Your can view the profiles of all keynote presenters here.
Carolyn Finney, Independent Scholar; Tuesday April 2, 2019 9:00 AM
Whitney Tome, Green 2.0; Tuesday April 2, 2019 10:30 AM
Unfortunately, this presentation has been cancelled.
Melinda Laituri, Tuesday April 2, 2019 7:00 PM
Spatial justice refers to the consequential geography of a place where spaces are socially produced. Our increasing dependence on digital data to represent space demands that we adopt practices that reflect how best to capture place. Places reflect where people live; the amenities and emotions associated with living there. However, mapping space through digital technologies often does not reflect the social connections to places. Who lives where and why? Who has access to resources and services and who does not? How are healthy environments measured? Understanding how spatial injustice is created at different spatial scales is an essential part of participatory practices to collect community data. Giving voice and visualization to marginal populations are part of mapping efforts to assess the spatial arrangement of space where communities are integrated and included in such projects. This is a fraught enterprise due to the digital divide, technological challenges and the need to ensure ethical practices in data collection and data integrity.
Marco Hatch; Wednesday April 2, 2019 8:40 AM
One common barrier to STEM engagement in underserved and underrepresented communities is a feeling of disconnection from mainstream science. This attitude is rooted in a history of researchers and decision-makers collecting, analyzing and interpreting data without engaging community members as true partners and equals. Spanning this boundary between ecological research and communities impacted by environmental change is foundational to moving toward a more equitable future focused on solutions that serve under-resourced communities facing the brunt of environmental degradation and climate change. Great strides have been made toward the goals of democratizing conservation science, empowering local communities to engage with mainstream research on a level playing field. However, these initiatives are subject to a few common pitfalls such as, projects that do not fully account for the social-cultural context of the community, projects that fail to understand the foundationally different worldview of Indigenous communities. These pitfalls can lead to partnerships with the unstated goal of “making them like us”, where the actions of the partnership are structured such that the decision-making power and authority is retained within the STEM disciplines, and if community members want access to that authority, they must conform their worldview to mainstream science. We believe that spanning this boundary between local communities and mainstream science will increase social justice, increase the relevance of conservation science, and open new opportunity spaces for all involved. Central to the success of this vision are boundary spanners.
Melvin Hall; Wednesday April 2, 2019 9:35 AM
Drew Hasley; Wednesday April 3, 2019 10:30 AM
If you were designing a course or employee training that introduces participants to writing and executing code, statistical analyses, and data visualization, what would you do to make it inclusive of participants with disabilities? What sorts of accessibility issues might you anticipate? How might you address them before you even know who the participants are? Why shouldn’t you just wait until you have a participant with a disability and work with them directly to make accommodations? Confidently answering such questions can be daunting. It requires knowing what disability is, awareness of some barriers to participation in data science by people with disabilities, some knowledge of tools and strategies for lowering those barriers, and above all, creativity. In this talk, I will address each of these, drawing on personal experience as a student and professional with a severe visual impairment, and knowledge gained from colleagues and friends during ongoing efforts in the area of accessible teaching in quantitative biology. Audience members will leave this talk with a better understanding of barriers to recruitment and training of people with disabilities in data science and some tools and strategies to lower them. They will also learn about areas requiring more attention. My primary goal is to leave audience members with the confidence that they can indeed help address the substantial underrepresentation of people with disabilities in this vital, growing field.
Carlos Castillo-Chavez; Wednesday April 4, 2019 8:40 AM
The spread of fads, scientific ideas and the growth and stability of communities can also be understood as contagions. In this talk, I would focus on contagion in all its glory, including its role on building communities of mentors and understanding the role that initial conditions should play in our definition of meritocracy.
Jason Williams, Cold Spring Harbor Laboratory; Tuesday April 2, 2019 1:45 PM
This talk highlights challenges and opportunities surrounding bioinformatics training and aims to spark conversation reshaping the training landscape. As new methods such as machine learning/deep learning become more relevant to biology, we risk widening the intelligibility gap between the training “haves” and “have-nots.” The community has a need for extensive discussion on this topic and support for development of alternatives to classroom training that can bridge gaps between the large numbers of existing researchers who need to understand and apply data science skills, but who are unlikely to return to formal schooling. Findings by NIBLSE (pronounced “nibbles”) – Network for Integrating Bioinformatics in Life Sciences Education – revealed that 95% of faculty believe bioinformatics should be taught, but only 40% manage to do so (with clear disparities for faculty at less-resourced institutions). Input from the survey and a NIBLSE working group has also generated a set of bioinformatics competencies for undergraduate bioinformatics (Sayers et.al. 2018). A a survey of NSF-funded investigators in the biological sciences (Barone et.al. 2017) conclude that training in several areas of bioinformatics are the most unmet need for established researchers. Improving the bioinformatics curriculum opens up opportunities for broadened participation by equipping students and teachers with the skills needed for 21st century careers in STEM. Examples of CyVerse and Cold Spring Harbor DNA Learning Center programs that integrate bioinformatics, big data, and data science will illustrate effective ways to engage diverse students with in-demand skills.
Yael Wyner, City College of New York, City University of New York and Janice Koch, American University; Tuesday April 2, 2019 1:50 PM
This speed talk will describe three education projects that engage urban minority students in science and the environment. Two projects focus on secondary school ecology and evolutionary biology learning in New York City science classrooms. The third project is a new science learning and public engagement major for City College of New York undergraduate students. Each of these projects seeks to increase access to science learning and science careers. With NSF funding, we created curricular resources grounded in published scientific data to connect the daily lives of New York City high school students to ecological concepts learned in school. We also created curricular resources for New York City middle school students to help them notice the evolutionary patterns of the sidewalk trees they pass daily. We are currently designing a new undergraduate program to prepare City College graduates to deliver STEM learning at botanical gardens, museums, zoos, environmental education centers, community-based organizations, educational, and science and environmental non-profits. The new City College program is a response to the unmet need to expand the science engagement pipeline to members of underrepresented groups.
Travis Belote, The Wilderness Society, Edem Yevoo, University of Maryland, and Teresa Mourad, Ecological Society of America; Tuesday April 2, 2019 1:55 PM
The EcologyPlus program recruits and supports a cohort of diverse students to pursue a variety of professional development opportunities through a diverse network of organizations. The Wilderness Society, as a partner organization, hosted three EcologyPlus student interns in the fall of 2018. The internship began with a week-long trip to Montana to visit Yellowstone National Park, meet local scientists, receive a short-course on geographic information systems (GIS) and spatial data, and develop research questions. Each student developed separate but related questions requiring various spatial datasets, data management, and analytical approaches. The students completed most of the work at their home institutions throughout the fall semester of 2018. The remote internship included biweekly check-ins including “shadowing” via screenshares to work through data analysis challenges. Students presented their work during a one-hour presentation and webinar at the end of the semester. We will discuss the value of spatial data and GIS in undergraduate education and provide recommendation for a successful remote internship. Our key recommendations include spending time together in-person for a kick-off event, regular check-in meetings with video conferencing and screenshares, and developing clear deliverables (report or professional presentation) to bookend the experience.
Edem Yevoo, University of Maryland and Travis Belote, The Wilderness Society; Tuesday April 2, 2019 2:00 PM
As the global population continues to increase, more people are moving from rural to urban areas. In the next decades, most of the world's population will be living in urban areas. Utilizing geospatial data from the United States Geological Survey (USGS), a predictive visual model was created using geographic information systems (GIS) software. The model was used to predict the change in the District of Columbia's (DC) urban landscape over time. The use of GIS and data analysis systems hold the key to tackling current and future environmental issues. I will discuss the use of spatial data and how it can be used to impact policy, climate change, and socioeconomic conditions in our urban environments.
Jennifer Balch, Earth Lab/University of Colorado-Boulder and Kirsten Rowell, University of Colorado-Boulder; Tuesday April 2, 2019 2:05 PM
What are we actually harnessing the data revolution for? It's for humanity. Ultimately, big data should help improve people's lives and help society live more sustainably with our planet. It's not anyone's data, it's everyone's data. This makes it critical to involve, encourage, and support a diversity of people in owning the data and ultimately owning the solutions that come from that data.
Tracy Teal, Kari L. Jordan and SherAaron Hurt, The Carpentries; Wednesday April 3, 2019 9:15 AM
Training for data skills is more critical now than ever before. In the past decade, we've seen the creation of certification and graduate programs for data science, as well as a plethora of interactive, self-paced online learning platforms. Today's learners are often learning on the job and need the flexibility of short, or self-paced learning experiences. Research results, however, stress the importance of guided instruction and learner-instructor interaction.
We've taken a distinctive approach to this problem, combining the power of guided instruction with the flexibility of short, focused learning experiences. Two-day, interactive, hands-on coding workshops train researchers to work with data, and have impacted over 27,500 researchers, ranging from biologists to physicists to engineers and economists. Researchers have benefited from evidence-based teaching approaches to learning data organization (spreadsheets), cleaning (OpenRefine), management (SQL), analysis and visualization (R and Python).
This talk focuses on implications and growth opportunities for incorporating data science curriculum at the university level, from the perspective of The Carpentries. We explore tips and best-practices in data science curriculum development including assessment strategies, accessibility, and equity and inclusion.
Sarah R. Supp, Denison University; Wednesday April 3, 2019 9:20 AM
This talk will use two examples to discuss inclusive pedagogical strategies for training in data science skills. Building a new interdisciplinary program for undergraduates in data analytics, we have a project-based pedagogy, and as a unit have considered ways in which we can spark interest and build academic successes for students more broadly, including students that are traditionally underrepresented in the Computer Sciences, or other related technical fields. This talk will also discuss an ongoing project to address gaps in training for undergraduate instructors, to enhance data education in biology curriculum, thus also broadening access to technical skills for students in these courses.
Melissa Watkinson, Salish Sea DEI Community of Practice; Wednesday April 3, 2019 9:25 AM
Addressing inequity and working toward environmental justice is essential to a successful environmental movement. Currently, there are significant disparities in the representation, content, and processes for implementing diversity, equity, and inclusion (DEI) within the environmental field across the Salish Sea and the Pacific Northwest Coast. Although professionals in this field are aware and concerned about issues related to DEI, there is an overall lack of understanding for how to integrate these concepts into the environmental workforce. Addressing inequity and working toward environmental justice is essential to a successful environmental movement. We believe that by creating and fostering a Salish Sea DEI Community of Practice (CoP), we can begin to build this critical foundation together.
Sarah Stone, University of Washington and Anissa Tanweer, University of Washington; Wednesday April 3, 2019 1:45 PM
Launched in Summer 2015, the UW Data Science for Social Good (DSSG) program partners eScience Data Scientists and Student Fellows from across the country with Project Leads from academia, government, and the private sector to find data-driven solutions to pressing societal challenges. Previous projects (15 over the past 4 summers) have involved data analysis and visualization on topics such as transportation, public health, sustainable urban planning, homelessness, and disaster response. Several projects have led to long-term collaborations and funding opportunities. Integrated project-based discussions and training around data science ethics, human-centered design and stakeholder collaboration are keystones of our DSSG program. Differences in prior experience and training among student fellows can pose a challenge, but often become a strength in the context of project work. Our experience running this program supports the notion that DSSG programs can both effectively impact social good and provide "real world" data science training for students from diverse disciplinary backgrounds.
Adrienne Smith, Cynosure Consulting and Rebecca Zulli Lowe, Cynosure Consulting; Wednesday April 3, 2019 1:50 PM
Asset maps serve as a simple, yet impactful tool for helping underrepresented groups connect with important people, programs, and resources that would support their recruitment and retention in STEM. In contrast to a traditional deficit-focused mindset, asset mapping was born out of an approach that seeks out existing strengths and works to build capacity by leveraging current resources as a foundation for further innovation. At the end of this talk, individuals will walk away with a list of steps that they can use to develop a comprehensive map that could be distributed immediately to current and future STEM (including high school seniors). These steps include identifying current assets within an array of existing categories (e.g., tutoring centers, individual faculty mentors, local chapters of STEM associations) designed to help mappers think expansively about existing supports. Additional steps involve reviewing contact lists and asking others to assist in the identification of assets, performing internet searches of the school/organization website looking for key words, and reading through the university directory to highlight offices that work on diversity issues or support the individuals targeted. The assets can be plotted directly onto a campus map and supplied to underrepresented groups, so they are aware of and can locate the resources and supports available to them. Additionally, the formation of the maps can be a beneficial exercise for departments to use to assess their own assets and strategically plan for the development of new assets.
Urooj Raja, University of Colorado-Boulder; Wednesday April 3, 2019 1:55 PM
This presentation will not be live streamed nor recorded.
Emerging technologies are proliferating at a rapid pace. Scholars use the broad term emerging technologies as a catchall phrase to describe those technologies that show massive innovative potential, can be rapidly absorbed into the market place, and have the power to disrupt the status quo. Artificial intelligence, nanotechnology, robotics, and virtual reality are all examples of emerging technology. A byproduct of emerging technologies is emerging inequality, for example, advances in automation will cut down the need for blue collar workers, whereas educational advances in artificial intelligence will help the most affluent school districts that have the ability to pay for the expensive tech retain the technology. It also remains that despite the pervasive use of emerging tech, scholars have been slow to investigate the social implications of these technologies. For example, little research considers the racial, gender, institutional and class disparity effects of emerging technology. Of the handful of studies that do consider these effects, many researchers study these impacts in isolation, and subsequently do not understand the intersecting nature of these disparities. Nonetheless, it remains that emerging technology is going to exert a momentous impact on how society is and will be shaped in the years to come. In this backdrop, it is essential that scholars discuss new ideas on how we can study the resultant inequity impacts of emerging tech on society. The ultimate goal of this presentation is to provide a snapshot of these new directions to the study of emerging tech and inequality, and perhaps more ambitiously to discuss how we can bring this issue to the consciousness of others. Questions to consider: How do we consider the benefits and potential pitfalls of emergent tech across disciplines and methodologies? What roles and responsibilities do scholars have in studying emerging tech? How does emerging tech magnify the already preexisting biases in our society? Is emerging tech making our society more or less unequal, what are the implications of such an occurrence?
Kirsten Rowell, University of Colorado-Boulder and Carolyn Finney, Independent Scholar; Thursday April 4, 2019 9:15 AM
This presentation will not be live streamed nor recorded.
The stories of environmental stewardship that have been historically championed in the U.S. have been woefully exclusive and homogenous - not very representative of national demographics. The impact and efficacy of environmental work is severely limited when communities don’t see themselves in language, curriculum, and media related to environmental work. Recruiting, retaining and enabling future professionals from across the many communities that represent the U.S. will require multiple approaches and restorative work within the environmental field, curriculum, and programming. We use storytelling as a tool for building identity within the field, a restorative and empowering practice, and even a learning tool for those stuck in normative culture. Through this process, a new generation of environmental professionals form their own authentic connections to the environment, built the intercultural trust necessary to talk across differences, and challenged our understanding of the boundaries in the field of conservation.
Hong Qin, University of Tennessee at Chattanooga; Thursday April 4, 2019 9:20 AM
The author will present his experience of integrate screen-recording to enhance student learning experience of computational biology. Students were required to screen-recording their process of solving computational problems. These screen-recordings can be used to identify the learning hurdles of students and improve student learning experiences.
Louis Gross, University of Tennessee; Thursday April 4, 2019 9:25 AM
Under the auspices of the National Academies, a Committee developed a consensus report regarding means to enhance undergraduate programs in the emerging discipline of data science. Building upon advice from a variety of on-line and in-person interactions with a broad spectrum of experts, the report provides a collection of findings and recommendations for initiating, developing and evaluating programs that prepare students for careers in data science as well as encouraging methods for all undergraduates to be exposed to basic concepts in this field. I will summarize the suggestions made regarding development of data acumen, incorporation of real-world examples, enhancing teamwork and communication, ethical considerations, and assessment and evaluation of data science programs. I will emphasize the potential for such programs to broaden participation in quantitative science and the benefit of utilizing environmental data and examples that align with the interests of diverse students.
Megan Jones, Battelle/NEON; Thursday April 4, 2019 9:30 AM
NEON, the National Ecological Observatory Network, is an NSF-funded large science facility, operated by Battelle, is designed to collect extensive ecological and environmental data from across the U.S. for the next 30 years. A primary product of NEON is freely available, open access data for use by the scientific research community as well as by students and others who will explore the petabytes of information that will be available during the lifetime of the Observatory. Using NEON data, however, may not be an easy task for researchers, faculty, and students who are not familiar with “big data” access, management and analytic methods. Many ecologists are transitioning to using data science and big data methods including programming-based data management and analysis, complex data portals and APIs that provide access to lots of different types of data, and diverse analytical methods beyond those classically used in their individual research area. Furthermore, ecological data is usually messy in the sense that variability and uncertainty are important components of data analysis and interpretation. Given these challenges, how do we accelerate the use of big data in ecological research and education? How to we create equitable opportunities for data and resource access to all interested individuals? How do we engage communities that have not traditionally been drawn to careers in ecology but for which data science focused careers may provide new opportunities?
Gary Silverstein, Westat and Coordination Hub Team; Thursday April 4, 2019 9:35 AM
Kaitlin Stack Whitney; Simon J Goring; Aerin Jacob, Emilio Bruna, and Timothee Poisot
Effective communication is critical to scientific practice. So much so that that helping scientists improve their communication skills has been a significant focus of energy for organizations ranging from academic societies to graduate training programs. The need for effective communication could also be viewed as central to "Open Science‚" and making research products (e.g., data, code, scientific literature) more broadly readily available. Despite this, however, surprisingly little attention has been paid to ensuring that presentations are accessible to all. Improving accessibility requires some foresight, planning, and preparation on the part of the presenter: accessibility-centered thinking. Yet fear that accessibility requires expensive or complicated tools and workflows may prevent people from trying - so here we provide evidence-based, simple but concrete steps for creating and sharing science for all.
National Institute for STEM Evaluation and Research Pam Bishop The National Institute for STEM Evaluation and Research (NISER) provides quality evaluation services to the Science, Technology, Engineering and Mathematics (STEM) research and education sectors, with an emphasis on diversity, equity, and inclusion. NISER was founded in 2016 under the leadership of Dr. Pamela Bishop and is part of the National Institute for Mathematical and Biological Synthesis (NIMBioS), housed at the University of Tennessee, Knoxville. NISER's staff has experience in systems-level evaluation, a deep understanding of interdisciplinary team science, a professional collaborative approach to program evaluation and research, and the ability to untangle the complexity of large-scale STEM programs. We offer a range of data-driven services to best serve our collaborators' needs.
The primary goal of Jarvis Christian College (JCC) two years project with the title, "The Implementation of Differentiated Instruction to Introduction to Statistics, Data Mining, and Analytics at Jarvis Christian College," is to meet the needs of students with diverse abilities and interests, so that the faculty could improve the engagement with the students, enhance the students' skills (abilities) and interests in mathematics, and increase the number of the students who passed the course with 80% passing grades. Differences in Introduction to Statistics, Data Mining, and Analytics at Jarvis Christian College are cognitive, learning styles and preferences, and abilities and interests. The differentiated instruction is a method of instruction designed to meet the needs of all students by changing what students learn (content), how they accumulate information (process), how they demonstrate knowledge or skills (product), and with whom and where learning happens (learning environment). Furthermore, it's a way of thinking about teaching and learning to ensure that children receive appropriate classroom experiences according to the differentiated instruction expert Carol Tomlinson. We build our differentiated instruction for this course by converging different student centered active learning into a blended course as follows: 1) Setting up the course as a blended or hybrid course, i.e. 75% is face to face instruction and 25% is online instruction. So, the classroom attendance is required and a part of the grade. Additionally, the students have one on one help sessions with the instructors and the teaching assistants in the classrooms and with the instructors during the office hours as well as with the teaching assistants in the Student Success Services Building. 2) Before coming to the classroom, the students should work on the flipped online assignments, i.e. reading the textbook and watching the video lectures related to the coming topics that will discuss in the classroom. 3) In the classroom, using inquiry based learning the faculty discussed the topics covered for that day for the entire class, then the faculty with teaching assistant have the one on one help session with the students for any problems in the homework assignments and assessments. 4) After the class, the students continue completing the assignments on the online automatic grading homework software. The students work in the groups or individually. For the high achievers, they could move ahead to the next assignments and finish earlier than the other students. For the lower achievers, they could go to the help sessions with the faculty or teaching assistants. 5) At the end of the semester, the students have to submit projects on the applications of statistics, data mining, and analytics in their majors.
Olivia Vasquez, John Petersen, and Rowan Hannan
"Environmental Dashboard" (ED) is an interactive communication technology that introduces feedback into our industrialized society, where we are so far removed from naturally occurring feedback loops. Our goal is to promote systems thinking and foster pro-environmental and pro-community action. Through the Dashboard's several core components, we provide real-time information on resource-use and highlight the thoughts and actions of community members. The ED content is available on the web and digital signage that show a virtual town model with animated characters and real-time flows of water, energy, and environmental conditions. The "Community Voices" component features images and text derived from community discussions, interviews, public documents, and schools to celebrate positive thought and action. The Environmental Dashboard has been implemented in the City of Oberlin, Ohio for over a decade and components are now installed in buildings and communities across the country. Extensive research suggests that the technology is effective at building awareness, shifting social norms, enhancing emotional connection to resource use, and promoting behavior change.
The participation of American Indian/Alaskan Native (AIAN) people and other underrepresented minority (URM) populations in STEM fields remains shockingly low. In the computational field, it is even lower. AIAN face various barriers that impede them from pursuing or continuing careers in genomics. Alongside, there is a demand for Integrating bioinformatics and data science into the life sciences curriculum. I am presenting a one-week workshop training format that allows students to gain hands-on laboratory and computational experience to understand the diversity of local environmental microbiomes in Colorado and New Mexico. This workshop targets early-career undergraduate students from Southwest regional PUIs, two-year and tribal colleges. Aligning cultural sensitivities that may arise with sampling and working with biological samples with Indigenous / AIAN cultures. Core competencies incorporated in the workshop are computational concepts (algorithms and file formats), statistics, accessing genomic data and running bioinformatics tools to analyze data. I will discuss some of the successes and pitfalls that I have encountered and the adaption for a one-semester course.
The West Big Data Innovation Hub builds and strengthen strategic partnerships across academia, industry, nonprofits, and government--harnessing the data revolution to address scientific and societal challenges. Whether working towards the future of data-informed policies to ensure safe drinking water or tackling challenges in disaster recovery, our diverse and growing team of stakeholders envisions a community empowered to contribute to a thriving regional, national, and global innovation ecosystem. The Hubs provide a creative and inclusive "home", an affiliation that sparks meaningful connections and enables valuable work to positively impact science and society. We focus on data science activities and initiatives that inspire cross-sector collaboration and exemplify the need for multi-disciplinary approaches. The Hub creates an open community with an array of engagement opportunities where all are welcome, encouraging participation from underrepresented groups, organizations, and geographic regions. The project broadens participation across traditional boundaries between disciplines, sectors, institutions, and demographic groups, focusing on critical challenges, open source tools, and collaborative insights.
Melissa Hernández, Bala Chaudhary, Malcom Engel, Charles Espedido, Amelia Howerton, Jazlyn Marcos, Brittany Rivera, and Tania Schusler
Racial and ethnic diversity in environmental disciplines lags far behind the 38% people of color (POC) population in the U.S., despite research documenting high levels of environmental concern among POC. Addressing this inequity is essential to advance environmental justice. Identity diversity also lends itself to cognitive diversity, which promotes creativity and innovation in solving environmental problems. Environmental degree programs serve as a pipeline to environmental careers. Thus, we investigated the experiences of students of color in undergraduate environmental degree programs using grounded theory methodology. We interviewed 24 undergraduates at two private universities in Chicago who self-identify as racial or ethnic minorities and have declared an environmental major. Interviews examined motivations for entering environmental fields, perceived barriers and supports to academic success, and suggestions to improve racial and ethnic inclusion within environmental degree programs. We inductively analyzed data across interviews via an iterative process of coding, categorizing, and memo-writing to identify emergent themes. The results deepen understanding of how environmental programs in higher education can become more inclusive, thereby strengthening the pipeline to environmental careers for POC and increasing racial and ethnic diversity in the field towards more innovative and just environmental solutions. The students we interviewed spoke of prior educational experiences, influential individuals, and prior experiences in their communities as factors influencing them to study the environment. Many described a concern for social well-being in tandem with ecological well-being as a key motivator to pursue an environmental major. Yet, some students felt that the curriculum in their program did not sufficiently integrate ecological and social perspectives. They perceived that social implications of science learning were understudied and that environmental solutions presented in classes often reflected a "white environmentalism" incompatible for many POC. This, as well as a lack of awareness or unwillingness of instructors and white peers to discuss the experiences of different social groups and the role of identity within social-ecological systems, left some students feeling excluded. As a POC in a majority white setting, some students also felt isolated due to a disconnect between their own backgrounds and those of peers and instructors. Others experienced discrimination, such as micro-aggressions or tokenism, that furthered this sense of isolation. On the other hand, some students described how support networks enhanced their program satisfaction. Faculty and staff played key roles in guiding students of color to enter and succeed in the environmental major. Some faculty validated racial and ethnic inequities in the context of course content, enabling students of color to feel comfortable sharing their own perspectives. Students‚ membership in organizations‚ some within the environmental degree program and others external to it‚ allowed them to connect and form bonds with other POC as well as white peers. These organizations also provided opportunities for students of color to engage more deeply with the environmental subjects of greatest interest to them. The students interviewed recommended four key ways to cultivate racial and ethnic diversity within environmental degree programs: (1) Intentionally recruit students of color. (2) Hire diverse faculty and staff, and provide diversity training for all faculty and staff. (3) Include the perspectives, literature, socio-ecological problems, and approaches of POC into the curriculum. (4) Create resources specifically for, and accessible to, students of color for finding support and engaging with environmental topics of interest.
Diana Dalbotten, Antony Berthelote, and Nievita Bueno Watts
The aim of the REU on Sustainable Land and Water Resources is to introduce undergraduate students to the key elements of research on land and water resources that are essential to improving management practices, with a focus on Community-Based Participatory Research (CBPR) and diverse interdisciplinary research teams. Students work on teams on projects that integrate Earth-surface dynamics, geology, hydrology and other disciplines. Research teams are hosted on two Native American reservations and at the Univ. MN and projects are developed in collaboration with the tribes' resource management divisions. The REU incorporates an interdisciplinary team-oriented approach that emphasizes quantitative and predictive methods, CBPR, indigenous research methods, and traditional ecological knowledge.
The REU Site is developing a new paradigm for undergraduate research incorporating place-based and community-based participatory research. The PIs are building knowledge on increasing participation in REUs by the non-traditional student and students from groups underrepresented in STEM. The PIs have developed a proven, structured, scaffolded method of teaching science research and writing, which takes students who may have never written a technical research paper and provides them the skills and support needed to routinely deliver an astonishing level of vigorous intellectual output and increase their intellectual self-confidence in the process.
Susan Bonfield and Dalia Dorta
Environment for the Americas (EFTA) has conducted model minority youth internship programs to recruit youth of color and to provide them the opportunity to work side by side with professionals from governmental and non-governmental organizations, including Los Angeles Audubon, US Fish and Wildlife Service, Bureau of Land Management, National Park Service, and US Forest Service. Our experience working with underserved youth is informed by four years of NSF-funded research on how to improve the participation by diverse people in informal science education programs. Today, we work with over 50 youth each year and provide mentorship and support not only during their internships, but also after, supporting them as they seek jobs and/or graduate school admissions. EFTA shares its expertise and participates in efforts nationally and internationally by serving on the Board of the Diversity Joint Venture and on the Society for Conservation Biology's Anti-Sexual Harassment/Violence Taskforce.
Dennis G. Dye
The Southwestern Indian Polytechnic Institute (SIPI) is an Albuquerque, New Mexico-based national community college that serves the higher education needs of Native American Tribes and Alaska Native communities throughout the country. Several of SIPI's academic programs, including Geospatial Information Technology (GIT), Pre-Engineering and Mathematics, expose students to various aspects of Data Science, however coordination of their respective curricula has been limited. This presentation describes emerging opportunities at SIPI to establish an interdisciplinary program in Data Science that provides a framework for coordination and synergy, and in turn, enhances SIPI students' success in 4-year baccalaureate programs, and improves their competitiveness for quality STEM-related jobs. Particular attention is given to possibilities to incorporate into the GIT Program a new area of emphasis on "Distributed Sensor Systems and Wireless Sensor Networks for Monitoring of Water Resources, Ecosystems and Climate", and its role in the potential Data Science program.
Jenny Palomino, Leah Wasser, and Lauren Herwehe
The Earth Lab Earth Analytics Education Initiative at the University of Colorado -- Boulder is building an innovative program that provides core in-market demand technical skills at the intersection of Earth and data science to undergraduate, graduate and professional students. The program includes formal courses, workshops, career development events with industry partners, paid undergraduate internships, an open online learning portal with global reach, and a professional certificate in Earth data analytics, one of the first of its kind in the country. We are committed to expanding the reach of Earth data science education for students across varying academic, professional, socio-economic and geographic dimensions to ensure broad accessibility to novel curriculum. All courses support a blended mix of students with varied academic and professional experiences, resulting in interdisciplinary and multi-level classrooms that enrich students’ learning through collaborative and peer feedback activities that introduce new ideas and ways of thinking. To accommodate diverse student needs and increase program access, courses are offered through both online and traditional options, allowing students to participate in-person, online in real-time, or asynchronously by reviewing materials at their own pace. This flexibility supports the inclusion of students with full-time employment or other commitments that challenge enrollment in traditional courses as well as remote students living in other parts of the country or globe, who may not have access to similar curriculum locally. Our curriculum is informed by industry surveys to ensure that students are learning sought after skills at the intersection of earth and data science. All lessons use open source tools to teach students how to work with real-world data to address questions and challenges for earth and environmental systems. We comprehensively evaluate our courses using formative, summative, and longitudinal approaches (including student surveys, grades, and website metrics) to ensure that learning goals are being met and that all students are satisfied with the blended learning environment. To support Universal education, all course materials are carefully designed to support asynchronous online and independent learning. Materials are search engine optimized to ensure greater visibility and then published online on the earthdatascience.org website, which has a rapidly growing user base of more than 41,000 unique global monthly users. Our blended, open education model opens access for students world-wide, who may otherwise not have access to this curriculum, to develop key skills for careers in earth and environmental data science at their own pace.
C. Diaz Eaton, M.D. LaMar, and N. Chodlowski
QUBES is a community of practitioners, institutions, researchers, networks, and professional societies all devoted to supporting instructors around the country for an increasingly quantitative biology field. We provide faculty mentoring networks for virtual professional support, connect faculty to high quality curriculum, and host a virtual infrastructure for open educational resource sharing and software use. All our welcome to join for free at qubeshub.org!
Alternative fueled vehicle adoption is one of the critical solutions to mitigate carbon emissions in the transportation sector. Even though electric vehicles (EV) have been leading the market adoption among zero-emission vehicles, hydrogen fuel cell vehicles (FCV) have also been increasingly adopted in the past few years. FCVs have several advantages over EVs, such as shorter refueling time and higher driving range, but unlike electric vehicles which could be charged at home or work, they require sufficient and reliable network of hydrogen refueling stations. This research project carries out an integrated quantitative-qualitative study to assess the reliability and performance of hydrogen fueling station network in California. For the quantitative analysis, we collected the hourly capacity data of all the hydrogen fueling stations for three months. This time-series data was used to develop a novel term called "Normalized Relative Usage Index" (NRUI) that encapsulates the usage of each station over time in the network. We spatially regressed this value over the number of fuel cell vehicles present in the neighborhood to identify the stations that are in the "healthy usage range" and those that are under-utilized or over-stressed. We also designed a survey to obtain the experiences of FCV drivers on the station performance. About 100 participants took the survey, and their answers predominantly validate the quantitative analysis. Moreover, the respondents articulated their reasons for the stations that are outside of the healthy usage range as well as their expectations for a station to be considered reliable. This comprehensive study is first of its kind to explore spatially explicit supply and demand of the hydrogen fueling infrastructure network. Even though the research paper focuses its analysis on the hydrogen refueling stations in California for a specific period, this data-driven methodology is region and timescale-independent and could be extended for larger timescales to monitor the station performance as perceived by the users. We are also releasing the hourly station capacity dataset that was collected as a part of this study to the research community.