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Scaffolding in Academic SettingsDeveloping Team Science Capacity at a Technological UniversityDr. Kathleen E Halvorsen, Michigan Technological UniversityMany universities struggle to develop team science capacity finding it difficult to bridge disciplinary and departmental boundaries. This paper focuses on describing how Michigan Technological University developed inter/transdisciplinary scientific research skills and networks in the area of environmental sustainability. This development started with a few key faculty across the university interested in developing interdisciplinary environmental sustainability research. A National Science Foundation IGERT grant on sustainability spurred the faculty to develop research projects, co-advise graduate students, create a cross-university graduate certificate, and put in place a research institute to connect faculty and facilitate interdisciplinary research. This institute was critical in identifying some funding opportunities, helping develop interdisciplinary teams to pursue them, and assisting with proposal development. This in turn led to successful funding awards from multiple federal science agencies. As a core of environmental sustainability researchers across social, natural, engineering, and computational sciences worked together to pursue various proposals and carry out funded grants, a core of experienced senior researchers developed skills in developing and managing inter/transdisciplinary scientific teams. Success in this research focus eventually began to attract more, higher caliber faculty and students in this area facilitated by a serious of university-wide faculty hiring initiatives in sustainability-related fields. The result has been the development of a "deep bench" of scientists skilled in working together across boundaries who can trade-off leadership responsibilities and pivot to take advantage of new opportunities. It has institutionalized norms and training (formal and informal) for new faculty and students. At this point in time, Michigan Tech is poised to expand this team science skill base to develop new areas of research going beyond the initial environmental sustainability core. SciTS Presentation: Developing team science capacity at a technological university
365: A Year Implementing a Team Science Movement in a British UniversityMs. Ruth Norris, The University of Manchester, UK; Dr. Claire Smith, The University of Manchester; Dr. Amanda Lamb, The University of Manchester; Ms. Charlotte Stockton-Powdrell, The University of Manchester; Ms. Rachel Chown, The University of ManchesterThe author and co-authors have informally applied components of the Team Science (TS) model to research at the University of Manchester for 10 years. Their particpation in SciTS 2018 was the catalyst for 365 days of change: empowering a knowledge-rich team with the toolkit required to formalize, spread and operationalize a TS approach across the University of Manchester, with the objectives of:
The approach combines complementary methods to proliferate and embed TS in the research ecosystem:
Development of a Research Management Development framework In conclusion, the journey to TS implementation across a British university was catalysed by attendance at the SciTS conference 2018. This initiative has begun at pace using several complementary activities and workstreams,and has gained significant enthusiasm and traction from key senior academic and operational leadership figures; plus interest from external partners across the United Kingdom for adoption. The depth, breadth and sustainability of this movement, and its positive effect on research, will depend on advocacy and sponsorship; operational and cultural change; and continued application of theory and methods to practice.
Assessing the Propensity to Collaborate in the Life SciencesDr. Kyuseon Lee, University of Minnesota; Dr. Steve Miller, University of Minnesota; Dr. Philip G. Pardey, University of MinnesotaCollaboration among researchers is increasing, but among all possible pairs of researchers few actually work together. It is thus natural to ask what information signals do researchers use in selecting research partners from among a large pool of potential collaborators. This study has addressed that question for life sciences researchers focusing on three particular types of signals: perceived research productivity, knowledge complementarity, and professional familiarity. We investigate the collaboration consequences of these signals by using academic publication data published by life sciences faculty at the University of Minnesota (UMN) from 1999 to 2014, focusing on papers in which all of the authors are affiliated with UMN. We have found perceived research productivity is positively associated with the initiation of first collaboration while complementary knowledge is not. For continuing collaborations, however, knowledge complementarity becomes significant as well as the recency of first collaboration and the frequency of past collaborations. While complementarity is noted as a key driver of repetitive collaborations, researchers are more likely to collaborate with coauthors who have moderate differences in research profile. This suggests that the factors researchers consider when choosing coauthors vary with respect to the types of collaboration. This study contributes to the empirical literature on research team formation and to university administrators seeking to promote more collaboration among researchers.
Societal Impact of Research on the Complexity of Language in FranceDr. Audrey Mazur-Palandre, University of Lyon; Dr. Gerald Niccolai, CNRS: Centre National de la Recherche Scientifique; Dr. François Pellegrino, CNRS: Centre National de la Recherche Scientifique; Dr. Kristine Lund, CNRS: Centre National de la Recherche ScientifiqueIn 2010, the Advanced Studies on LANguage complexity (ASLAN) “Laboratory of Excellence” obtained funding for ten years. Primarily mobilizing the laboratories DDL (Dynamics of Language) and ICAR (Interactions, Corpora, Learning, Representations), it has now been one of the 12 LabEx funded by the University of Lyon during 2011-2019. By considering language as a complex dynamic system, ASLAN proposes to examine all facets of language use and acquisition, as well as language diversity and history. This approach addresses all language components (from phonemes to gestures, from grammar to interaction) as well as how biological, cognitive and social factors and language reciprocally influence each other. Although public sector researchers who willingly contribute to the resolution of societal issues is not new, ASLAN’s goal is to develop a collective approach, still lacking in the mid 2000s in France, especially in the Human and Social Sciences (HSS). To meet this challenge, ASLAN put together a policy of innovation, dissemination and exploitation of research results in order to respond institutionally to societal issues. In addition to three scientific axes structuring research activities, ASLAN has also included three societal challenges, two transversal scientific approaches, and axes dedicated to training, inreach, and outreach activities. A team responsible for the communication and enhancement of ASLAN was set up to rethink and increase the societal value of ASLAN’s perimeter, while working closely within the scientific axes and approaches. Since 2012, ASLAN has developed a program aimed at facilitating multi-inter-transdisciplinary collaboration as well as real expertise in adding societal value to research results in language sciences, educational sciences and psychology. We have done this by reflecting on the concepts of inreach, outreach, and dissemination of research in HSS (Ogilivie Hendren & Ku, forthcoming). Our experience has led us to redefine the value of HSS research. This was facilitated by our decision to give responsibility for the development and animation of inreach, outreach, and dissemination to staff who are trained and practicing researchers (Scholz, 2017). This dual position - researcher and in charge of the development of inreach, outreach, and dissemination – allows for excellent knowledge of ASLAN’s disciplinary fields. Such knowledge enables a quick understanding of research projects, and ease in identifying partnerships and new academic possibilities. Finally, awareness of different stakeholders’ constraints (e.g. difference in the public and private sector timescales) facilitates finding solutions that satisfy different partners. In light of this background, our presentation will have a twofold objective. We will (1) illustrate that what is defined by societal value is extremely rich and goes beyond the creation of market value, especially in HSS and (2) show examples from ASLAN that can be transferred or adapted to other societal issues in HSS research. Our work will soon be available in the form of a white paper. References: Ogilvie Hendren, C. & Ku, S. (forthcoming). New Directions Spotlight: The Interdisciplinary Executive Scientist. Scholz, R.W. (2017). The Normative Dimension in Transdisciplinarity, Transition Management, and Transformation Sciences: New Roles of Science and Universities in Sustainable Transitioning. Sustainability, 9, 991.
Deep Knowledge Integration Across Disciplines: The EMBeRS MethodDr. Deana Pennington, University of Texas at El Paso; Dr. Kate Thompson, Griffith University; Dr. Shirley Vincent, Vincent Evaluation Consulting, LLC; Dr. David Gosselin, University of Nebraska at Lincoln
The EMBeRS project (Employing Model-Based Reasoning in Socio-Environmental Synthesis) is investigating the challenge of deep knowledge integration across disciplines as a learning problem. Team members must learn enough about each other’s research and the basic concepts that are fundamental to understanding it to be able to generate an internal mental model of each colleague’s This presentation will summarize the EMBeRS method for learning across disciplines to purposefully identify potential conceptual linkages between team members and converge through time on a shared mental model of the problem. The presentation will briefly summarize learning theories on which the method is based; provide a heuristic model for practices that facilitate learning in science teams derived from synthesizing those theories; describe the PhD workshops that are being used to test the EMBeRS method; and present results from qualitative and quantitative analysis of data collected during the workshops. Results show promise for development of a set of generic activities that can be used in interdisciplinary science teams to intentionally and purposefully integrate deep knowledge across disciplines, leading to development of a shared mental model of the problem and a path towards identifying a shared vision of synergistic research. SciTS Presentation: Deep Knowledge Integration Across Disciplines: The EMBeRS Method |