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Sample records for bk960061 bioquest dqb-elpha

  1. Communities of Transformation and Their Work Scaling STEM Reform

    Science.gov (United States)

    Kezar, Adrianna; Gehrke, Sean

    2015-01-01

    This mixed-methods study examined four STEM communities (BioQUEST, Project Kaleidoscope, the POGIL Project, and SENCER) in order to better understand the roles of these communities in advancing the goals of scaling STEM education reform. The project explored three key questions: (1) How do members and leaders of communities of practice (CoPs1)…

  2. Mathematical manipulative models: in defense of "beanbag biology".

    Science.gov (United States)

    Jungck, John R; Gaff, Holly; Weisstein, Anton E

    2010-01-01

    Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process-1) use of physical manipulatives, 2) interactive exploration of computer simulations, 3) derivation of mathematical relationships from core principles, and 4) analysis of real data sets-we demonstrate a process that we have shared in biological faculty development workshops led by staff from the BioQUEST Curriculum Consortium over the past 24 yr. We built this approach based upon a broad survey of literature in mathematical educational research that has convincingly demonstrated the utility of multiple models that involve physical, kinesthetic learning to actual data and interactive simulations. Two projects that use this approach are introduced: The Biological Excel Simulations and Tools in Exploratory, Experiential Mathematics (ESTEEM) Project (http://bioquest.org/esteem) and Numerical Undergraduate Mathematical Biology Education (NUMB3R5 COUNT; http://bioquest.org/numberscount). Examples here emphasize genetics, ecology, population biology, photosynthesis, cancer, and epidemiology. Mathematical manipulative models help learners break through prior fears to develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology and enhance the diversity of quantitative biology education.

  3. Soil bioremediation at CFB Trenton: evaluation of bioremediation processes

    International Nuclear Information System (INIS)

    Ouellette, L.; Cathum, S.; Avotins, J.; Kokars, V.; Cooper, D.

    1996-01-01

    Bioremediation processes and their application in the cleanup of contaminated soil, were discussed. The petroleum contaminated soil at CFB Trenton, was evaluated to determine which bioremediation process or combination of processes would be most effective. The following processes were considered: (1) white hot fungus, (2) Daramend proprietary process, (3) composting, (4) bioquest proprietary bioremediation processes, (5) Hobbs and Millar proprietary bioremediation process, and (6) farming. A brief summary of each of these options was included. The project was also used as an opportunity to train Latvian and Ukrainian specialists in Canadian field techniques and laboratory analyses. Preliminary data indicated that bioremediation is a viable method for treatment of contaminated soil. 18 refs., 3 figs

  4. Bioinformatics education dissemination with an evolutionary problem solving perspective.

    Science.gov (United States)

    Jungck, John R; Donovan, Samuel S; Weisstein, Anton E; Khiripet, Noppadon; Everse, Stephen J

    2010-11-01

    Bioinformatics is central to biology education in the 21st century. With the generation of terabytes of data per day, the application of computer-based tools to stored and distributed data is fundamentally changing research and its application to problems in medicine, agriculture, conservation and forensics. In light of this 'information revolution,' undergraduate biology curricula must be redesigned to prepare the next generation of informed citizens as well as those who will pursue careers in the life sciences. The BEDROCK initiative (Bioinformatics Education Dissemination: Reaching Out, Connecting and Knitting together) has fostered an international community of bioinformatics educators. The initiative's goals are to: (i) Identify and support faculty who can take leadership roles in bioinformatics education; (ii) Highlight and distribute innovative approaches to incorporating evolutionary bioinformatics data and techniques throughout undergraduate education; (iii) Establish mechanisms for the broad dissemination of bioinformatics resource materials and teaching models; (iv) Emphasize phylogenetic thinking and problem solving; and (v) Develop and publish new software tools to help students develop and test evolutionary hypotheses. Since 2002, BEDROCK has offered more than 50 faculty workshops around the world, published many resources and supported an environment for developing and sharing bioinformatics education approaches. The BEDROCK initiative builds on the established pedagogical philosophy and academic community of the BioQUEST Curriculum Consortium to assemble the diverse intellectual and human resources required to sustain an international reform effort in undergraduate bioinformatics education.

  5. Mathematics and evolutionary biology make bioinformatics education comprehensible

    Science.gov (United States)

    Weisstein, Anton E.

    2013-01-01

    The patterns of variation within a molecular sequence data set result from the interplay between population genetic, molecular evolutionary and macroevolutionary processes—the standard purview of evolutionary biologists. Elucidating these patterns, particularly for large data sets, requires an understanding of the structure, assumptions and limitations of the algorithms used by bioinformatics software—the domain of mathematicians and computer scientists. As a result, bioinformatics often suffers a ‘two-culture’ problem because of the lack of broad overlapping expertise between these two groups. Collaboration among specialists in different fields has greatly mitigated this problem among active bioinformaticians. However, science education researchers report that much of bioinformatics education does little to bridge the cultural divide, the curriculum too focused on solving narrow problems (e.g. interpreting pre-built phylogenetic trees) rather than on exploring broader ones (e.g. exploring alternative phylogenetic strategies for different kinds of data sets). Herein, we present an introduction to the mathematics of tree enumeration, tree construction, split decomposition and sequence alignment. We also introduce off-line downloadable software tools developed by the BioQUEST Curriculum Consortium to help students learn how to interpret and critically evaluate the results of standard bioinformatics analyses. PMID:23821621

  6. Mathematics and evolutionary biology make bioinformatics education comprehensible.

    Science.gov (United States)

    Jungck, John R; Weisstein, Anton E

    2013-09-01

    The patterns of variation within a molecular sequence data set result from the interplay between population genetic, molecular evolutionary and macroevolutionary processes-the standard purview of evolutionary biologists. Elucidating these patterns, particularly for large data sets, requires an understanding of the structure, assumptions and limitations of the algorithms used by bioinformatics software-the domain of mathematicians and computer scientists. As a result, bioinformatics often suffers a 'two-culture' problem because of the lack of broad overlapping expertise between these two groups. Collaboration among specialists in different fields has greatly mitigated this problem among active bioinformaticians. However, science education researchers report that much of bioinformatics education does little to bridge the cultural divide, the curriculum too focused on solving narrow problems (e.g. interpreting pre-built phylogenetic trees) rather than on exploring broader ones (e.g. exploring alternative phylogenetic strategies for different kinds of data sets). Herein, we present an introduction to the mathematics of tree enumeration, tree construction, split decomposition and sequence alignment. We also introduce off-line downloadable software tools developed by the BioQUEST Curriculum Consortium to help students learn how to interpret and critically evaluate the results of standard bioinformatics analyses.