Predicting the impact of scientific concepts using full‐text features

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134425/1/asi23612.pd

Scholarly Collaboration In Engineering Education: From Big-Data Scientometrics To User-Centered Software Design

Engineering education research has grown into a flourishing community with an-ever increasing number of publications and scholars. However, recent studies show that a significant amount of engineering education knowledge retains a clear disciplinary orientation. If the gaps in scholarly collaboration continue to be prevalent within the entire community, it will become increasingly difficult to sustain community memory. This will eventually inhibit the propagation of innovations and slow the movement of research findings into practice. This dissertation studies scholarly collaboration in the engineering education research community. It provides a clear characterization of collaboration problems and proposes potential solutions. The dissertation is composed of four studies. First, the dissertation recognizes gaps in scholarly collaboration in the engineering education research community. To achieve this goal, a bibliometric analysis based on 24,172 academic articles was performed to describe the anatomy of collaboration patterns. Second, the dissertation reviewed existing technologies that enhance communication and collaboration in engineering and science. This review elaborated and compared features in 12 popular social research network sites to examine how these features support scholarly communication and collaboration. Third, this dissertation attempted to understand engineering education scholars‟ behaviors and needs related to scholarly collaboration. A grounded theory study was conducted to investigate engineering education scholars‟ behaviors in developing collaboration and their technology usage. Finally, a user-centered software design was proposed as a technological solution that addressed community collaboration needs. Results show that the engineering education research community is at its early stage of forming a small world network relying primarily on a small number of key scholars in the community. Scholars‟ disciplinary background, research areas, and geographical locations are factors that affect scholarly collaboration. To facilitate scholarly communication and collaboration, social research network sites started to be adopted by scholars in various disciplines. However, engineering education scholars still prefer face-to-face interactions, emails, and phone calls for connecting and collaborating with other scholars. Instead of connecting to other scholars online, the present study shows that scholars develop new connections and maintain existing connections mainly by attending academic conferences. Some of these connections may eventually develop into collaborative relationships. Therefore, one way to increase scholarly collaboration in engineering education is to help scholars better network with others during conferences. A new mobile/web application is designed in this dissertation to meet this user need. The diffusion of innovation theory and the small world network model suggest that a well-connected community has real advantages in disseminating information quickly and broadly among its members. It allows research innovations to produce greater impacts and to reach a broader range of audiences. It can also close the gap between scholars with different disciplinary backgrounds. This dissertation contributes to enhancing community awareness of the overall collaboration status in engineering education research. It informs policy making on how to improve collaboration and helps individual scientists recognize potential collaboration opportunities. It also guides the future development of communication and collaboration tools used in engineering education research

The Effect of Scientific Collaboration on CSCW Research: A Scientometric Study

The structure and evolution of a scientific research community can be quantitatively assessed taking into account the interactions between scientific agents dispersed geographically. In the recent years, CSCW has stabilized as a cross-disciplinary field suffering significant changes in its core structure, and there is limited understanding about the factors influencing the nature and progress of collaborative computing research. In this paper, we measure the correlation between a set of features related to the influence of collaboration types on the number of citations as well as the geographical distribution of the accumulated contribution to the CSCW literature. Overall, our work can represent a starting point to demonstrate how the study of scientific collaboration can partly explain the variations in the number of citations, frequency of papers, and topics addressed

Co-authorship, Homophily, and Scholarly Influence in Information Systems Research

Information Systems (IS) researchers have increasingly focused attention on understanding the identity of our field (Hirschheim & Klein 2003; Lyytinen & King 2004). One facet of any discipline’s identity is the social aspect of how its scholars actually conduct their work (DeSanctis 2003), which is formally labeled as the study of sociology of science. Contributing to this tradition of work, we empirically examine scholarly influence (Acedo et al., 2006); scientific collaboration, including metrics that capture the prevalence of c-oauthored work; antecedents to co-authorship; and the effect of co-authorship on subsequent citations. Based on analyzing five leading IS journals for a period of seven years, we found that co-authored papers have become increasingly common in leading IS journals and that co-authoring continues to be more prevalent in journals published in North America compared to European journals. Moreover, we found significant effects of homophily related to gender, homophily/proximity, and geography. IS scholars worldwide exhibit a stronger preference for collaborating with co-authors of the same sex and those who attended the same PhD program than one would expect by chance. We also examined differences among journals and found some intriguing results for the effect of co-authorship on citations. Overall, we found evidence that the number of co-authors was positively related to citations although there was some variance across journals. These findings point to a need for more research to better understand both the processes of collaboration and the drivers and downstream benefits associated with it

Learning within Digital Media: Investigating the Relationships Between Student Citation Networks, Assignment Structures, and Learning Outcomes

Students are comfortable sharing digital content with others, yet the effect of sharing of digital media for learning remains largely unexplored. Building on research in social network analysis and learning analytics, this research explores the use and sharing of digital media in learning activities, analyzing the effects of the design of the learning activities on the resulting networks of students and their cited resources, and exploring relationships between attributes of these citation networks and students’ perceptions of the learning outcomes. Results suggest that the extent to which an assignment is well-structured and converges towards a single solution positively influences the density and clustering coefficient of the resulting citation network, and that these network measures in turn have a positive influence on students’ perceptions of learning from the assignment

The Interdependence of Scientists in the Era of Team Science: An Exploratory Study Using Temporal Network Analysis

How is the rise in team science and the emergence of the research group as the fundamental unit of organization of science affecting scientists’ opportunities to collaborate? Are the majority of scientists becoming dependent on a select subset of their peers to organize the intergroup collaborations that are becoming the norm in science? This dissertation set out to explore the evolving nature of scientists’ interdependence in team-based research environments. The research was motivated by the desire to reconcile emerging views on the organization of scientific collaboration with the theoretical and methodological tendencies to think about and study scientists as autonomous actors who negotiate collaboration in a dyadic manner. Complex Adaptive Social Systems served as the framework for understanding the dynamics involved in the formation of collaborative relationships. Temporal network analysis at the mesoscopic level was used to study the collaboration dynamics of a specific research community, in this case the genomic research community emerging around GenBank, the international nucleotide sequence databank. The investigation into the dynamics of the mesoscopic layer of a scientific collaboration networked revealed the following—(1) there is a prominent half-life to collaborative relationships; (2) the half-life can be used to construct weighted decay networks for extracting the group structure influencing collaboration; (3) scientists across all levels of status are becoming increasingly interdependent, with the qualification that interdependence is highly asymmetrical, and (4) the group structure is increasingly influential on the collaborative interactions of scientists. The results from this study advance theoretical and empirical understanding of scientific collaboration in team-based research environments and methodological approaches to studying temporal networks at the mesoscopic level. The findings also have implications for policy researchers interested in the career cycles of scientists and the maintenance and building of scientific capacity in research areas of national interest

Mapping bilateral information interests using the activity of Wikipedia editors

We live in a global village where electronic communication has eliminated the geographical barriers of information exchange. The road is now open to worldwide convergence of information interests, shared values, and understanding. Nevertheless, interests still vary between countries around the world. This raises important questions about what today's world map of in- formation interests actually looks like and what factors cause the barriers of information exchange between countries. To quantitatively construct a world map of information interests, we devise a scalable statistical model that identifies countries with similar information interests and measures the countries' bilateral similarities. From the similarities we connect countries in a global network and find that countries can be mapped into 18 clusters with similar information interests. Through regression we find that language and religion best explain the strength of the bilateral ties and formation of clusters. Our findings provide a quantitative basis for further studies to better understand the complex interplay between shared interests and conflict on a global scale. The methodology can also be extended to track changes over time and capture important trends in global information exchange.Comment: 11 pages, 3 figures in Palgrave Communications 1 (2015