13,568 research outputs found

    Adaptive Information Visualization for Personalized Access to Educational Digital Libraries

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    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

    The other side of the social web: A taxonomy for social information access

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    The power of the modern Web, which is frequently called the Social Web or Web 2.0, is frequently traced to the power of users as contributors of various kinds of contents through Wikis, blogs, and resource sharing sites. However, the community power impacts not only the production of Web content, but also the access to all kinds of Web content. A number of research groups worldwide explore what we call social information access techniques that help users get to the right information using "collective wisdom" distilled from actions of those who worked with this information earlier. This invited talk offers a brief introduction into this important research stream and reviews recent works on social information access performed at the University of Pittsburgh's PAWS Lab lead by the author. Copyright © 2012 by the Association for Computing Machinery, Inc. (ACM)

    Motivational Social Visualizations for Personalized E-Learning

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    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

    Progressor: Social navigation support through open social student modeling

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    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

    QuizMap: Open social student modeling and adaptive navigation support with TreeMaps

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    In this paper, we present a novel approach to integrate social adaptive navigation support for self-assessment questions with an open student model using QuizMap, a TreeMap-based interface. By exposing student model in contrast to student peers and the whole class, QuizMap attempts to provide social guidance and increase student performance. The paper explains the nature of the QuizMap approach and its implementation in the context of self-assessment questions for Java programming. It also presents the design of a semester-long classroom study that we ran to evaluate QuizMap and reports the evaluation results. © 2011 Springer-Verlag Berlin Heidelberg

    Progressor: Personalized visual access to programming problems

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    This paper presents Progressor, a visualization of open student models intended to increase the student's motivation to progress on educational content. The system visualizes not only the user's own model, but also the peers' models. It allows sorting the peers' models using a number of criteria, including the overall progress and the progress on a specific topic. Also, in this paper we present results of a classroom study confirming our hypothesis that by showing a student the peers' models and ranking them by progress it is possible to increase the student's motivation to compete and progress in e-learning systems. © 2011 IEEE

    Addictive links: The motivational value of adaptive link annotation

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    Adaptive link annotation is a popular adaptive navigation support technology. Empirical studies of adaptive annotation in the educational context have demonstrated that it can help students to acquire knowledge faster, improve learning outcomes, reduce navigational overhead, and encourage non-sequential navigation. In this paper, we present our exploration of a lesser known effect of adaptive annotation, its ability to significantly increase students' motivation to work with non-mandatory educational content. We explored this effect and confirmed its significance in the context of two different adaptive hypermedia systems. The paper presents and discusses the results of our work

    Guiding and motivating students through open social student modeling: Lessons learned

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    Background/Context: A large number of educational resources are now made available on the web to support both regular classroom learning and online learning. The abundance of available content has produced at least two problems: how to help students find the most appropriate resources and how to engage them in using and benefiting from these resources. Personalized and social learning have been suggested as potential ways to address these problems. Our work attempts to integrate these directions of research by combining the ideas of adaptive navigation support and open student modeling with the ideas of social comparison and social visualization. We call our approach Open Social Student Modeling (OSSM). Objective/Research Questions: First, we review a sequence of our earlier projects focused on Open Social Student Modeling for one kind of learning content and formulate several key design principles that contribute to the success of OSSM. Second, we present our exploration of OSSM in a more challenging context of modeling student progress for two kinds of learning content in parallel. We aim to answer the following research questions: How do we design OSSM interfaces to support many kinds of learning content in parallel? Will current identified design principles (key features) confirm the power of the learning community through OSSM with multiple learning-resource collections? Will the OSSM visualization provide successful personalized guidance within a richer collection of educational resources? Research Design: We designed four classroom studies to assess the value of different options for OSSM visualization of one and multiple kinds of learning content in the context of programming-language learning. We examined the comparative success of different design options to distill successful design patterns and other important lessons for the future developers of OSSM for personalized and social e-learning. Findings/Results: The results confirmed the motivational impact of personalized social guidance provided by the OSSM system in the target context. The interface encouraged students to explore more topics and motivated them to work ahead of the course schedule. Both strong and weak students worked with the appropriate levels of questions for their readiness, which yielded consistent performance across different levels of complex problems. Additionally, providing more realistic content collection on the navigation-supported OSSM visualizations resulted in uniform performance for the group. Conclusions/Recommendation: A sequence of studies of several OSSM interfaces confirmed that a combination of adaptive navigational support, open student modeling, and social visualization in the form of the OSSM interface can reinforce the navigational and motivational values of these approaches. In several contexts, the OSSM interface demonstrated its ability to offer effective guidance in helping students to locate the most relevant content at the right time while increasing student motivation to work with diverse learning content

    Virtual reality in theatre education and design practice - new developments and applications

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    The global use of Information and Communication Technologies (ICTs) has already established new approaches to theatre education and research, shifting traditional methods of knowledge delivery towards a more visually enhanced experience, which is especially important for teaching scenography. In this paper, I examine the role of multimedia within the field of theatre studies, with particular focus on the theory and practice of theatre design and education. I discuss various IT applications that have transformed the way we experience, learn and co-create our cultural heritage. I explore a suite of rapidly developing communication and computer-visualization techniques that enable reciprocal exchange between students, theatre performances and artefacts. Eventually, I analyse novel technology-mediated teaching techniques that attempt to provide a new media platform for visually enhanced information transfer. My findings indicate that the recent developments in the personalization of knowledge delivery, and also in student-centred study and e-learning, necessitate the transformation of the learners from passive consumers of digital products to active and creative participants in the learning experience
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