Bibliometric Indicators for Assessing the Quality of Scholarly Communications: A Case Study on International Journal of Cooperative Information Systems

This paper analyses various bibliometric dimensions of the journal literature such as authors’ productivity, geographical distribution, citation pattern, institution-wise distribution of articles, discipline-wise distributions of articles, productive institutions, Productivity Index (PI), Activity Index (AI), Domestic Collaborative Index (DCI) and International Collaborative Index (ICI) etc. It also explores the applicability of Lotka’s Inverse Square Law and Zipf’s Law to examine the observed rank – frequency pattern of Keywords and Subject Terms of Information Systems (IS) literature. To illustrate these bibliometric indicators pertinent information on the field of Information Systems (IS) collected from EBSCO database for the International Journal of Cooperative Information Systems (IJCIS). Results indicated that a high level of collaboration exists among the authors, USA occupies the dominant position in terms of high productive authors, institutions and tops the list with highest number of domestic collaboration. Authors’ productivity confirms to Lotka’s law and the Frequency distribution of both Subject Terms and Keywords in IJCIS journal literature follow Zipf’s distribution

Fund Finder: A case study of database-to-ontology mapping

The mapping between databases and ontologies is a basic problem when trying to "upgrade" deep web content to the semantic web. Our approach suggests the declarative definition of mappings as a way to achieve domain independency and reusability. A specific language (expressive enough to cover some real world mapping situations like lightly structured databases or not 1st normal form ones) is defined for this purpose. Along with this mapping description language, the ODEMapster processor is in charge of carrying out the effective instance data migration. We illustrate this by testing both the mappings definition and processor on a case study

Motivational Social Visualizations for Personalized E-Learning

A large number of educational resources is now available on the Web to support both regular classroom learning and online learning. However, the abundance of available content produces at least two problems: how to help students find the most appropriate resources, and how to engage them into using these resources and benefiting from them. Personalized and social learning have been suggested as potential methods for addressing these problems. Our work presented in this paper attempts to combine the ideas of personalized and social learning. We introduce Progressor + , an innovative Web-based interface that helps students find the most relevant resources in a large collection of self-assessment questions and programming examples. We also present the results of a classroom study of the Progressor +  in an undergraduate class. The data revealed the motivational impact of the personalized social guidance provided by the system in the target context. The interface encouraged students to explore more educational resources and motivated them to do some work ahead of the course schedule. The increase in diversity of explored content resulted in improving students’ problem solving success. A deeper analysis of the social guidance mechanism revealed that it is based on the leading behavior of the strong students, who discovered the most relevant resources and created trails for weaker students to follow. The study results also demonstrate that students were more engaged with the system: they spent more time in working with self-assessment questions and annotated examples, attempted more questions, and achieved higher success rates in answering them

R2O, an extensible and semantically based database-to-ontology mapping language

We present R2O, an extensible and declarative language to describe mappings between relational DB schemas and ontologies implemented in RDF(S) or OWL. R2O provides an extensible set of primitives with welldefined semantics. This language has been conceived expressive enough to cope with complex mapping cases arisen from situations of low similarity between the ontology and the DB models

Methodological issues in developing a multi-dimensional coding procedure for small group chat communication

In CSCL research, collaboration through chat has primarily been studied in dyadic settings. This article discusses three issues that emerged during the development of a multi-dimensional coding procedure for small group chat communication: a) the unit of analysis and unit fragmentation, b) the reconstruction of the response structure and c) determining reliability without overestimation. Threading, i.e. connections between analysis units, proved essential to handle unit fragmentation, to reconstruct the response structure and for reliability of coding. In addition, a risk for reliability overestimation was illustrated. Implications for analysis methodology in CSCL are discussed

Source Update Capture in Information Agents

In this paper we present strategies for successfully capturing updates at Web sources. Web-based information agents provide integrated access to autonomous Web sources that can get updated. For many information agent applications we are interested in knowing when a Web source to which the application provides access, has been updated. We may also be interested in capturing all the updates at a Web source over a period of time i.e., detecting the updates and, for each update retrieving and storing the new version of data. Previous work on update and change detection by polling does not adequately address this problem. We present strategies for intelligently polling a Web source for efficiently capturing changes at the source

Progressor: Social navigation support through open social student modeling

The increased volumes of online learning content have produced two problems: how to help students to find the most appropriate resources and how to engage them in using these resources. Personalized and social learning have been suggested as potential ways to address these problems. Our work presented in this paper combines the ideas of personalized and social learning in the context of educational hypermedia. We introduce Progressor, an innovative Web-based tool based on the concepts of social navigation and open student modeling that helps students to find the most relevant resources in a large collection of parameterized self-assessment questions on Java programming. We have evaluated Progressor in a semester-long classroom study, the results of which are presented in this paper. The study confirmed the impact of personalized social navigation support provided by the system in the target context. The interface encouraged students to explore more topics attempting more questions and achieving higher success rates in answering them. A deeper analysis of the social navigation support mechanism revealed that the top students successfully led the way to discovering most relevant resources by creating clear pathways for weaker students. © 2013 Taylor and Francis Group, LLC