Associate Professor Pace University NEW YORK, New York, United States
Session Description: The biological and environmental sciences have been rapidly and fundamentally reshaped by recent technological advances, including increased computational power, sensor technologies, publicly available software and data, and Internet connectivity. These advances, together with the demands that we provide our students with technical skills to navigate data and technology in the 21st century, necessitate the integration of computational data sciences into our undergraduate and graduate classrooms. However, many instructors do not feel qualified or prepared to teach such materials, either for lack of technical skills or pedagogical training, limiting the usefulness of already developed computational course or lab modules. This “train the teachers” short course will include both technical training for fundamental data science skills, including R and Markdown, and pedagogical training for communicating those skills in the classroom and lab. Working through data science examples in-real time, participants will experience the material as a learner and gain strategies toward including and being able to teach these skills in their own courses. Participants will also learn and practice the use of pedagogy techniques, such as backwards design, to envision how data science can be integrated within their courses. The goal is to equip instructors with technical tools and instructional strategies that they can then confidently customize to their own curricular goals and institutional needs.