PROJECT EDDIE: SUPPORTING TEACHING QUANTITATIVE REASONING USING LARGE DATA SETS

The availability and wealth of large, environmental datasets creates opportunities to teach scientific concepts and quantitative reasoning with these data. A new NSF-funded component of Project EDDIE (Environmental Data-Driven Inquiry and Exploration) is focused on developing and expanding a self-sustaining community of instructors able to effectively use and develop teaching materials that use large datasets to teach scientific concepts and quantitative reasoning. The community will build a shared vision that starts with understanding the best practices and strategies for improving the teaching of quantitative reasoning using data in the classroom and identifying gaps in available .

We found that instructors perceive multiple benefits of using data in their teaching to develop quantitative reasoning in undergraduate students, including increasing student engagement, bolstering students’ academic and professional skills, increasing scientific literacy, and helping students understand the value of science. Instructors also identified a variety of challenges to developing students’ quantitative reasoning via the use of large datasets, including a lack of confidence and skills among both students and faculty and inadequate resources. Participants noted that Project EDDIE could play an important role in mitigating these challenges by continuing to facilitate the development of teaching modules that support and guide faculty as they incorporate real-world data into their teaching of a student body that is diverse in motivation, self-efficacy, and skill-level. In addition, instructors identified interest in a community of practice of faculty members who can share challenges and successes in implementing EDDIE modules in their classrooms.

Findings are currently informing professional development opportunities, including the upcoming EDDIE Module Design and Development Workshop (https://serc.carleton.edu/216830). Each module will focus on specific scientific concepts and address a set of quantitative reasoning or analytical skills, using large datasets that are publicly available online.