7,484 research outputs found

    Integrating Computational Thinking into Information Systems and Other Curricula

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    Computational thinking (CT) is a fundamental skill needed to function in modern society. Despite widespread use of computers as productivity tools, existing curricula in information systems (IS) and other disciplines have not fully embraced CT concepts and skills. Increasing cross-disciplinary integration of CT into these curricula can help develop studentsā€™ problem-solving ability and provide educators with useful resources. Our collaborative initiative, named the Living in the Knowledge Society (LIKES) community building project, supports the integration of CT into college-level curricula by building a community of scholars and educators who will define the way to make systemic changes in how computing and IT concepts are taught and applied in both computing and other fields, thus better preparing the next-generation Knowledge Society builders. We describe the workshops, community-building activities, outcomes achieved, and case studies of developing teaching modules, curriculum guidelines, and teacher adoption strategies. Our work should benefit educators interested in integrating CT in their curricula, computing researchers interested in collaborating with other domain experts, and current students who aspire to become educators

    Changes in studentsā€™ mental models from computational modeling of gene regulatory networks

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    Background: Computational modeling is an increasingly common practice for disciplinary experts and therefore necessitates integration into science curricula. Computational models afford an opportunity for students to investigate the dynamics of biological systems, but there is significant gap in our knowledge of how these activities impact student knowledge of the structures, relationships, and dynamics of the system. We investigated how a computational modeling activity affected introductory biology studentsā€™ mental models of a prokaryotic gene regulatory system (lac operon) by analyzing conceptual models created before and after the activity. Results: Studentsā€™ pre-lesson conceptual models consisted of provided, system-general structures (e.g., activator, repressor) connected with predominantly incorrect relationships, representing an incomplete mental model of gene regulation. Studentsā€™ post-lesson conceptual models included more context-specific structures (e.g., cAMP, lac repressor) and increased in total number of structures and relationships. Student conceptual models also included higher quality relationships among structures, indicating they learned about these context-specific structures through integration with their expanding mental model rather than in isolation. Conclusions: Student mental models meshed structures in a manner indicative of knowledge accretion while they were productively re-constructing their understanding of gene regulation. Conceptual models can inform instructors about how students are relating system structures and whether students are developing more sophisticated models of system-general and system-specific dynamics

    The Need for Research-Grade Systems Modeling Technologies for Life Science Education

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    The coronavirus disease 2019 (COVID-19) pandemic not only challenged deeply-rooted daily patterns but also put a spotlight on the role of computational modeling in science and society. Amid the impromptu upheaval of in-person education across the world, this article aims to articulate the need to train students in computational and systems biology using research-grade technologies. ... Life sciences education needs multiple technical infrastructures explicitly designed to support this fieldā€™s vast computational needs. Developing and sustaining effective, scientifically authentic educational technologies is not easy. It requires expertise in software development and the scientific domain as well as in education and education research. Discipline-based education research (DBER) is an emerging field defined as ā€˜an empirical approach to investigating learning and teaching that is informed by an expert understanding of (STEM) disciplinary knowledge and practiceā€™ [14]. In life sciences education, DBER scientists, in particular, are focused on the integration of systems thinking concepts, computational modeling, and the use of new technologies. DBER scientists are exquisitely positioned to partner with computational systems biologists to increase the ease-of-use of existing, scientifically authentic technologies for postsecondary, secondary, and even primary educational purposes. They are also well-placed to design new research-grade technologies for life sciences education, and thus should be tasked with not only the intersection of deep disciplinary expertise and education but also codeveloping new technologies using the same tools and approaches as scientists to foster authentic competencies

    Nanoinformatics: developing new computing applications for nanomedicine

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    Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended ?nanotype? to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others

    Integrating Emerging Areas of Nursing Science into PhD Programs

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    The Council for the Advancement of Nursing Science aims to ā€œfacilitate and recognize life-long nursing science career developmentā€ as an important part of its mission. In light of fast-paced advances in science and technology that are inspiring new questions and methods of investigation in the health sciences, the Council for the Advancement of Nursing Science convened the Idea Festival for Nursing Science Education and appointed the Idea Festival Advisory Committee to stimulate dialogue about linking PhD education with a renewed vision for preparation of the next generation of nursing scientists. Building on the 2010 American Association of Colleges of Nursing Position Statement ā€œThe Research-Focused Doctoral Program in Nursing: Pathways to Excellence,ā€ Idea Festival Advisory Committee members focused on emerging areas of science and technology that impact the ability of research-focused doctoral programs to prepare graduates for competitive and sustained programs of nursing research using scientific advances in emerging areas of science and technology. The purpose of this article is to describe the educational and scientific contexts for the Idea Festival, which will serve as the foundation for recommendations for incorporating emerging areas of science and technology into research-focused doctoral programs in nursing

    Toward Integration: From Quantitative Biology to Mathbio-Biomath?

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    In response to the call of BIO2010 for integrating quantitative skills into undergraduate biology education, 30 Howard Hughes Medical Institute (HHMI) Program Directors at the 2006 HHMI Program Directors Meeting established a consortium to investigate, implement, develop, and disseminate best practices resulting from the integration of math and biology. With the assistance of an HHMI-funded mini-grant, led by Karl Joplin of East Tennessee State University, and support in institutional HHMI grants at Emory and University of Delaware, these institutions held a series of summer institutes and workshops to document progress toward and address the challenges of implementing a more quantitative approach to undergraduate biology education. This report summarizes the results of the four summer institutes (2007ā€“2010). The group developed four draft white papers, a wiki site, and a listserv. One major outcome of these meetings is this issue of CBEā€”Life Sciences Education, which resulted from proposals at our 2008 meeting and a January 2009 planning session. Many of the papers in this issue emerged from or were influenced by these meetings

    LIKES: Educating the Next Generation of Knowledge Society Builders

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    Although information technology (IT) is used extensively in the education of all disciplines, the computing-related fields are facing tremendous challenges, such as declining student enrollment and a lack of representation from minorities and women. Strengthening the connection between computing and other fields could help instructors to integrate IT in their teaching and to support the learning of students, who will become the next generation of Knowledge Society builders. Presently, this connection is weak due to the lack of interdisciplinary collaboration and mutual understanding among faculty in computing and other fields. Our ongoing effort entitled ā€œLiving in the KnowlEdge Society (LIKES) Community Building Projectā€ aims to build a community that will define a socially-relevant way to make systemic changes in how computing and IT concepts are taught and applied in both computing and other fields. In this paper, we review previous efforts in this area and summarize our projectā€™s achievements and lessons learned. We also provide recommendations on integrating IT into other curricula and on strengthening interdisciplinary collaborations
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