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Diaz Eaton, Carrie, (2016), "Topics and Issues in Mathematical Biology Education", Annual Meeting of the Society for Mathematical Biology, : Nottingham, UK, July, . Cited by:

Minisymposium Co-organizer

Diaz Eaton, Carrie, (2016), "Frameworks for Teaching Mathematical Modeling to Biologists", Joint Meeting of the Education Section of the Society for Industrial and Applied Mathematics and Mathematics of Planet Earth, : Philadelphia, Pennsylvania, October, . Cited by:

Invited Session C-organizer

Diaz Eaton, Carrie, (2016), "Approaches to Teaching Mathematical Modeling", International Symposium of Biomathematics and Ecology Education and Research, : Charleston, South Carolina, October, . Cited by:

Invited Session Co-organizer

Diaz Eaton, Carrie, (2017), "Careers in Environmental biology", : . Cited by:

Steering Committee member on NSF RCN-UBE grant submitted 2017, Lead PI Teresa Mourad, Ecological Society of America.

Diaz Eaton, Carrie, LaMar, Drew, (2017), "Modeling Hub", : . Cited by:

Steering Committee for a joint project of SIAM, MAA, NCTM, and COMAP

Fleming-Davies, Arietta, (2017), "4th Life Discovery – Doing Science Biology Education Conference ", : . Cited by:

Planning Committee

Wojdak, Jeremy, (2017), "QUBES Faculty Mentoring Fellows Program", Online, : Online, March, . Cited by:
Monfils, Anna, Phillips, Molly, Linton, Debra, Donovan, Sam, Hale, Alison, (2017), "Resources for Collections-Based Undergraduate Education Faculty Mentoring Network", Online, : Online, April, . Cited by:
Hanselman, Jennifer, Holmberg, Tara, Steinweg, Meg, Hamerlinck, Gaby, (2017), "InTeGrate 2017 Faculty Mentoring Network", Online, : Online, January, . Cited by:
Fleming-Davies, Arietta, Grayson, Kristine, Bonner, Kaitlin, (2017), "DIG into Data Faculty Mentoring Network", Online, : Online, January, . Cited by:
Hamerlinck, Gaby, Fleming-Davies, Arietta, Jenkins, Kristin, Mourad, Teresa, (2017), "ESA Data Discovery Faculty Mentoring Network", Online, : Online, January, . Cited by:
Amagai, Satoshi, Csikari, Melissa, Hamerlinck, Gaby, (2016), "HHMI Biointeractive Faculty Mentoring Network", Online, : Online, June, . Cited by:
Fleming-Davies, Arietta, Wojdak, Jeremy, Hale, Alison, Jenkins, Kristin, (2016), "Math Attitudes and Anxiety Faculty Mentoring Network", Online, : Online, September, . Cited by:
Donovan, Sam, Jenkins, Kristin, Hale, Alison, Meir, Eli, Roach, John, (2016), "SimBio Faculty Mentoring Network", Online, : Online, July, . Cited by:
Orndorf, Hayley, Pauley, Mark, Ryder, Elizabeth, Sierk, Michael, Wright, Robin, Rosenwald, Anne, Dinsdale, Elizabeth, Triplett, Eric W., Donovan, Sam, Morgan, William, (2017), "Incubators: A community based model for improving the usability of bioinformatics learning resources", Gordon Research Conference on Undergraduate Biology Education Research, : Easton, Massachusetts, July, . Cited by:

The Network for Integrating Bioinformatics into Life Sciences Education (NIBLSE) is an NSF funded Research Coordination Network that aims to establish bioinformatics as an essential component of undergraduate life sciences education. As part of that effort, the project is working to make existing bioinformatics learning resources more accessible to non-specialists and increase their use across undergraduate biology courses. To this end, NIBLSE has partnered with the Quantitative Undergraduate Biology Education and Synthesis (QUBES) project and CourseSource to develop and implement a novel model for supporting the refinement, publication, and dissemination of high quality bioinformatics teaching resources.

Dinsdale, Elizabeth, Pauley, Mark, Rosenwald, Anne, Triplett, Eric W., Morgan, William, (2017), "NIBLSE: A network to fully integrate bioinformatics into undergraduate life science education", Great Lakes Bioinformatics Conference, : Chicago, Illinois, May, . Cited by:

Despite its increasing importance in nearly all areas of biology, bioinformatics has yet to be fully integrated into undergraduate life science curricula. To this end, the Network for Integrating Bioinformatics into Life Sciences Education (NIBLSE, pronounced “nibbles”) was formed and funded by the NSF to: 1) create a network of investigators committed to integrating bioinformatics into undergraduate life sciences education; 2) develop and disseminate a set of core bioinformatics competencies for undergraduate students in the biological sciences; 3) identify and disseminate assessment tools that are aligned with the core competencies; and 4) organize and vet curricular activities and professional development materials that address the competencies. This presentation will present our current progress on these objectives. Foremost, the growing NIBLSE community of biology and bioinformatics educators has recently defined a set of bioinformatics core competencies essential for all life scientists. In addition, NIBLSE, in cooperation with QUBES, has developed an online platform to develop and disseminate bioinformatics learning resources (https://qubeshub.org/groups/niblse). Finally, NIBLSE will soon begin efforts to identify assessment tools for biology instructors incorporating bioinformatics into their classrooms.

Morgan, William, (2017), "The NIBLSE Network", Fifth Biannual Undergraduate Bioinformatics Education Conference Program, : Latrobe, Pennsylvania, April, . Cited by:
Jenkins, Kristin, Donovan, Sam, LaMar, Drew, Hamerlinck, Gabriela, Orndorf, Hayley, (2017), "Making the Most of Models", National Association of Biology Teachers 2017 Annual Conference, : St. Louis, MO, November, . Cited by:
Donovan, Sam, Hale, Alison, Monfils, Anna, Orndorf, Hayley, (2017), "Designing undergraduate biology curricula to teach skills and knowledge for data-intensive environmental research", ESA 2017 Annual Meeting, : Portland, OR, August, (DOI: 10.25334/Q4HW9C). Cited by:
Jenkins, Kristin, (2016), "Modeling for Understanding: An authentic scientific experience in the undergraduate biology classroom", Biology Department Seminar Series, : Georgetown, Washington, DC, September, . Cited by:

Models are an integral part of the scientific process used to represent ideas, solve problems, predict outcomes, and test theories. Modeling involves a broad set of skills and approaches, including quantitative reasoning. Students are exposed to models throughout their education, but may not understand the role of modeling in the scientific process or how to use models to increase their content knowledge. The Quantitative Undergraduate Biology Education (QUBES) project has been supporting a working group exploring how this key scientific practice be more effectively used in undergraduate biology education.

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