and experiment in the advancement of scientific knowledge and engineering practice. Currently, enormous opportunities are available in computational and data-enabled science and the demand in this area is expected to increase significantly in coming years. It is important to educate the next generation of undergraduate students to confront the challenges in computational and data science. At Clark Atlanta University (CAU), we have developed and pilot-tested two (2) new undergraduate courses: ‘Introduction to Computational Chemistry and Molecular Modeling’ and ‘Introduction to Computational Biology and Bioinformatics’ correspondingly in the Departments of Chemistry and Biological Sciences. The NSF funded HBCU-UP Targeted Infusion Project (TIP) enhances CAU’s academic cyberinfrastructure by adding computers and scientific software for computational chemistry and biology education integrated with research for undergraduate students. By the support of external evaluator, formative evaluation for the course development was undertaken to evaluate project elements which are relevant to project implementation. Findings from this evaluation are used to improve the course development products and process. Student perceptions regarding key areas of the course/laboratory were ascertained through a focus group type interview conducted with students enrolled in the newly developed courses. The findings of the students’ interviews will be presented. Students were unanimous in their agreement that they had learned a lot in these courses. The cumulative effect of newly developed courses ensures that they would be able to achieve the goal of being prepared to engage in advanced study and/or entry level employment in the area of computational chemistry and molecular modeling, as well as computational biology.
Funder Acknowledgement(s): NSF HBCU-UP TIP (Grant number 1623287).
Faculty Advisor: None Listed,