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In Proceedings of the 2014 IEEE/ACM joint conference on digital libraries (JCDL) (pp. The ups and downs of knowledge infrastructures in science: Implications for data management. International Journal on Digital Libraries, 16( 3–4), 207– 227. Knowledge infrastructures in science: Data, diversity, and digital libraries. Proceedings of the Association for Information Science and Technology, 53, 1– 10. The durability and fragility of knowledge infrastructures: Lessons learned from astronomy. Los Angeles, CA: University of California. Our knowledge of knowledge infrastructures: Lessons learned and future directions (p. Big data, little data, no data: Scholarship in the networked world, Cambridge, MA: MIT Press. Computer Supported Cooperative Work, 15( 4), 359– 383. What can studies of e‐learning teach us about collaboration in e‐research? Some findings from digital library studies. From Gutenberg to the global information infrastructure: Access to information in the networked world, Cambridge, MA: MIT Press. Computer Supported Cooperative Work, 22( 4–6), 373– 423. Reflections on 25 years of ethnography in CSCW. Research note: From co‐location to co‐presence: Shifts in the use of ethnography for the study of knowledge. Disentangling knowledge production and data production.
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In Proceedings of the 15th participatory design conference: Full papers (Vol. Data care and its politics: Designing for local collective data management as a neglected thing.
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ATLAS.ti Scientific Software Development GmbH. The qualitative data analysis and research software (Version 8). Washington, DC: National Science Foundation. Revolutionizing science and engineering through cyberinfrastructure: Report of the national science foundation blue‐ribbon panel on cyberinfrastructure (p.
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We reflect on continuity over generations of students and staff, transitions between grants, transfer of legacy data between software tools, research methods, and the role of professional data managers in the social sciences. This article reflects on the social, technical, organizational, economic, and policy challenges the team has encountered in creating new knowledge from data old and new. Edwards's model of “making global data”-collecting signals via consistent methods, technologies, and policies-to “make data global”-comparing and integrating those data, the research team has managed and exploited these data as a collaborative resource. By emulating the “team science” approaches of the scientists studied, the UCLA Center for Knowledge Infrastructures accumulated a comprehensive collection of qualitative data about how scientists generate, manage, use, and reuse data across domains. All rights reserved.A 5‐year project to study scientific data uses in geography, starting in 1999, evolved into 20 years of research on data practices in sensor networks, environmental sciences, biology, seismology, undersea science, biomedicine, astronomy, and other fields. This novel virtual didactic method may be used in non-surgical clerkships as well.ĬOVID-19 Innovation in medical education Medical student clerkships Surgical education Undergraduate medical education Virtual learning.Ĭopyright © 2021 Elsevier Inc. Medical students regarded SET QD as impactful for shelf exam preparation, clinical preparation, and long-term retention of the material. 3) Virtual Accessibility (sub-themes: alleviating time constraints, and mitigating life-stressors). 2) Experienced Educator (subtheme: transformational teaching). There are three themes and eight subthemes that emerged: 1) The SET QD Framework (sub-themes: questions as learning opportunities interleaving notable clinical scenarios team learning accountability). Audio recordings were transcribed verbatim and the Atlas.Ti software was used to manage the thematic analysis. In this qualitative study using grounded theory, we conducted purposive sampling and used 23 in-depth semi-structured interviews. The current study aims to: 1) describe third-year medical students' experiences with the novel Shelf-Exam-Type Question Didactics (SET QD) before (in-person) and during (virtual) COVID-19.
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The COVID-19 pandemic brings unforeseen challenges in medical education.