Browsing by Author "Kwon, Kyungbin"

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    Multimodal Data Analytics for Assessing Collaborative Interactions
    (International Society of the Learning Sciences (ISLS), 2020-06) Kim, Yanghee; D'Angelo, Cynthia; Cafaro, Francesco; Ochoa, Xavier; Espino, Danielle; Kline, Aaron; Hamilton, Eric; Lee, Seung; Butail, Sachit; Liu, Lichuan; Trajkova, Milka; Tscholl, Michael; Hwang, Jaejin; Lee, Sungchul; Kwon, Kyungbin; Human-Centered Computing, School of Informatics and Computing
    This symposium will discuss the current status of the research and development of multimodal data analytics (MDA) for the observation of collaboration. Five research groups will present their current work on MDA, each with a unique focus on different data sources and different approaches to the analysis and synthesis of multimodal data sets. A few themes emerge from these studies: i) the studies seek to examine collaborative behaviors as a process in ordinary settings, both formal and informal; ii) with MDA being in its early stage, manual and computational approaches are taken complementarily, also using human annotation as the ground truth for the computational approach; and iii) several different discipline-specific research and development lines contribute integrally to generating authentic measures of collaborative interactions in situ, making this line of research transdisciplinary.
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    Peer Collaborative Clinical Decision-Making in Virtual Reality Nursing Simulation
    (2023-05) Ngo, Thye Peng; Reising, Deanna L.; Draucker, Claire Burke; Barnes, Roxie; Kwon, Kyungbin
    In nursing education, it is common for students to collaborate and make decisions as a group in simulations. One of the vital nursing competencies is students’ ability to make sound clinical judgments and decision-making in simulation. Teamwork among students in simulation significantly affects their critical thinking and clinical reasoning. However, how students collaborate and make decisions in simulation is a complex phenomenon and not well studied and understood. In addition, most existing decision-making frameworks, such as Tanner’s Clinical Judgment Model and the National Council of State Boards of Nursing’s Clinical Judgment Measurement Model, focus solely on individual decision-making. Alternatively, teamwork and collaboration frameworks, such as TeamSTEPPS®, emphasize interprofessional collaboration rather than intraprofessional or peer-to-peer collaboration. Furthermore, peer collaboration and decision-making cannot be accurately measured without a theoretical framework. Because clinical decision-making in nursing practice is a complex process that involves peer collaboration, more research is needed to explore how nursing students collaborate and make decisions in simulation. This qualitative study comprises of a hybrid concept analysis and Charmaz’s constructivist grounded theory to explore prelicensure nursing student’s peer collaborative clinical decision-making (PCCDM). The concept analysis develops a comprehensive definition of PCCDM based on theoretical and empirical data. The grounded theory develops the theoretical framework that captures the process of PCCDM, which consists of the three major domains of group cognition, behavior, and emotion. These domains undergo the peer regulatory process of awareness, communication, and regulation within the individual and collaborative space at various simulation phases. Additionally, a thematic analysis further explores group emotion in PCCDM as the domain is the least studied in nursing simulation. This study provides the framework to support healthcare and nursing simulation involving peer collaboration and decision-making.