Conducting ecological research in a way that addresses complex, real‐world problems requires a diverse, interdisciplinary and quantitatively trained ecology and environmental science workforce. This begins with equitably training students in ecology, interdisciplinary science, and quantitative skills at the undergraduate level. Understanding the current undergraduate curriculum landscape in ecology and environmental sciences allows for targeted interventions to improve equitable educational opportunities. Ecological forecasting is a sub‐discipline of ecology with roots in interdisciplinary and quantitative science. We use ecological forecasting to show how ecology and environmental science undergraduate curriculum could be evaluated and ultimately restructured to address the needs of the 21stcentury workforce. To characterize the current state of ecological forecasting education, we compiled existing resources for teaching and learning ecological forecasting at three curriculum levels: online resources; US university courses on ecological forecasting; and US university courses on topics related to ecological forecasting. We found persistent patterns (1) in what topics are taught to US undergraduate students at each of the curriculum levels; and (2) in the accessibility of resources, in terms of course availability at higher education institutions in the United States. We developed and implemented programs to increase the accessibility and comprehensiveness of ecological forecasting undergraduate education, including initiatives to engage specifically with Native American undergraduates and online resources for learning quantitative concepts at the undergraduate level. Such steps enhance the capacity of ecological forecasting to be more inclusive to undergraduate students from diverse backgrounds and expose more students to quantitative training.
Developing a flexible learning activity on biodiversity and spatial scale concepts using open‐access vegetation datasets from the National Ecological Observatory Network
Biodiversity is a complex, yet essential, concept for undergraduate students in ecology and other natural sciences to grasp. As beginner scientists, students must learn to recognize, describe, and interpret patterns of biodiversity across various spatial scales and understand their relationships with ecological processes and human influences. It is also increasingly important for undergraduate programs in ecology and related disciplines to provide students with experiences working with large ecological datasets to develop students’ data science skills and their ability to consider how ecological processes that operate at broader spatial scales (macroscale) affect local ecosystems. To support the goals of improving student understanding of macroscale ecology and biodiversity at multiple spatial scales, we formed an interdisciplinary team that included grant personnel, scientists, and faculty from ecology and spatial sciences to design a flexible learning activity to teach macroscale biodiversity concepts using large datasets from the National Ecological Observatory Network (NEON). We piloted this learning activity in six courses enrolling a total of 109 students, ranging from midlevel ecology and GIS/remote sensing courses, to upper‐level conservation biology. Using our classroom experiences and a pre/postassessment framework, we evaluated whether our learning activity resulted in increased student understanding of macroscale ecology and biodiversity concepts and increased familiarity with analysis techniques, software programs, and large spatio‐ecological datasets. Overall, results suggest that our learning activity improved student understanding of biological diversity, biodiversity metrics, and patterns of biodiversity across several spatial scales. Participating faculty reflected on what went well and what would benefit from changes, and we offer suggestions for implementation of the learning activity based on this feedback. This learning activity introduced students to macroscale ecology and built student skills in working with big data (i.e., large datasets) and performing basic quantitative analyses, skills that are essential for the next generation of ecologists.
more » « less- NSF-PAR ID:
- 10452755
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Ecology and Evolution
- Volume:
- 11
- Issue:
- 9
- ISSN:
- 2045-7758
- Page Range / eLocation ID:
- p. 3660-3671
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Opportunities for undergraduate research in STEM programs at community colleges can be few where lower-division science curriculum emphasizes classroom and laboratory-based learning and research laboratories are limited in number. This is particularly true in the geosciences where specialized programs are extremely rare. Urban serving academic research institutions have a unique role and opportunity to partner with regional community college programs for undergraduate research early-on in student post-secondary educational experiences. Programs built for community college transfer students to urban serving undergraduate programs can serve to integrate students into major programs and help reduce transfer shock. The benefits of exploring research as an undergraduate scholar are numerous and include: building towards mastery of technical skills; developing problem-solving in a real-world environment; reading and digesting scientific literature; analyzing experimental and simulation data; working independently and as part of a team; developing a mentoring relationship with a research advisor; and building a sense of belonging and confidence in a scientific field. However, many undergraduate research internships are targeted towards junior-level STEM majors already engaged in upper-division coursework and considering graduate school which effectively excludes community college students from participating. The Center for Climate and Aerosol Research (CCAR) Research Experience for Undergraduate program at Portland State University serves to help build the future diverse research community. 10-week intern research experiences are paired with an expert faculty mentor are designed for students majoring in the natural/physical sciences but not necessarily with a background in climate or atmospheric science. Additional programmatic activities include: 1-week orientation and training using short courses, faculty research seminars, and hands-on group workshops; academic professional and career development workshops throughout summer; journal club activities; final presentations at end of summer CCAR symposium; opportunities for travel for student presentations at scientific conferences; and social activities. Open to all qualifying undergraduates, since 2014 the program recruits primarily from regional (Northwest) community colleges, rural schools, and Native American serving institutions; recruiting students who would be unlikely to be otherwise exposed to such opportunities at their home institution. Over the past 9 cohorts of REU interns (2014-2019), approximately one third of CCAR REU scholars are community colleges students. Here we present criteria employed for selection of REU scholars and an analysis of selection biases in a comparison of students from community colleges, 4-year colleges, and PhD granting universities. We further investigate differential outcomes in efficacy of the REU program using evaluation data to assess changes over the program including: knowledge, intrinsic motivation, extrinsic motivation, science identity, program satisfaction, and career aspirations. In this presentation, we present these findings along with supportive qualitative analyses and discuss their implications for community college students in undergraduate research programs in geosciences.more » « less
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There is a critical need for more students with engineering and computer science majors to enter into, persist in, and graduate from four-year postsecondary institutions. Increasing the diversity of the workforce by inclusive practices in engineering and science is also a profound identified need. According to national statistics, the largest groups of underrepresented minority students in engineering and science attend U.S. public higher education institutions. Most often, a large proportion of these students come to colleges and universities with unique challenges and needs, and are more likely to be first in their family to attend college. In response to these needs, engineering education researchers and practitioners have developed, implemented and assessed interventions to provide support and help students succeed in college, particularly in their first year. These interventions typically target relatively small cohorts of students and can be managed by a small number of faculty and staff. In this paper, we report on “work in progress” research in a large-scale, first-year engineering and computer science intervention program at a public, comprehensive university using multivariate comparative statistical approaches. Large-scale intervention programs are especially relevant to minority serving institutions that prepare growing numbers of students who are first in their family to attend college and who are also under-resourced, financially. These students most often encounter academic difficulties and come to higher education with challenging experiences and backgrounds. Our studied first-year intervention program, first piloted in 2015, is now in its 5th year of implementation. 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Abstract Inquiry activities have become increasingly common in
Ecology and Evolution courses, but the rapid shift to remote instruction for many faculty members in response to the COVID‐19 pandemic has created new challenges for maintaining these student‐centered activities in a distance learning format. Moving forward, many instructors will be asked to create flexible course structures that allow for a mix of different teaching modalities and will be looking for resources to support student inquiry in both online and in‐person settings. Here, we propose the use of data‐driven inquiry activities as a flexible option for offering students experiences to build career‐relevant skills and learn fundamental ecological concepts. We share lessons learned from our experiences teaching a two‐semester course‐based research experience in global change ecology that leverages publicly available datasets to engage students in broadly relevant scientific inquiry.
