Visit Project EDDIE at GSA 2019 in Phoenix

As they become more commonly available online, large environmental datasets provide new opportunities for instructors to teach quantitative reasoning and scientific concepts. However, curricular materials developed to help instructors use these resources need to be flexible and adaptable for a wide ranges of abilities, course types, and time limits. Project EDDIE (Environmental Data-Driven Inquiry and Exploration) modules are built with this flexibility in mind. Modules are scaffolded to progress from guided- to open-ended inquiry. As well as student handouts, modules include extensive supporting information for instructors, with the intention that they will be able to modify these as appropriate for their course, students, and learning goals. We have found that Project EDDIE modules can be effective in achieving the overall conceptual scientific and quantitative reasoning goals across a wide range of courses and approaches.

The EDDIE Climate Change module provides an example of the flexible approach of the EDDIE modules. This module uses global temperature and atmospheric CO2 datasets to explore current rates of change, and to compare those to rates that are calculated using Vostok Ice core data. Students are asked to reach their own conclusions regarding how modern changes compare with past change, and what this might imply about the role of human activity in current climate change. As with all modules, one key component is that students make their own decisions about how to use the data, in this case selecting the time frames that they want to use.

We demonstrate the flexibility of the EDDIE Climate Change module by illustrating how it has been modified in structure and approach by instructors. Variations of this module have been used across a range of ages, from middle school students to retired professionals. The module has been adapted for use in 4-hour laboratory sessions, 50-minute lecture periods, and for out-of-class assignments. Instructors have developed alternative approaches to fit their needs, such as providing students with cleaned datasets vs. having them access the data online, and providing hard copies of graphs to be used for simplified calculations vs. having the students graph the data themselves. The flexible and adaptable nature of EDDIE modules allows them to be widely used to improve quantitative reasoning and to engage participants in working with large authentic datasets on real-world problems.

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.