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

Knowledge-Based Techniques for Scholarly Data Access: Towards Automatic Curation

Accessing up-to-date and quality scientific literature is a critical preliminary step in any research activity. Identifying relevant scholarly literature for the extents of a given task or application is, however a complex and time consuming activity. Despite the large number of tools developed over the years to support scholars in their literature surveying activity, such as Google Scholar, Microsoft Academic search, and others, the best way to access quality papers remains asking a domain expert who is actively involved in the field and knows research trends and directions. State of the art systems, in fact, either do not allow exploratory search activity, such as identifying the active research directions within a given topic, or do not offer proactive features, such as content recommendation, which are both critical to researchers. To overcome these limitations, we strongly advocate a paradigm shift in the development of scholarly data access tools: moving from traditional information retrieval and filtering tools towards automated agents able to make sense of the textual content of published papers and therefore monitor the state of the art. Building such a system is however a complex task that implies tackling non trivial problems in the fields of Natural Language Processing, Big Data Analysis, User Modelling, and Information Filtering. In this work, we introduce the concept of Automatic Curator System and present its fundamental components.openDottorato di ricerca in InformaticaopenDe Nart, Dari

From Social Networks to Publishing Platforms: A Review of the History and Scholarship of Academic Social Network Sites

Social network sites enable people to easily connect to and communicate with others. Following the success of generic platforms such as Facebook, a variety of online services launched during the mid 2000s in order to bring the benefits of online social networking to an academic audience. However, it is not clear whether these academic social network sites (ASNS) are primarily aligned with social networking or alternative publishing, and functionalities continue to change. Now ten years since the launch of the three main platforms which currently lead the market (Academia.edu, ResearchGate, and Mendeley), it is timely to review how and why ASNS are used. This paper discusses the history and definition of ASNS, before providing a comprehensive review of the empirical research related to ASNS to-date. Five main themes within the research literature are identified, including: the relationship of the platforms to Open Access publishing; metrics; interactions with others through the platforms; platform demographics and social structure; and user perspectives. Discussing the themes in the research both provides academics with a greater understanding of what ASNS can do and their limitations, and identifies gaps in the literature which would be valuable to explore in future research

Relational social recommendation: Application to the academic domain

This paper outlines RSR, a relational social recommendation approach applied to a social graph comprised of relational entity profiles. RSR uses information extraction and learning methods to obtain relational facts about persons of interest from the Web, and generates an associative entity-relation social network from their extracted personal profiles. As a case study, we consider the task of peer recommendation at scientific conferences. Given a social graph of scholars, RSR employs graph similarity measures to rank conference participants by their relatedness to a user. Unlike other recommender systems that perform social rankings, RSR provides the user with detailed supporting explanations in the form of relational connecting paths. In a set of user studies, we collected feedbacks from participants onsite of scientific conferences, pertaining to RSR quality of recommendations and explanations. The feedbacks indicate that users appreciate and benefit from RSR explainability features. The feedbacks further indicate on recommendation serendipity using RSR, having it recommend persons of interest who are not apriori known to the user, oftentimes exposing surprising inter-personal associations. Finally, we outline and assess potential gains in recommendation relevance and serendipity using path-based relational learning within RSR

Institutional Repositories and Academic Social Networks: Competition or Complement? A Study of Open Access Policy Compliance vs. ResearchGate Participation

INTRODUCTION The popularity of academic social networks like ResearchGate and Academia.edu indicates that scholars want to share their work, yet for universities with open access (OA) policies, these sites may be competing with institutional repositories (IRs) for content. This article seeks to reveal researcher practices, attitudes, and motivations around uploading their work to ResearchGate and complying with an institutional OA Policy through a study of faculty at the University of Rhode Island (URI). METHODS We conducted a population study to examine the participation by 558 full-time URI faculty members in the OA Policy and ResearchGate followed by a survey of 728 full-time URI faculty members about their participation in the two services. DISCUSSION The majority of URI faculty do not participate in the OA Policy or use ResearchGate. Authors’ primary motivations for participation are sharing their work more broadly and increasing its visibility and impact. Faculty who participate in ResearchGate are more likely to participate in the OA Policy, and vice versa. The fact that the OA Policy targets the author manuscript and not the final published article constitutes a significant barrier to participation. CONCLUSION Librarians should not view academic social networks as a threat to open access. Authors’ strong preference for sharing the final, published version of their articles provides support for calls to hasten the transition to a Gold OA publishing system. Misunderstandings about the OA Policy and copyright indicate a need for librarians to conduct greater education and outreach to authors about options for legally sharing articles

Cautious explorers generate more future academic impact

Some scientists are more likely to explore unfamiliar research topics while others tend to exploit existing ones. In previous work, correlations have been found between scientists' topic choices and their career performances. However, literature has yet to untangle the intricate interplay between scientific impact and research topic choices, where scientific exploration and exploitation intertwine. Here we study two metrics that gauge how frequently scientists switch topic areas and how large those jumps are, and discover that 'cautious explorers' who switch topics frequently but do so to 'close' domains have notably better future performance and can be identified at a remarkably early career stage. Cautious explorers who balance exploration and exploitation in their first four career years have up to 19% more citations per future paper. Our results suggest that the proposed metrics depict the scholarly traits of scientists throughout their careers and provide fresh insight, especially for nurturing junior scientists.Comment: 16 pages of main text and 94 pages of supplementary informatio