PIs: John Symms, Jane Hopp
This workshop is funded through the “Dear Colleague Letter: Principles for the Design of Digital Science, Technology, Engineering, and Mathematics (STEM) Learning Environments (NSF 18-017).” Driven by rapid technological change, the United States is facing a critical workforce shortage in science, technology, engineering, and mathematics (STEM) professions. Furthermore, employers across all fields are increasingly seeking employees who possess computational thinking and data science and analytics skill sets. Eighty percent of the nation’s colleges and universities are classified as small institutions and enroll 5,000 or fewer students. Many of these small colleges and universities are grounded in the liberal arts and have a tradition of infusing personalized learning and common thought across disciplines within their general education curricula. This makes them particularly well-suited for preparing students in human literacy, technological literacy, and data literacy. Because computational thinking and data science and analytics work is most often conducted digitally, it is imperative that students learn these skills in digital environments to prepare them for what they will encounter in the workplace. The next generation of digital learning environments encompassing five areas (interoperability; personalization; analytics, advising, and learning assessment; collaboration; and accessibility and universal learning design) will be used by students to learn data science and analytics skill sets. Small colleges and universities often lack the financial resources to build the necessary human and technological infrastructure to support digital learning. This workshop will design digital learning environments that will meet the substantial need for data science and analytics-educated professionals, promote equity in learning, and assist small liberal arts colleges and universities to contribute to the early development of these efforts. Experts will advise teams to design digital science and analytics curricula that will be incorporated in blueprint designs for next generation of digital learning environments meeting the needs of learners and the workforce.
The goal of the project is to convene a workshop that results in blueprint designs of next generation of digital learning environments to answer the question – How can science, technology, and mathematics digital learning environments be designed to enhance the digital science and data analytic skill competencies of learners at small liberal arts institutions of higher education? The research questions include: 1) How will the innovative digital learning environments prepare students for employment that requires data science and analytics? 2) How will the design of data science and analytics digital learning environments account for the variability of learners? 3) How will data be collected and learning environments assessed to measure students’ data science and analytics competency? 4) How will a national consortium form and function to sustain and expand the workshop outcomes? Based on the tradition in small liberal arts colleges and universities of offering personalized learning, universal design learning for technology will be emphasized and serve as a model for supporting more underrepresented students in STEM to persist to graduation. The complexity of data sciences and analytics skill sets require an assessment of the workshop participants’ progress toward meeting the planned outcomes, and education on individual motivations, both which are done through team science. Team science is also innovatively incorporated into the data science and analytics undergraduate curriculum design to educate students how their skills can contribute to a greater product that is the result of the collective contribution of the multidisciplinary team. The project draws upon the expertise of national experts who provide content knowledge not otherwise available to small liberal arts colleges and universities. The forming of a national consortium for digital learning at small liberal arts colleges and universities will sustain and expand the workshop outcomes. It will provide authentic hands-on digital learning research experience through curriculum innovations that introduce students to computational thinking, data science, and analytic skills. The result will be prepared students who fit the workforce need in this area.