Paper No. 336-3
Presentation Time: 2:15 PM
TRANSLATING CLIMATE-ORIENTED PROFESSIONAL DEVELOPMENT EXPERIENCES INTO LIBERAL ART EDUCATION VIA CONTENT EMBEDDING ACROSS CURRICULUM
St. Thomas University is a four-year liberal art college and a minority serving institution with a predominantly Hispanic population. For three consecutive semesters Physical Science general education courses were not offered and were instead substituted with computer technology training. In this academic climate, an important question for STEM faculty is how can climate awareness and quantitative literacy best be taught to support our students as future decision makers? In an exploratory pilot experience at the level of the School of Science for the last three semesters, a group of topics based on materials discussed in the Climate Diversity Project as well as in MSI-REaCH program were explored for potential translation into the existing courses/curriculum. As a result, the more feasible in our conditions were: (1) Climate and weather motivated exercises and case discussions adapted from above mentioned workshops were introduced into the curriculum of Calculus, Statistics, College and University Physics and Differential Equations as well as in General Chemistry and Biology which are part of the requirements students have to complete in order to graduate, (2) Summer Research Internships with undergraduate research projects that focus on the potential impacts of changing weather conditions on plants, human health, and weather-society relationships, and (3) Integration of datasets from a variety of sources into above-mentioned courses. This integrated and data rich approach required an interdisciplinary effort to teaching, a database-driven and computer assisted education, a better understanding of the associations between student expectations, job market expectations, and skills to be developed, and a strong professional development from the end of Faculty involved in all these changes. After a year and a half of transition to alternative solutions, about 60 % of junior and senior STEM majors are able to work with R-software, while a minor percent (about 30%) of non STEM majors started being introduced into it. Some students can already perform comprehensive statistical analysis of time series, differentiating short-term variations from long term ones, do entry level modeling and coding, and are able to establish associations between physical, economic, and societal variables.