Emerging and scripted roles in computer-supported collaborative learning

Emerging and scripted roles pose an intriguing approach to analysing and facilitating CSCL. The concept of emerging roles provides a perspective on how learners structure and self-regulate their CSCL processes. Emerging roles appear to be dynamic over longer periods of time in relation to learners’ advancing knowledge, but are often unequally distributed in ad hoc CSCL settings, e.g. a learner being the ‘typist’ and another being the ‘thinker’. Empirical findings show that learners benefit from structuring or scripting CSCL. Scripts can specify roles and facilitate role rotation for learners to equally engage in relevant learning roles and activities. Scripted roles can, however, collide with emerging roles and therefore need to be carefully attuned to the advancing capabilities of the learners

Static and Dynamic Aspects of Scientific Collaboration Networks

Collaboration networks arise when we map the connections between scientists which are formed through joint publications. These networks thus display the social structure of academia, and also allow conclusions about the structure of scientific knowledge. Using the computer science publication database DBLP, we compile relations between authors and publications as graphs and proceed with examining and quantifying collaborative relations with graph-based methods. We review standard properties of the network and rank authors and publications by centrality. Additionally, we detect communities with modularity-based clustering and compare the resulting clusters to a ground-truth based on conferences and thus topical similarity. In a second part, we are the first to combine DBLP network data with data from the Dagstuhl Seminars: We investigate whether seminars of this kind, as social and academic events designed to connect researchers, leave a visible track in the structure of the collaboration network. Our results suggest that such single events are not influential enough to change the network structure significantly. However, the network structure seems to influence a participant's decision to accept or decline an invitation.Comment: ASONAM 2012: IEEE/ACM International Conference on Advances in Social Networks Analysis and Minin

SPECTRUM-BASED AND COLLABORATIVE NETWORK TOPOLOGY ANALYSIS AND VISUALIZATION

Networks are of significant importance in many application domains, such as World Wide Web and social networks, which often embed rich topological information. Since network topology captures the organization of network nodes and links, studying net- work topology is very important to network analysis. In this dissertation, we study networks by analyzing their topology structure to explore community structure, the relationship among network members and links as well as their importance to the belonged communities. We provide new network visualization methods by studying network topology through two aspects: spectrum-based and collaborative visualiza- tion techniques. For the spectrum-based network visualization, we use eigenvalues and eigenvectors to express network topological features instead of using network datasets directly. We provide a visual analytics approach to analyze unsigned networks based on re- cent achievements on spectrum-based analysis techniques which utilize the features of node distribution and coordinates in the high dimensional spectral space. To assist the interactive exploration of network topologies, we have designed network visual- ization and interactive analysis methods allowing users to explore the global topology structure. Further, to address the question of real-life applications involving of both positive and negative relationships, we present a spectral analysis framework to study both signed and unsigned networks. Our framework concentrates on two problems of net- work analysis - what are the important spectral patterns and how to use them to study signed networks. Based on the framework, we present visual analysis methods, which guide the selection of k-dimensional spectral space and interactive exploration of network topology. With the increasing complexity and volume of dynamic networks, it is important to adopt strategies of joint decision-making through developing collaborative visualiza- tion approaches. Thus, we design and develop a collaborative detection mechanism with matrix visualization for complex intrusion detection applications. We establish a set of collaboration guidelines for team coordination with distributed visualization tools. We apply them to generate a prototype system with interactions that facilitates collaborative visual analysis. In order to evaluate the collaborative detection mechanism, a formal user study is presented. The user study monitored participants to collaborate under co-located and distributed collaboration environments to tackle the problems of intrusion detection. We have observed participants’ behaviors and collected their performances from the aspects of coordination and communication. Based on the results, we conclude several coordination strategies and summarize the values of communication for collaborative visualization. Our visualization methods have been demonstrated to be efficient topology explo- ration with both synthetic and real-life datasets in spectrum-based and collaborative exploration. We believe that our methods can provide useful information for future design and development of network topology visualization system

Visual network storytelling

We love networks! Networks are powerful conceptual tools, encapsulating in a single item multiple affordances for computation (networks as graphs), visualization (networks as maps) and manipulation of data (networks as interfaces). In the field of mathematics, graph theory has been around since Euler’s walk on Königsberg’s bridges (Euler 1736). But it is not until the end of the last century that networks acquired a multidisciplinary popularity. Graph computation is certainly powerful, but it is also very demanding and for many years its advantages remained the privilege of scholars with solid mathematical fundamentals. In the last few decades, however, networks acquired a new set of affordances and reached a larger audience, thanks to the growing availability of tools to design them. Drawn on paper or screen, networks became easier to handle and obtained properties that calculation could not express. Far from being merely aesthetic, the graphical representation of networks has an intrinsic hermeneutic value. Networks can become maps and be read as such. Combining the computation power of graphs with the visual expressivity of maps and the interactivity of computer interface, networks can be used in Exploratory Data Analysis (Tukey, 1977). Navigating through data becomes so fluid that zooming in on a single data-point and out to a landscape of a million traces is just a click away. Increasingly specialized software has been designed to support the exploration of network data. Tools like Pajek (vlado.fmf.uni-lj.si/pub/networks/pajek), NetDraw (sites.google.com/site/ netdrawsoftware), Ucinet (www.analytictech.com/ucinet), Guess (graphexploration.cond.org) and more recently Gephi (gephi.org) have progressively smoothed out the difficulties of graph mathematics, turning a complex mathematical formalism into a more user-friendly point-and-click interface (1) . If visual exploration of networks can output to confirmatory statistics, what about sharing one network exploration with others? We developed Manylines (https://github.com/medialab/manylines), a tool allowing you to share the visual analysis of a network with a wide audience by publishing it on the web. With Manylines, you can not only easily publish a network on the web but also share its exploration by describing the network’s visual key findings. Through a set of examples, we will illustrate how the narrative opportunities of Manylines can contribute to the enunciation of a visual grammar of networks. (1) A simple look at the URLs of the subsequent tools reveals the efforts deployed to make network-manipulation tools user-friendly and thereby available to a larger public

Designing product-service systems for sustainability : a methodological exploration

Tese de mestrado. Engenharia de Serviços e Gestão. Faculdade de Engenharia. Universidade do Porto. 201

Emotions in Learning, Teaching, and Leadership: A Bibliometric Review of Asian Literature (1990–2018)

This study aims to map the Asian literature on emotions in learning, teaching, and leadership through a review of published research in Web of Science Core Collection. In all, 862 articles published between 1990 and 2018 were retrieved and analyzed. Bibliographic coupling of the countries, bibliographic coupling of the authors, co-occurrences of author keywords, bibliographic coupling of the journals, and bibliographic coupling of the institutions were extracted through bibliographic visualization methods. All the h-classics publications were also reviewed and categorized according to their topics. People’s Republic of China (Hong Kong), Israel, Turkey, and Cyprus are the countries with most relevant evidence. The top authors are found to be D.W Chan and M. Zembylas, while emotional intelligence, empathy, burnout, emotion, and self-efficacy have been the most frequently studied concepts. Teaching and Teacher Education and Journal of Educational Psychology are the journals with prominent pertinent influence. Education University of Hong Kong, Chinese University of Hong Kong, and Ben-Gurion University of the Negev are the institutions with the most notable influence. The current situation and research trends are discussed in the article

The “social” aspect of social-ecological systems : a critique of analytical frameworks and findings from a multisite study of coastal sustainability

The work described here was partly funded by the European Commission’s FP6 contract 036992.We evaluate whether society can adequately be conceptualized as a component of social-ecological systems, given social theory and the current outputs of systems-based research. A mounting critique from the social sciences posits that resilience theory has undertheorized social entities with the concept of social-ecological systems. We trace the way that use of the term has evolved, relating to social science theory. Scientometic and network analysis provide a wide range of empirical data about the origin, growth, and use of this term in academic literature. A content analysis of papers in Ecology and Society demonstrates a marked emphasis in research on institutions, economic incentives, land use, population, social networks, and social learning. These findings are supported by a review of systems science in 18 coastal assessments. This reveals that a systems-based conceptualization tends to limit the kinds of social science research favoring quantitative couplings of social and ecological components and downplaying interpretive traditions of social research. However, the concept of social-ecological systems remains relevant because of the central insights concerning the dynamic coupling between humans and the environment, and its salient critique about the need for multidisciplinary approaches to solve real world problems, drawing on heuristic devices. The findings of this study should lead to more circumspection about whether a systems approach warrants such claims to comprehensiveness. Further methodological advances are required for interdisciplinarity. Yet there is evidence that systems approaches remain highly productive and useful for considering certain social components such as land use and hybrid ecological networks. We clarify advantages and restrictions of utilizing such a concept, and propose a reformulation that supports engagement with wider traditions of research in the social sciences.Publisher PDFPeer reviewe

Psychosocial Stages of Symbolic Action in Social Media

Social media provides new capabilities for engaging in symbolic action through digital content and network structure. Most social media research assumes that people engage in similar symbolic actions regardless of their developmental maturity. Developmental psychology, however, argues that people are capable of different symbolic engagement and exhibit predictable social needs during different stages of life, suggesting that they may use social media in very different ways at different stages. This research note explores the implications of Erikson’s psychosocial theory on symbolic action using social media, and concludes that people are likely to use social media in fundamentally different ways, depending on their stage of psychosocial development. These conclusions have numerous implications for social media theory, research methodology, and practice

Examining the Effects of Discussion Strategies and Learner Interactions on Performance in Online Introductory Mathematics Courses: An Application of Learning Analytics

This dissertation study explored: 1) instructors’ use of discussion strategies that enhance meaningful learner interactions in online discussions and student performance, and 2) learners’ interaction patterns in online discussions that lead to better student performance in online introductory mathematics courses. In particular, the study applied a set of data mining techniques to a large-scale dataset automatically collected by the Canvas Learning Management System (LMS) for five consecutive years at a public university in the U.S., which included 2,869 students enrolled in 72 courses. First, the study found that the courses that posted more open-ended prompts, evaluated students’ discussion messages posted by students, used focused discussion settings (i.e., allowing a single response and replies to that response), and provided more elaborated feedback had higher students final grades than those which did not. Second, the results showed the instructors’ use of discussion strategies (discussion structures) influenced the quantity (volume of discussion), the breadth (distribution of participation throughout the discussion), and the quality of learner interactions (levels of knowledge construction) in online discussions. Lastly, the results also revealed that the students’ messages related to allocentric elaboration (i.e., taking other peers’ contributions in argumentive or evaluative ways) and application (i.e., application of new knowledge) showed the highest predictive value for their course performance. The findings from this study suggest that it is important to provide opportunities for learners to freely discuss course content, rather than creating a discussion task related to producing a correct answer, in introductory mathematics courses. Other findings reported in the study can also serve as guidance for instructors or instructional designers on how to design better online mathematics courses