Research and management of aquatic ecosystems toward resiliency goals requires long-term monitoring. Monitoring systems, such as the Integrated Ocean Observing System, Long Term Ecological Research Networks, and the Ocean Observatories Initiative, stream large volumes of data. These datasets are complex in not only their size, but also in the variety of types of data and multiple overlapping signals in real-world systems. The next generation of aquatic scientists need strong data literacy skills to be able to synthesize these datasets and interpret drivers of ecosystem change. Therefore, it is critical that higher education experiences build students’ skills in working with authentic data at all levels. Presentations focused on new opportunities to engage undergraduate students in authentic data experiences using real-world datasets to teach aquatic science processes are welcomed. Discussions may include classroom curriculum, other training of data skill development at the undergraduate or graduate level, data management, use of software for accessing and interacting with data, data visualization, pattern interpretation, and related skills needed to make meaning of complex, real-world data.
Lead Organizer: Denise Bristol, Hillsborough Community College - SouthShore (dbristol@hccfl.edu)
Co-organizers:
Anna Pfeiffer-Herbert, Stockton University (Anna.Pfeiffer-Herbert@stockton.edu)
Janice McDonnell, Rutgers University (mcdonnel@marine.rutgers.edu)
Presentations
09:00 AM
Building a community to engage students in data from the NSF Ocean Observatories Initiative to enhance data literacy: The OOI Data Labs design workshop model (9634)
Primary Presenter: Charles Lichtenwalner, Rutgers University (sage@marine.rutgers.edu)
Introductory courses in oceanography typically cover a wide range of ocean science concepts, but often spend little time with authentic datasets, apart from idealized data depictions found in many textbooks. For many undergraduate students, these courses may be one of the few opportunities they have to engage in scientific practices like analyzing and interpreting data. Since 2018, the OOI Data Labs project has worked to engage a community of undergraduate educators in collaboratively developing practical, data-focused activities that connect datasets and science from the NSF Ocean Observations Initiative (OOI) with concepts taught in typical oceanography courses. The community-developed collection of activities includes several dozen web-based interactive “Data Explorations” and an online “Lab Manual” of activities. These resources were developed through a series of iterative design workshops, which included sessions on effective pedagogy, data literacy skills, and scaffolding oceanographic concepts with relevant datasets from the NSF OOI. This past fall, we gathered community members to develop a 3rd edition of the Lab Manual with new and revised activities. The next version will also add several Python notebook-based activities, allowing students to use a guided inquiry-based approach to explore additional relevant datasets. We will share our design approach, lessons learned in engaging the community, and the challenges of translating datasets for use in student activities.
09:15 AM
CREATING AN UNDERGRADUATE OCEANOGRAPHY LAB EXERCISE: FROM OOI DATA EXPLORER TO OOI DATA LAB (9004)
Primary Presenter: Jean Anastasia, Suffolk County Community College (anastaj@sunysuffolk.edu)
In this session I will walk attendees through the process of data lab design, which can be replicated by instructors of oceanography and modified for their own classes. I will demonstrate the process used in creating a data lab focused on water masses: from identifying important oceanographic concepts and defining learning objectives, to finding authentic and current oceanographic data, to designing a student lab activity that follows the learning cycle to ensure student engagement and learning. I will highlight how to use the Ocean Observatory Initiative’s (OOI) data explorer to find data and showcase the OOI Data Labs project template to create a new data lab.
09:30 AM
USING MULTIPLE REAL-WORLD DATASETS TO BUILD DATA LITERACY AMONG UNDERGRADUATE STUDENTS IN ASYNCHRONOUS ONLINE INTRODUCTION TO OCEANOGRAPHY LABS (9491)
Primary Presenter: Margaret Blome, East Carolina University (blomem19@ecu.edu)
Introductory Oceanography textbooks illustrate and explain oceanographic processes by focusing on the “ideal” situations; students need to learn what is “normal” before they can understand how real-world processes deviate from “normal” and why. Real-time ocean data includes numbers, units of measurement, and various visualization techniques ranging from graphs with x and y axes to maps. Data can be scary, particularly for students who consider themselves “not good at math” – “math” being a catch-all for anything involving numbers. An online oceanography lab provides the perfect opportunity for students to build the skills necessary to improve their data literacy and become more comfortable with “math”. Several real-world datasets are used in my oceanography lab course (e.g., the Ocean Observatories Initiative, earth.nullschool.net, Google Earth) to show students how and where processes “match” their textbook diagrams, and how and where they differ. Students are guided through a scaffolded process to increase familiarity with different data visualization techniques including station profiles, vertical sections, bathymetric maps, and animated data maps, and then answer questions and create their own graphs and charts to demonstrate their understanding. At the end of each module, students reflect on what they learned and where they struggled in the lab exercises – often these reflections illustrate a conversion from “math averse” to “math curious” over the course of the semester!
09:45 AM
CHANGING 2YC STUDENTS’ PERCEPTIONS AND DATA LITERACY USING OOI DATA (9485)
Primary Presenter: Denise Bristol, Hillsborough Community College - SouthShore (dbristol@hccfl.edu)
Understanding and working with data is one of the most increasingly critical in-demand career skills in the modern workforce and is no longer limited to STEM careers. The ability to read, understand, interpret, and communicate data effectively has become as essential as reading, writing and math. However, students enter Community Colleges (2YCs) have varying backgrounds and often represent under-prepared student populations in skill sets and confidence in language, math, science questioning, critical thinking, data analysis, and the ability to synthesize or apply concepts. Introductory general education students mostly fall into categories of data avoiders or data novices, and rarely have skills expected by employers. In fact, students may never have been introduced to non-idealized data sets which have outliers, gaps, messy trends or visualizations that are discipline specific. Students new to working with complex data need to be guided through structured methods of examining and making sense of the data. Our study evaluated 2YC online introductory oceanography students’ change in perceptions and understanding of authentic ‘big data’ visualizations. We used large Ocean Observatories data sets from the Ocean Data Lab Manual: Building Data Skills activity that uses a scaffolded learning cycle approach where data literacy skills and scientific concepts are incrementally introduced within the activity. The activity meets students’ needs by placing information into relevant contexts, self-checking knowledge throughout the activity and promotes self-directed discovery in an effort to transform students from data avoiders into more confident data interpreters that can read, interpret, and critically evaluate data from different data visualizations and increase their data literacy.
10:00 AM
INTEGRATING DATA LITERACY INTO UNDERGRADUATE COURSEWORK AT SAINT MARY’S COLLEGE OF CALIFORNIA. (9448)
Primary Presenter: Nekesha Williams, Saint Mary's College of California (nbw1@stmarys-ca.edu)
At Saint Mary’s College of California (SMC), preparing the future workforce in aquatic sciences requires not only a strong foundational knowledge, but also proficiency in data literacy skills essential for collecting, analyzing, interpreting, visualizing and communicating data. Achieving this proficiency requires creativity. It also necessitates a deliberate design of undergraduate coursework that prioritizes these competencies. One of the key challenges is balancing the need to increase students' disciplinary knowledge and enhance their data literacy. A promising solution is the incorporation of real-time, real-life data to address these objectives. In this presentation, I will highlight the integration of data literacy into the learning objectives of upper division course syllabi at SMC. I will discuss the importance of tools such as Microsoft Excel in laying the foundation for students' data analysis and visualizing skills. Additionally, I will showcase specific exercises, such as analyzing wave characteristics using data from OOI Ocean Data Labs Project to cultivate students' data analysis and interpretation skills. Finally, I will address the importance of developing students’ spatial data literacy skills as an important component of workforce readiness and the benefits of using tools such as Google Earth and the potential of ArcGIS Survey 123 to facilitate data collection. The audience will learn about the various tools and data sources employed primarily in the classroom, to equip students for graduate programs and for successful careers in the aquatic sciences
EP02A - Building Data Literacy Skills in the Next Generation of Aquatic Scientists
Description
Time: 9:00 AM
Date: 29/3/2025
Room: W206B