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CITATION McDonnell, J., A. deCharon, C.S. Lichtenwalner, K. Hunter-Thomson, C. Halversen, O. Schofield, S. Glenn, C. Ferraro, C. Lauter, and J. Hewlett. 2018. Education and public engagement in OOI: Lessons learned from the field. Oceanography 31(1):138–146, https://doi.org/10.5670/oceanog.2018.122.

DOI https://doi.org/10.5670/oceanog.2018.122

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DOWNLOADED FROM HTTP://TOS.ORG/OCEANOGRAPHY SPECIAL ISSUE ON THE OCEAN OBSERVATORIES INITIATIVE

Education and Public Engagement in OOI Lessons Learned from the Field

By Janice McDonnell, Annette deCharon, C. Sage Lichtenwalner, Kristin Hunter-Thomson, Catherine Halversen, Oscar Schofield, Scott Glenn, Carrie Ferraro, Carla Lauter, and James Hewlett

138 Oceanography | Vol.31, No.1 To build the most user-friendly way for professors and researchers to access OOI data for undergraduate teaching, EPE created“ a suite of effective tools through an iterative development cycle. .

By Janice McDonnell, Annette deCharon, C. Sage Lichtenwalner, Kristin Hunter-Thomson, Catherine Halversen, Oscar Schofield, Scott Glenn, Carrie Ferraro, Carla Lauter, and James Hewlett ”

ABSTRACT. The Ocean Observing Initiative (OOI) was designed to advance manipulating data, learners are chal- understanding of complex oceanographic processes by acquiring large quantities of lenged to construct meaning and develop data at six key locations in the world ocean. The OOI Education and Public Engagement a deeper understanding of a topic or (EPE) Implementing Organization has built an educational cyberinfrastructure and phenomenon. This type of learning also developed interactive tools targeted for undergraduate-level learners that enable easy encourages student inquiry and helps access to OOI data, images, and video. To develop the suite of OOI education tools, develop practical science skills (Hays EPE used an iterative design process, including needs assessment, tool prototyping, and et al., 2000; Adams and Matsumoto, usability testing in undergraduate classrooms. Data visualization and concept mapping 2009). Working with real data helps stu- tools were envisioned as a way to help undergraduates link concepts students see in dents develop interest in, motivation oceanography textbooks to real-world phenomena. A Data Investigation Builder (DIB) for, and identity with respect to sci- was constructed to assist professors in designing data activities. During the usability ence (National Science Board, 2007). testing, professors provided valuable feedback that allowed EPE to improve the tools. Moreover, analyzing data and identifying Based on the lessons learned from EPE, in 2016 we developed a new prototype set of patterns have become core skills in the Data Explorations that were more modular and easier to integrate into an undergraduate workplace and for civic engagement in lecture or problem set. This paper reviews how the EPE toolset was developed, including the twenty-first century (Oceans of Data establishment of requirements for the tools and incorporation of lessons learned from Institute, 2015). the user needs assessment and the results of usability testing of prototype tools. Despite the benefits and opportuni- ties of having students work with real INTRODUCTION and plate-scale geodynamics for the com- data, undergraduate teaching is often not A growing number of geoscience research ing decades. The OOI is already advanc- data intensive (Krumhansel et al., 2013). programs collect high volumes of data ing our ability to understand the natu- Limited experience and exposure to dif- using advanced technologies, espe- ral world by acquiring large quantities of ferent data types and sources can cause cially in oceanography. One such pro- data to address complex oceanographic students to struggle in their courses, and gram is the National Science Foundation processes at six locations of interest they may purposefully avoid the use and (NSF) Ocean Observatories Initiative in the world ocean. evaluation of data in their everyday lives. (OOI), which has constructed obser- Expanded access to online data pro- Cognitive studies reveal that students vational and computational infrastruc- vides geoscience professors with myriad who are not regularly exposed to data ture to provide sustained ocean measure- opportunities to engage undergrad- manipulation often fail to see patterns ments for the study of climate variability, uate learners through the use of real- emerging across scientific experiments, ocean circulation, ecosystem dynam- world data sets, models, and simulations frequently ignoring anomalous data or ics, air-sea exchange, seafloor processes, of oceanographic processes. By directly distorting them to match their personal beliefs (Chinn and Brewer, 1998). Studies FACING PAGE. From left to right: Cheryl Greengrove (University of Washington Tacoma), Deborah also indicate that students need to learn Kelley (University of Washington Seattle), Alan Trujillo (Palomar College), and Rus Higley (Highline College) explore teaching with data at the Rutgers University Inn and Conference Center, more about the types of conclusions that New Brunswick, NJ. scientists can draw from observations,

Oceanography | March 2018 139 what kinds of evidence are needed to However, the transition from using data Education and Public Engagement (EPE) support scientific ideas, and how that evi- they collected to using professionally col- Implementing Organization worked to dence can be gathered and interpreted lected data can be very challenging for build an educational cyberinfrastructure (Sampson and Clark, 2008). students. They need to shift from using and develop interactive tools to enable To support data literacy and enhance familiar to unfamiliar analysis tools, from easy access to OOI data, images, and critical thinking skills, undergraduates hands-on experiences to gaining context video in formal learning environments. need to transition from working with from metadata, and from simple to com- Toward this end, we explored methodol- small, typically self-collected data sets plex lines of reasoning (Kastens, 2011). ogies for effectively integrating data into to large, professionally collected data Supporting students while they transition learning strategies and creating data visu- sets (Kastens, 2011) such as those pro- to using professionally collected data can alization tools to teach twenty-first cen- vided by the OOI. Student-collected data be challenging for professors too, as there tury science skills and practices in under- can spur discussion of “data ownership” is often a lack of adequate tools to help graduate classrooms. To build the most (i.e., provenance) and how data provide students in the classroom easily digest user-friendly way for professors and evidence for claims, interpretations, and and manipulate large data sets. researchers to access OOI data for under- conclusions (Hug and McNeill, 2008). With these challenges in mind, the OOI graduate teaching, EPE created a suite of effective tools through an iterative devel- opment cycle. This paper reviews how A Brief History of Education the EPE toolset was developed, including how the requirements for the tools were and Public Engagement in OOI established, and how we folded in lessons learned from the user needs assessment and results from the usability testing of the prototype tools. Our experiences will help future developers interested in learn- ing about effective processes for building their own educational tools and content.

HISTORY OF EDUCATION AND PUBLIC ENGAGEMENT IN OOI Education and public awareness was a crucial component of the early Ocean Research Interactive Observation Net- works (ORION) program (Matsumoto et al., 2006) that eventually evolved into the OOI program. From 2002 to 2010, there was a national focus on ocean science education, espe- cially through the NSF-funded Centers for Ocean Science Education Excellence (COSEE), NOAA’s Integrated Ocean Observing System (IOOS; Simoniello et al., 2010; Pfirman et al., 2011), and the EPE Implementing Organization for OOI (Figure 1). Early OOI strategic planning called for a central coordination office, as well as collaboration with a national network of observatory educators who would wel- come sustained partnerships with sci- entists and engineers (Matsumoto et al., 2006). Educators and scientists articu- FIGURE 1. The progression of thinking about using data in teaching and learning. lated the need for a data management

140 Oceanography | Vol.31, No.1 and information translation facility assessment results showed professors conceptual understanding. that would be tasked with transform- were interested in using data sets to con- These professors also recommended ing OOI research results, technology nect important themes and concepts in that EPE develop tools for creating basic innovations, and data into ready-to- introductory oceanography courses. They statistics (e.g., calculation of mean, stan- use forms for a variety of education and wanted simple, clearly defined variables dard deviation, standard error, cor- outreach audiences. that are easily grasped by students. They relation coefficient, regression line), In 2011, NSF funded the EPE preferred temporally based and easily interpolating data, and helping stu- Implementing Organization (IO) for the manipulated data and visualization tools dents visualize time-series data sets OOI. The overarching objective was to that allowed for easy downloading of out- (McDonnell et al., 2015). The profes- develop tools and approaches that lever- puts. Finally, they requested metadata to sors also supported the development of age the unique science and engineer- bring the context of data into student-​ a specialized tool that would allow them ing capacities of OOI. EPE IO’s charge centered activities while supporting to create lessons using OOI data, rate was to facilitate and support educa- tion and outreach; however, the team was not supported to create educational projects or products per se. Based on Tools Development Process NSF guidance, the primary focus of the OOI project was on developing infra- structural tools to support undergrad- 2011 – uate education. The EPE team was led 2012 by Rutgers University and included the University of Maine, Raytheon Web Solutions, and education liaisons from the other previously awarded IOs: The University of Washington, Scripps Institution of Oceanography, and Oregon State University.

THE PROCESS: BUILDING EPE TOOLS FOR UNDERGRADUATE 2012 – STUDENT LEARNING 2014 EPE used an iterative design process to support the use of OOI data in under- graduate teaching (Figure 2). The EPE team conducted user needs assessments and usability tests, and developed a num- ber of prototype tools with professors who teach undergraduates. Needs assessments consisted of phone interviews in 2011 and 2012 with pro- 2015 fessors who were teaching undergradu- – ates as well as a national survey in 2012 2017 (n = 133; response rate 14%). We focused on understanding undergraduate teach- ing practices employed at the time and collecting example summaries of how data were used in undergraduate class- rooms. These data were synthesized into recommendations to aid OOI software developers in designing tools that would FIGURE 2. The OOI Education and Public Engagement (EPE) used a development process enable undergraduates to interpret and that included needs assessment of the professors, prototyping of data activities, and testing analyze oceanographic data. Overall, with undergraduates.

Oceanography | March 2018 141 or review colleagues’ lessons, and copy EPE tools were designed to help stu- in the pilot. Professors reported that and edit lessons created by others. They dents understand and visualize how these types of lessons broadened stu- suggested that EPE continue to develop ocean data and research findings are tied dents’ views from local to more regional/ and refine the Concept Mapper, devel- to key oceanography concepts. For exam- global perspectives. This observation was oped earlier by COSEE Ocean Systems ple, the Data Investigation Builder (DIB) common among the CCURI community (deCharon et al., 2013). The Concept is designed for learners to collect and college faculty whose students had col- Mapper was highly regarded by the pro- interpret their own data and/or explore lected data locally before learning about fessors, who recognized its high poten- research data sets to answer questions, as the OOI program. tial for teaching oceanographic con- described by Manduca and Mogk (2002). Finally, undergraduate survey results cepts. They also expressed the need for The DIB tool assists professors in draft- demonstrate that they need more guid- help in deciphering the extensive and ing student learning objectives, identi- ance and support to learn how to inter- jargon-heavy vocabulary of the OOI pro- fying and visualizing OOI data sets and, pret graphs. Students found the graphs gram. This request spurred development most importantly, creating research chal- difficult to read and interpret (e.g., the of the Vocabulary Navigator, which uses lenges for undergraduates to pursue. axes were sometimes unclear; more cap- backend ontologies (deCharon et al., Thus, the Education Portal was designed tions, key terms, visualizations, videos, 2015) to display and describe connec- to help students explore scientific prac- and maps were needed to understand tions among various components of the tices (e.g., developing a conceptual model data sources; photos of instruments were OOI using a concept-map format. or diagram), analyze OOI data sets, con- requested; McDonnell et al., 2015). Some During 2012–2014, EPE developed struct written explanations of phenom- key outcomes include: requirements for its prototype tools and ena observed in the data, and develop • Data visualization tools are most conducted usability testing on early pro- new questions based on OOI data. critical to successfully integrating totypes. “Think Aloud” testing was used OOI into undergraduate classrooms. to solicit feedback from undergraduate IMPLEMENTING EPE TOOLS: Professors and their students agreed professors at universities and community HOW CAN THE TOOLS BE that there is great value to the types of colleges. Think Aloud is a method of user USED IN UNDERGRADUATE tools developed by EPE; however, they testing that involves asking users to think TEACHING? need additional effort to increase their out loud as they perform a task. The pro- The collection of tools developed by reliability and usability. There is broad tocol included collecting information on EPE effectively integrates OOI data into agreement that bringing traditional the backgrounds of the users/testers, and undergraduate teaching, as demonstrated textbook discussions of oceanographic asking them to review time-series visual- by results of our pilot tests (Hunter- concepts alive with OOI data would izations, “glider” tools, and the prelimi- Thomson et al., 2017). However, there is be of great value to students. Thus, nary Vocabulary Navigator. EPE also con- still much work to be done to facilitate more research and evaluation should ducted a demonstration of pilot EPE tools the use of OOI data in education. Pilot be conducted to ascertain whether or in collaboration with the NSF-funded testers stated that EPE data visualization how data interactions impact student Community College Undergraduate tools provided their students with exam- learning and their likelihood of pursu- Research Initiative (CCURI) network. ples of how oceanographic data are col- ing scientific careers. lected, graphed, and analyzed. The tools • Lack of model content or OOI- EPE OCEAN EDUCATION also allow students to see how data can be specific data visualization tools was PORTAL graphed and visualized for better analysis. a significant barrier to the success of The primary goal of the EPE effort was to During the EPE development phase, the EPE. The OOI construction funds develop an online Ocean Education Portal a collection of five lessons were created for EPE were limited to tool develop- (http://education.oceanobservatories. in the Education Portal, entitled Ocean- ment and could not be applied to class- org) to support the creation and shar- Atmosphere Interactions During Storms, room lesson development. However, ing of educational resources by under- Salinity Matters, Seasonality in the Ocean, supplemental NSF funding has sup- graduate faculty. The EPE portal includes Is Overfishing Creating a Population ported the successful development of a suite of tools (Table 1) that enable fac- Bottleneck?, and Ocean Acidification. the classroom exemplars used in our ulty to create custom activities online for These prototype lessons employed other CCURI pilot demonstration. Although group or individual projects that can be data sets from NOAA as placeholders the simultaneous development of the used either during lectures or as home- for OOI data, which were not yet avail- OOI Cyberinfrastructure/Data Portal work assignments. The site also includes a able. EPE conducted formative eval- and the EPE tools initially complicated variety of resources to facilitate using OOI uation, surveying both the professors the use of OOI data streams to test the data to teach oceanography concepts. (n = 8) and undergraduates participating tools and demonstrate their utility,

142 Oceanography | Vol.31, No.1 TABLE 1. A description of EPE tools. Educational Data Visualization Tools

Description. Provide simple interfaces to Key Features. One example is the interact with OOI datasets. A collection “Simple Time Series” tool, which is used of five interactive visualization tools was to select instruments and date ranges. designed to be intuitive and adaptable to This allows students to explore changes professors’ teaching goals. in environmental conditions over time (e.g., hurricanes, seasons).

Concept Mapper

Description. Allows users to build Key Features. Concept maps are widely connected diagrams of their knowledge, used in education to aid or evaluate using shapes to represent concepts students’ contextual understanding of and arrows to describe the relationships topics. between them.

Data Investigation Builder (DIB)

Description. Resources—including OOI Key Features. Well-defined steps data visualizations, images, videos, and help educators develop lessons using concept maps—can be assembled into OOI data. The tool promotes effective learning modules. These lessons can education practices by supporting also be shared with colleagues. students’ use of data-based evidence to answer prompting questions.

Vocabulary Navigator

Description. Provides an intuitive Key Features. Based on organizational and visual way to explore OOI’s structures used in information and infrastructure. Its five interlinked computer sciences, these vocabularies vocabularies include terms and images were designed to meet users’ needs by from high-level science themes to placing information into relevant context, specific data products. while promoting self-directed discovery.

Oceanography | March 2018 143 it was possible to conduct some lim- online autonomously or facilitated by a based on the knowledge levels of their stu- ited testing with National Data Buoy professor as part of classroom lectures. dents and their course setups (e.g., face- Center data. Experience, user feed- Lessons should be progressive and scaf- to-face, hybrid). back, and supplemental support have folded to help students get the experi- Each event focused on developing all contributed to the capability for ence they need with data while also effective teaching practices for using OOI integrating OOI data into the visual- helping to build their confidence and data assets and customized data visual- ization tools. skills. Scaffolding refers to a variety of ization tools. To build a community of • Continue to develop EPE tools to instructional techniques used to move practice among participating professors, support inquiry-based learning. students progressively toward stronger we focused on developing content exem- CCURI professors felt the DIB could understanding and, ultimately, greater plars that use OOI data. Another work- be an asset for engaging in active independence in the learning process. shop objective was to provide pedagogi- learning and teaching. They recom- cal guidance to professors who often do mended that EPE provide support for BEYOND EPE: DATA not have much opportunity to learn about professors to create more data activ- EXPLORATIONS PROJECT effective teaching practices. ities and resources, including peda- Based on lessons learned from EPE, we Data Explorations employed the gogical support for both online and developed a new prototype set of Data Learning Cycle model developed by the face-to-face implementations. They Explorations in 2016 (http://explorations.​ Lawrence Hall of Science at the University suggested that EPE focus development visualocean.net). These activities are more of California, Berkeley, where instruction on the data visualization and con- modular and thus easier to integrate into is organized to be consistent with what cept mapping tools, as they felt those an undergraduate lecture or problem set. is known about how people learn (see tools had the most potential. Finally, Through hands-on workshops, professors Box 1). The student-centered explorations they recommended EPE provide from diverse institutions—including com- developed in this workshop were designed training and marketing of its tools to munity colleges, primarily undergraduate to connect new content to students’ prior the community. institutions, and minority-serving​ insti- knowledge, elicit questions and explana- • Additional professional develop- tutions—became engaged in the Data tions, provide opportunities for explora- ment support for professors using Explorations project. Overall, 28 profes- tion and discussion of ideas with peers, the tools is needed. EPE tools should sors participated in three OOI workshops and apply students’ understanding to new be iterated and refined based on the focused on biological productivity (May situations (Lawson, 2002; Bybee et al., types of instruction being used by 2016), properties of seawater (May 2017), 2006; Brown and Abell, 2007). undergraduate professors. For exam- and tectonics and seamounts (June 2017). To help facilitate integration of OOI ple, instructions to students will differ Participants developed implementa- data into undergraduate teaching, we based on whether they are being used tion plans for subsequent academic years identified connections between themes in

Box 1. The Learning Cycle Explained

INVITATION - Initiates the learning task and sets the con- APPLICATION - Armed with new ideas, learners apply text. It sparks interest, and spurs learners to recall and new knowledge and skills to solving a problem or meeting retrieve past connections that may be relevant to present a challenge, transferring their new knowledge to unfamil- learning experiences. iar contexts in the world.

EXPLORATION - Involves exploration of real phenom- REFLECTION - After trying out new ideas in different set- ena driven mainly by learners’ interest and questions, fol- tings, learners reflect on how their original notions have lowed by discussion about discoveries, results, ideas, and been or need to be modified. It invites them to monitor questions. Provides a common base of experiences for and regulate their own evolving understanding, and gen- learners to develop new concepts and skills. erate new questions.

CONCEPT INVENTION - After interest and attention is focused, learners actively process the experience, review evidence and data gathered through exploration, and try to make sense of it.

144 Oceanography | Vol.31, No.1 oceanography textbooks commonly used ANATOMY OF A DATA The Explorations each include a descrip- in lower division classes (e.g., “101 level”) EXPLORATION tion of the student objective and data tips and the OOI science themes. To enable Data Explorations are designed as for the student to begin interacting with easy adoption in community college in-class, group explorations and take data. The activity also includes questions and university 101-level oceanogra- 15–20 minutes to complete. One such to prompt interpretation and analysis, phy courses, we purposely linked our example data activity is highlighted facilitating each student’s ability to digest data explorations to one of the most in Figure 3. The learning objective for and make sense of the data. Annotated used textbooks in the United States, The each Exploration is closely tied to the background images and resources pro- Essentials of Oceanography (Trujillo and Learning Cycle, with different data activ- vide context. In addition, professors are Thurman, 2016). A complete cross ref- ities designed to be used at specific encouraged to use the EPE concept-​ erence between this textbook’s themes Learning Cycle phases. Thus, the learn- mapping tool to assess prior knowledge and OOI data can be found on the Data ing objective and the questions students and reflect on knowledge gained. Explorations website. will address vary across each Exploration.

Example Data Interactive from The OOI Data Explorations Project

Exploration The exploration phase focuses on exploring data to see what you can observe.

Application The application phase focuses on comparing patterns to determine relationships in the data in time and space. Concept Maps Concept maps can be used to support the learning cycle—especially invitation and reflection phases.

FIGURE 3. An example of one of the data activities, Seasonal Variation of Surface Salinity, from the 30 developed as part of the Data Explorations proj- ect. The data activities were largely devoted to the “Exploration” and “Application” phases of the Learning Cycle and associated question prompts. In “Exploration,” the learner focuses on observations that can be made from the data. In “Application,” the learner focuses on comparing spatial and tem- poral patterns and relationships in the data. The Concept Mapper tool was frequently used to support learning, especially during the “Invitation” and “Reflection” phases.

Oceanography | March 2018 145 Professors can use Data Explorations Chinn, C.A., and W. Brewer. 1998. An empirical Pfirman, S., F. Lawrenz, G. Chin-Leo, K. St. John, test of a taxonomy of responses to anomalous R. Kinzler, S. Pompea, and B. Herbert. 2011. COSEE activities to augment concepts already data in science. Journal of Research in Science Decadal Review Committee Report. http://www. included in their courses. For example, if Teaching 35(6):623–654, https://doi.org/10.1002/ cosee.net/files/coseenet/COSEE Decadal Review (SICI)1098-2736(199808)35:6<623::AID-TEA3>​ Report final 092411 3.pdf. they teach about seasonal variation of sea 3.0.CO;2-O. Sampson, V., and D. Clark. 2008. Assessment of surface salinity, they can use data activ- deCharon, A., L. Duguay, J. McDonnell, C. Peach, the ways students generate arguments in sci- C. Companion, C. Herren, P. Harcourt, T. Repa, ence education: Current perspectives and rec- ities tied to relevant OOI data sets and C. Ferraro, P. Kwon, and others. 2013. Concept ommendations for future directions. Science interactive visualizations. Given that each mapping workshops: Helping ocean scien- Education 92(3):447–472, https://doi.org/10.1002/ tists represent and communicate science. sce.20276. Data Explorations activity includes mul- Oceanography 26(1):98–105, https://doi.org/​ Simoniello, C., L. Spence, N. Deans, and J. McDonnell. tiple options, professors can tailor them 10.5670/oceanog.2013.08. 2010. Developing an education and outreach deCharon, A., L. Smith, and C. Companion 2015. program for the US. IOOS: Eyes on the ocean, to support the learning objectives and the Characterizing complex marine systems and tech- hands-on learning. Marine Technology Society abilities of their students. nology using visualized vocabularies. Marine Journal 44(6):176–184. Technology Society Journal 49(4):53–63, Trujillo, A,, and H. Thurman. 2016. Essentials of https://doi.org/10.4031/MTSJ.49.4.2. Oceanography, 12th ed. Pearson Press, 624 pp. LOOKING FORWARD Hays, J.D., S. Pfirman, B. Blumenthal, AND NEXT STEPS K. Kastens, and W. Menke. 2000. Earth sci- ACKNOWLEDGMENTS ence instruction with digital data. Computers We would like to acknowledge the support of We hope the community of profes- & Geosciences 26(6):657–668, https://doi.org/​ the OOI data team, Michael Vardaro, Lori Garzio, 10.1016/​S0098-3004(99)00101-6. sors using OOI data in their classrooms Friedrich Knuth, Michael Smith, and Leila Belabassi; Hug, B., and K.L. McNeill. 2008. Use of first-hand the Raytheon Web Solutions team, Sean Graham, will continue to expand over the com- and second-hand data in science: Does data type Allan Yu, and Joe Wieclawek; and the Consortium for influence classroom conversations? International ing years. As we further develop content, Ocean Leadership office, especially Andrea McCurdy. Journal of Science Education 30(13):1,725–1,751, We thank Debi Kilb, Ailison Fundis, and Craig Risien, in-person and online courses, and tuto- https://doi.org/10.1080/09500690701506945. who served as EPE liaisons during the project. We Hunter-Thomson, K., S. Lichtenwalner, and rials, we hope that leaders will emerge greatly appreciate advice and support from Cheryl J. McDonnell. 2017. Incorporating observatory data Peach and Liesl Hotaling. We especially thank Lisa who are excited about engaging students into oceanography courses. Eos 98, https://doi.org/​ Rom for her support and guidance over the years. 10.1029/2017EO087369. in OOI data and science. We invite new Kastens, K. 2011. Learning to learn from data. Earth AUTHORS and Mind: The blog, http://serc.carleton.edu/​ partners to participate and will continue Janice McDonnell ([email protected]) earthandmind/​posts/​datalearningpro.html. is an Educator in the Department of Marine and to add content to the Data Explorations Krumhansl, R., A. Busey, K. Krumhansl, J. Foster, Coastal Sciences, Rutgers University, New Brunswick, and C. Peach. 2013. Visualizing Oceans of Data: website as funding allows. Finally, we NJ, USA. Annette deCharon is Senior Marine Educational Interface Design. 8 pp., http://www. Outreach Education Scientist, University of will work with educational research- oceansofdata.org/sites/oceansofdata.org/files/ Maine, Darling Marine Science Center, Walpole, MTS-2013.pdf. ers and practitioners to refine our Data ME, USA. C. Sage Lichtenwalner is Research Lawson, A.E. 2002. The learning cycle. Pp. 51–76 Programmer, Department of Marine and Coastal Explorations model, building a criti- in A Love of Discovery: Science Education—The Sciences, Rutgers University, New Brunswick, Second Career of Robert Karplus. R.G. Fuller, ed., cal mass of exemplars and sharing effec- NJ, USA. Kristin Hunter-Thomson is Program Springer. Director of Dataspire and Teaching Instructor, tive practices in the educational litera- Manduca, C.A., and D.W. Mogk. 2002. Using Data in Department of Human Ecology, Rutgers University, Undergraduate Science Classrooms: Final Report ture. Our EPE experience shows that the New Brunswick, NJ, USA. Catherine Halversen is on An Interdisciplinary Workshop Held at Carleton Senior Program Director, Lawrence Hall of Science, oceanographic community needs to con- College, April 2002. Carleton College, Science University of California, Berkeley, Berkeley, CA, Education Resource Center. tinue improving its data tools to support USA. Oscar Schofield is Professor, Scott Glenn Matsumoto, G., J. Bursek, R. Czujko, A. deCharon, is Professor, and Carrie Ferraro is Education and educational needs, thereby reducing bar- S. Franks, S. Gilman, A. Holt-Cline, D. Keith, Outreach Program Coordinator, all in the Department D. Malmquist, J. McDonnell, and others. riers to accessing and understanding sci- of Marine and Coastal Sciences, Rutgers University, 2006. Ocean Research and Interactive New Brunswick, NJ, USA. Carla Lauter is Research ence content. The community needs to Observatory Networks (ORION) Education Associate, University of Maine, Darling Marine and Public Awareness Draft Strategic Plan. be able to build/update tools and content Science Center, Walpole, ME, USA. James Hewlett http://oceanleadership.org/wp-content/uploads/ ​ ​ ​ is Professor, Finger Lakes Community College, (lessons) as OOI evolves. We recommend 2009/07/OOI_ORIONEducationPlan_4_0.pdf. Canandaigua, NY, USA. a continued focus on developing new McDonnell, J., S. Lichtenwalner, S. Glenn, C. Ferraro, K. Hunter-Thomson, and J. Hewlett. 2015. The chal- data activities and providing professional lenges and opportunities of using data in teach- ARTICLE CITATION development to continue to expand a ing from the perspective of undergraduate ocean- McDonnell, J., A. deCharon, C.S. Lichtenwalner, ography professors. Marine Technology Science K. Hunter-Thomson, C. Halversen, O. Schofield, user base for OOI education. Journal 49(4):76–85, https://doi.org/10.4031/ S. Glenn, C. Ferraro, C. Lauter, and J. Hewlett. 2018. MTSJ.49.4.9. Education and public engagement in OOI: Lessons REFERENCES National Science Board. 2007. A National Action learned from the field. Oceanography 31(1):138–146, Adams, L.G., and G. Matsumoto. 2009. Commentary: Plan for Addressing the Critical Needs of the https://doi.org/10.5670/oceanog.2018.122. Enhancing ocean literacy using real-time data. 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