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1. Quantitative Biology at Community Colleges, a Network of Biology and Mathematics Faculty Focused on Improving Numerical and Quantitative Skills of Students

   https://doi.org/10.1187/cbe.21-09-0244  

   Esquibel, Joseph; Rook, Deborah L.; LoRe, Sondra M.; Starnes, John H.; Miller, Jillian M.; Buntz, Jennifer G.; Hugo, Alys; Nieuwsma, Christianne B.; Seitz, Heather; Bissell, Ahrash; et al (June 2023, CBE—Life Sciences Education)

   Kurushima, Jennifer (Ed.)

   Mastery of quantitative skills is increasingly critical for student success in life sciences, but few curricula adequately incorporate quantitative skills. Quantitative Biology at Community Colleges (QB@CC) is designed to address this need by building a grassroots consortium of community college faculty to 1) engage in interdisciplinary partnerships that increase participant confidence in life science, mathematics, and statistics domains; 2) generate and publish a collection of quantitative skills–focused open education resources (OER); and 3) disseminate these OER and pedagogical practices widely, in turn expanding the network. Currently in its third year, QB@CC has recruited 70 faculty into the network and created 20 modules. Modules can be accessed by interested biology and mathematics educators in high school, 2-year, and 4-year institutions. Here, we use survey responses, focus group interviews, and document analyses (principles-focused evaluation) to evaluate the progress in accomplishing these goals midway through the QB@CC program. The QB@CC network provides a model for developing and sustaining an interdisciplinary community that benefits participants and generates valuable resources for the broader community. Similar network-building programs may wish to adopt some of the effective aspects of the QB@CC network model to meet their objectives. 

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2. “It Can’t Tell You How to Do That.” Suggesting a Faculty-Focused Subgenre of Instructional Writing

   https://doi.org/10.1109/ProComm53155.2022.00006  

   Owusu-Ansah, Alfred L.; Jarvie-Eggart, Michelle (July 2022, 2022 IEEE International Professional Communication Conference (ProComm))

   As we prepare new engineers to take on the fourth industrial revolution, engineering faculty are tasked with selecting, learning, evaluating, using, and teaching new technologies to apprentice engineers. To understand how these important tasks are being achieved, 21 engineering faculty members in a STEMfocused Midwest US university were interviewed. Engineering faculty showed an awareness of the rhetorical power of manuals and other instructional resources. Unfortunately, these resources are often inadequately designed to meet the unique needs of engineering faculty. In this paper, we propose that there is an exigency for a faculty-focused subgenre of instructional writing which addresses the needs of engineering instructors who teach students how to use technology while simultaneously learning how to use it themselves. Because of the overwhelming roles that faculty perform, we propose that the composition of this sub-genre should be the duty of technical writers who work closely with technology developers and engineering faculty. We forward that such a subgenre may find space in digital and non-digital learning resources through the inclusion of both the technical information necessary to use the technology, as well as pedagogical tools and activities to support student learning. These materials should be released in accordance with technology updates to ensure faculty are best positioned to teach the most current technologies. The proposed faculty-focused instructional writing subgenre may have implications beyond engineering education, because the need for learning resources may not be unique to engineering faculty, and likely exists for all university faculty learning and introducing new technologies within their courses. 

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3. The Genomics Education Partnership: First Findings on Genomics Research in Community Colleges

   https://doi.org/10.18833/spur/6/3/1  

   Croonquist, Paula; Falkenberg, Virginia; Minkovsky, Natalie; Sawa, Alexa; Skerritt, Matthew; Sustacek, Maire; Diotti, Raffaella; Aragon, Anthony; Mans, Tamara; Sherr, Goldie; et al (January 2023, Scholarship and Practice of Undergraduate Research)

   The Genomics Education Partnership (GEP), a consortium of diverse colleges and universities, provides support for integrating genomics research into undergraduate curricula. To increase research opportunities for underrepresented students, GEP is expanding to more community colleges (CC). Genomics research, requiring only a computer with Internet access, may be particularly accessible for two-year institutions with limited research capacity and significant budget constraints. To understand how GEP supports student research at CCs, the authors analyzed student knowledge and self-reported outcomes. It was found that CC student gains were comparable to non-CC student gains, with improvements in attitudes toward science and thriving in science. The early findings suggest that the GEP model of centralized support with flexible implementation of a course-related undergraduate research experience benefits CC students and may help mitigate barriers to implementing research at CCs. 

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4. Diversifying the genomic data science research community

   https://doi.org/10.1101/gr.276496.121  

   The Genomic Data Science Community Network (July 2022, Genome Research)

   Over the past 20 years, the explosion of genomic data collection and the cloud computing revolution have made computational and data science research accessible to anyone with a web browser and an internet connection. However, students at institutions with limited resources have received relatively little exposure to curricula or professional development opportunities that lead to careers in genomic data science. To broaden participation in genomics research, the scientific community needs to support these programs in local education and research at underserved institutions (UIs). These include community colleges, historically Black colleges and universities, Hispanic-serving institutions, and tribal colleges and universities that support ethnically, racially, and socioeconomically underrepresented students in the United States. We have formed the Genomic Data Science Community Network to support students, faculty, and their networks to identify opportunities and broaden access to genomic data science. These opportunities include expanding access to infrastructure and data, providing UI faculty development opportunities, strengthening collaborations among faculty, recognizing UI teaching and research excellence, fostering student awareness, developing modular and open-source resources, expanding course-based undergraduate research experiences (CUREs), building curriculum, supporting student professional development and research, and removing financial barriers through funding programs and collaborator support. 

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5. Using genome annotation projects to teach eukaryotic gene structure and to engage studentsin genomics research

   https://doi.org/10.37590/able.v43.art17  

   Santisteban, Maria S.:; Goodman, Anya L.; Hauser, Charles R.; Paetkau, Don; Reinke, Catherine; Leung, Wilson; Arrigo, Cindy; Mortimer, Nathan T.; Reed, Laura K. (January 2023, Advances in Biology Laboratory Education)

   The Genomics Education Partnership (GEP; https://thegep.org) began as a consortium of 16 faculty in 2006 with a goal of providing students with Course-based Undergraduate Research Experiences (CUREs) in genomics. Today, GEP has over 200 faculty from more than 180 institutions and engages more than 3,900 undergraduates in authentic genomics research annually. These faculty joined and continued to participate in the GEP for many reasons, including the collaborative nature of the research, the well-established infrastructure, and the supportive network of like-minded colleagues. Faculty implement GEP materials in diverse settings ? ranging from short modules (2-8 weeks) within a course, to a standalone full-semester course, to independent student research. GEP students show significant gains in scientific knowledge and attitudes toward science. In addition to improving their understanding of the research process and how new knowledge is created in the field, GEP students acquire desirable and transferable skills essential for future participation in the workforce, such as problem solving, independence, application of knowledge, team-work, and collaboration. Students also gain competence in the use of computational algorithms to analyze large biological datasets ? thereby preparing students for a growing need of a workforce trained at applying statistics and computational tools to analyze large datasets. In addition, GEP students and their faculty mentors are eligible to be co-authors on the scientific publications that are based on their work. In this workshop, we will provide an overview of the GEP community, a hands-on guided tour of our introductory curriculum aimed to teach gene structure, transcription, translation, and processing, and a step-by-step walkthrough that illustrates the protocol for annotating a protein-coding gene in Drosophila. Participants will receive information on how to join the GEP community and receive training and resources to enable their implementations. 

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