1,630 research outputs found
Improving instructional effectiveness with computer‐mediated communication
This study explores the use of asynchronous Computer‐Mediated Communication (CMC) in the delivery of instructional content, and points up the interaction among learners, as well as between learners and instructors. The instructional content in the project described was available to learners online as Microsoft Word documents, with email being used for communicating within the student group. Many students, as well as some of the instructors, felt uncomfortable with the flexibility and openness that a CMC environment allowed. However, once familiar with this process of instruction and interaction, learners were able to work consistently at their own pace, and understand that instructors are interested in every individual learner's opinion and in the collective views of the group. It was evident that a CMC‐based instructional delivery system, when carefully planned, has the potential to facilitate that outcome, and to improve instructional effectiveness
Building multi-layer social knowledge maps with google maps API
Google Maps is an intuitive online-map service which changes people's way of navigation on Geo-maps. People can explore the maps in a multi-layer fashion in order to avoid information overloading. This paper reports an innovative approach to extend the "power" of Google Maps to adaptive learning. We have designed and implemented a navigator for multi-layer social knowledge maps, namely ProgressiveZoom, with Google Maps API. In our demonstration, the knowledge maps are built from the Interactive System Design (ISD) course at the School of Information Science, University of Pittsburgh. Students can read the textbooks and reflect their individual and social learning progress in a context of pedagogical hierarchical structure
Adaptive Information Visualization for Personalized Access to Educational Digital Libraries
Personalization is one of the emerging ways to increase the power of modern Digital Libraries. The Knowledge Sea II system presented in this paper explores social navigation support, an approach for providing personalized guidance within the open corpus of educational resources. Following the concepts of social navigation we have attempted to organize a personalized navigation support that is based on past learners’ interaction with the system. The study indicates that Knowledge Sea II became the students' primary tool for accessing the open corpus documents used in a programming course. The social navigation support implemented in this system was considered useful by students participating in the study of Knowledge Sea II. At the same time, some user comments indicated the need to provide more powerful navigational support, such as the ability to rank the usefulness of a page
Adaptive hypertext and hypermedia : workshop : proceedings, 3rd, Sonthofen, Germany, July 14, 2001 and Aarhus, Denmark, August 15, 2001
This paper presents two empirical usability studies based on techniques from Human-Computer Interaction (HeI) and software engineering, which were used to elicit requirements for the design of a hypertext generation system. Here we will discuss the findings of these studies, which were used to motivate the choice of adaptivity techniques. The results showed dependencies between different ways to adapt the explanation content and the document length and formatting. Therefore, the system's architecture had to be modified to cope with this requirement. In addition, the system had to be made adaptable, in addition to being adaptive, in order to satisfy the elicited users' preferences
Adaptive hypertext and hypermedia : workshop : proceedings, 3rd, Sonthofen, Germany, July 14, 2001 and Aarhus, Denmark, August 15, 2001
This paper presents two empirical usability studies based on techniques from Human-Computer Interaction (HeI) and software engineering, which were used to elicit requirements for the design of a hypertext generation system. Here we will discuss the findings of these studies, which were used to motivate the choice of adaptivity techniques. The results showed dependencies between different ways to adapt the explanation content and the document length and formatting. Therefore, the system's architecture had to be modified to cope with this requirement. In addition, the system had to be made adaptable, in addition to being adaptive, in order to satisfy the elicited users' preferences
Exact ICL maximization in a non-stationary temporal extension of the stochastic block model for dynamic networks
The stochastic block model (SBM) is a flexible probabilistic tool that can be
used to model interactions between clusters of nodes in a network. However, it
does not account for interactions of time varying intensity between clusters.
The extension of the SBM developed in this paper addresses this shortcoming
through a temporal partition: assuming interactions between nodes are recorded
on fixed-length time intervals, the inference procedure associated with the
model we propose allows to cluster simultaneously the nodes of the network and
the time intervals. The number of clusters of nodes and of time intervals, as
well as the memberships to clusters, are obtained by maximizing an exact
integrated complete-data likelihood, relying on a greedy search approach.
Experiments on simulated and real data are carried out in order to assess the
proposed methodology
A Study on the Use of Ontologies to Represent Collective Knowledge
The development of ontologies has become an area of considerable research interest over the past number of years. Domain ontologies are often developed to represent a shared understanding that in turn indicates cooperative effort by a user community. However, the structure and form that an ontology takes is predicated both on the approach of the developer and the cooperation of the user community. A shift has taken place in recent years from the use of highly specialised and expressive ontologies to simpler knowledge models, progressively developed by community contribution. It is within this context that this thesis investigates the use of ontologies as a means to representing collective knowledge. It investigates the impact of the community on the approach to and outcome of knowledge representation and compares the use of simple terminological ontologies with highly structured expressive ontologies in community-based narrative environments
Menu-Based User Interface Systems: Theory and Practice
The thesis discusses the menu selection technique, which is one of the most commonly used interaction techniques in Human-Computer Interfaces, and continues to flourish because of its simple interaction format and its adaptability to the many diverse applications. The ease of use of the technique, particularly by novices, contributes significantly to the widespread acceptance of menu-based user interface systems, despite their inherent disadvantages and drawbacks. Chapter One surveys the issues concerning the design and use of menu-based interfaces, and addresses particularly the navigational problems encountered by users of menu selection systems, identifying various navigational aids which help overcome these problems. The chapter concludes with a comparison between menu-based interfaces and other interface styles (command language, natural language and form-filling). Chapter Two describes the practical work of the thesis which consists of implementing a particularly demanding menu-based interface example involving multiple menu selections using four different dialogue specification systems. The implementation is discussed mainly from a menu system designer's view. Strategies to solve or address the multiple selection mechanism problem as well as some the navigational concepts discussed in chapter one are devised and used within each the four target systems. Also, some other related user interface design issues are reported in chapter two. The principal aim of the work is to investigate the difficulties a dialogue designer may face in attempting to implement a common type of menu-based interface using various delivery systems, all of which claim in varying degrees to support menu-based interactive styles. In the final chapter conclusions are drawn from the practical work concerning desirable menu support features in user interface implementation systems, and issues requiring further investigation are identified
Business Intelligence from Web Usage Mining
The rapid e-commerce growth has made both business community and customers
face a new situation. Due to intense competition on one hand and the customer's
option to choose from several alternatives business community has realized the
necessity of intelligent marketing strategies and relationship management. Web
usage mining attempts to discover useful knowledge from the secondary data
obtained from the interactions of the users with the Web. Web usage mining has
become very critical for effective Web site management, creating adaptive Web
sites, business and support services, personalization, network traffic flow
analysis and so on. In this paper, we present the important concepts of Web
usage mining and its various practical applications. We further present a novel
approach 'intelligent-miner' (i-Miner) to optimize the concurrent architecture
of a fuzzy clustering algorithm (to discover web data clusters) and a fuzzy
inference system to analyze the Web site visitor trends. A hybrid evolutionary
fuzzy clustering algorithm is proposed in this paper to optimally segregate
similar user interests. The clustered data is then used to analyze the trends
using a Takagi-Sugeno fuzzy inference system learned using a combination of
evolutionary algorithm and neural network learning. Proposed approach is
compared with self-organizing maps (to discover patterns) and several function
approximation techniques like neural networks, linear genetic programming and
Takagi-Sugeno fuzzy inference system (to analyze the clusters). The results are
graphically illustrated and the practical significance is discussed in detail.
Empirical results clearly show that the proposed Web usage-mining framework is
efficient
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