Papers by Jelena Jovanovic
Expert Systems With Applications, 2006
The paper describes JavaDON, an open-source expert systems shell based on the OBOA framework for ... more The paper describes JavaDON, an open-source expert systems shell based on the OBOA framework for developing intelligent systems. The central idea of the JavaDON project was to make an easy-to-use and easy-to-extend tool for building practical expert systems. Since JavaDON is rooted in a sound theoretical framework, it is well-suited for building even complex expert system applications, both stand-alone and Web-based ones. JavaDON knowledge representation scheme supports using multimedia elements along with traditional techniques, such as rules and frames. Another important feature of JavaDON is its capability of saving knowledge bases in XML format (in addition to the shell's native format), thus making them potentially easy to interoperate with other knowledge bases on the Internet. So far, JavaDON has been used to build several practical expert systems, as well as a practical knowledge engineering tool to support both introductory and advanced university courses on expert systems. The paper presents design details of JavaDON, explains its links with the underlying OBOA framework, and shows examples of using JavaDON in expert system development. It also discusses some of the current efforts in extending JavaDON. q
IEEE Internet Computing, 2007
The authors demonstrate how to use Semantic Web technologies to improve the state-of-the-art in o... more The authors demonstrate how to use Semantic Web technologies to improve the state-of-the-art in online learning environments and bridge the gap between students on the one hand, and authors or teachers on the other. The ontological framework presented here helps formalize learning object context as a complex interplay of different learning-related elements and shows how we can use semantic annotation to interrelate diverse learning artifacts. On top of this framework, the authors implemented several feedback channels for educators to improve the delivery of future Web-based courses.
IEEE Internet Computing, 2007
Experience with building distance-learning applications shows that a clear understanding of the b... more Experience with building distance-learning applications shows that a clear understanding of the big picture of standardization in this area is a necessary prerequisite for successful use of standards in practical developments. This article presents e-learning standards, standardization activities and organizations, standards-based development practices, and driving forces for improving existing standards and developing new ones. With these resources, educators and Webbased education system developers will have the tips necessary to approach, implement, and reuse a standards-based distance-learning application. 16 Published by the IEEE Computer Society 1089-7801/07/$25.00
This paper presents an ontology-based approach for automatic decomposition of learning objects (L... more This paper presents an ontology-based approach for automatic decomposition of learning objects (LOs) into reusable content units, and dynamic reassembly of such units into personalized learning content. To test our approach we developed TANGRAM, an integrated learning environment for the domain of Intelligent Information Systems. Relying on a number of ontologies, TANGRAM allows decomposition of LOs into smaller content units, which can be later assembled into new LOs personalized to the user’s domain knowledge, preferences, and learning styles. The focus of the presentation is on the ontologies themselves, in the context of user modeling and personalization. Furthermore, the paper presents the algorithm we apply to dynamically assemble content units into personalized learning content. We also discuss our experiences with dynamic content generation and point out directions for future work.
Educational Technology & Society, 2007
This paper presents an ontology-based framework aimed at explicit representation of context-speci... more This paper presents an ontology-based framework aimed at explicit representation of context-specific metadata derived from the actual usage of learning objects and learning designs. The core part of the proposed framework is a learning object context ontology, that leverages a range of other kinds of learning ontologies (e.g., user modeling ontology, domain ontology, and learning design ontology) to capture the information about the real usage of a learning object inside a learning design. We also present some learner-centered and teacher-centered scenarios enabled by the proposed framework in order to illustrate the benefits the framework offers to these key participants of any learning process. Finally, we demonstrate how two present educational tools (i.e. TANGRAM and LOCO-Analyst) correspond to the proposed architecture.
Expert Systems With Applications, 2005
Development of an intelligent system requires not only profound understanding of the problem unde... more Development of an intelligent system requires not only profound understanding of the problem under study, but also employment of different knowledge representation techniques and tools often based on a variety of paradigms and technological platforms. In this context automation of knowledge sharing between different systems becomes increasingly important. One solution might be to extend a knowledge modeling tool by implementing a set of new classes or functions for importing other knowledge formats (using, e.g. Java, CCC, etc.). But, this can be a rather difficult and time consuming task. Since XML is now widely accepted as knowledge representation syntax, we believe that a more suitable solution would be to use eXtensible Stylesheet Language Transformation (XSLT) a W3C standard for transforming XML documents. A special advantage of this approach is that even though an XSLT is written independently of any programming language, it can be executed by a program written in almost any up-to-date programming language. We experiment on an XSLT-based infrastructure for sharing knowledge between three knowledge modeling and acquisition tools that use different conceptual models for knowledge representation in order to evaluate cons and pros of the proposed XSLT approach. Two of these tools, JessGUI and JavaDON are ongoing efforts of the GOOD OLD AI research group to develop interoperable development tools for building intelligent systems, while the third one is Protégé-2000, a broadly accepted ontology development tool. q (J. Jovanović), dgasevic@ acm.org (D. Gašević). 1 Tel.: C1 604 268 7520; fax: C1 604 268 7488.
This paper presents an ontology-based framework for repurposing learning object components. Unlik... more This paper presents an ontology-based framework for repurposing learning object components. Unlike the usual practice where learning object components are assembled manually, the proposed framework enables on-the-fly access and repurposing of learning object components. The framework supports two processes: the decomposition of learning objects into their components as well as the automatic assembly of these components in real-world applications. For now, the framework supports slide presentations. As an application, we will present in this paper the integration of this functionality in MS PowerPoint.
The paper proposes a framework for building learning object (LO) content using ontologies. In the... more The paper proposes a framework for building learning object (LO) content using ontologies. In the previous work on using ontologies to describe LOs, researchers employed ontologies exclusively for describing LOs' metadata. Although such an approach is useful for searching for LOs in LO Repositories, it does not provide us with features to reuse components of LOs, nor to incorporate an explicit specification of domain semantics into LO content. We propose the use of two kinds of ontologies as a solution to this problem: content structure ontologies and domain ontologies.
One of the main obstacles for wider adoption of semantic rich e-learning systems is the difficult... more One of the main obstacles for wider adoption of semantic rich e-learning systems is the difficulty in creating and maintaining domain ontologies describing courses. Annotations, such as those resulting from collaborative tagging, provide a new source of information which can be used to ease the process of author-ing and updating domain ontologies. This paper presents an extension to the LOCO-Analyst tool, which leverages student folksonomies to support instructors when revising and updating course domain ontologies. The support is based on a computation of relatedness between ontology concepts and students tags which takes into account the "context" defined by the domain ontology. The computed scores are visualized in a tag cloud along with tag popularity scores, to allow instructors to easily comprehend the emergent feedback of their students. This approach allows for a simple and intuitive method for instructors to associate tags with concepts in their domain ontology.
This paper gives a proposal to enhance learning object (LO) content using ontological engineering... more This paper gives a proposal to enhance learning object (LO) content using ontological engineering. In the previous work on using ontologies to describe LO researchers build ontologies for description of metadata. These semantically annotated metadata improves retrieval for objects describing the same or similar content. However, these ontologies do not improve an LO content. Our approach suggests creating LOs that have content marked up in accordance with domain ontologies. Accordingly, LOs can be used not only as learning materials, but can also be used in real world applications (e.g. simulation and CASE tools, etc.). This approach is based, on defining domain ontologies, annotation-based author tools, ontology languages (RDF), and transformation (e.g. XSLT). As an illustration, we developed a simple Web application for teaching Petri nets is a simulation-supported environment.
This paper proposes an ontology that enables a formal definition of Learning Object (LO) content ... more This paper proposes an ontology that enables a formal definition of Learning Object (LO) content structure. The ontology extends the Abstract Learning Object Content Model (ALOCoM) with concepts from information architectures. It defines a number of concepts that represent different types of content units and it specifies their structure. Formalising structural aspects of LOs, the ontology facilitates re-purposing of LOs at different levels of content granularity, i.e. LOs in their entirety and their components. Furthermore, being a generic LO content model, the ontology serves as an integration point of heterogeneous LO content models.
LOCO-Analyst: A Tool for Raising Teachers' Awareness in Online Learning Environments
The paper presents LOCO-Analyst, an educational tool for providing teachers with feedback on the ... more The paper presents LOCO-Analyst, an educational tool for providing teachers with feedback on the relevant aspects of the learning process taking place in a web-based learning environment. The feedback provision is based on the learning context, which we dubbed Learning Object Context and consider as a complex interplay of learning activities, learning objects, and learners. Here we present a usage scenario based on the real data obtained from the Web-based iHelp Courses Learning Content Management System, in order to illustrate some of the functionalities that LOCO-Analyst provides. We also briefly overview Semantic Web technologies that lay beneath LOCO-Analyst and make it a generic feedback provision tool. Related work is presented as well. The paper concludes with a sketch of our current and planned future efforts for further improving LOCO-Analyst.
Expert Systems With Applications, 2004
The paper describes JessGUI, a graphical user interface developed on top of the Jess expert syste... more The paper describes JessGUI, a graphical user interface developed on top of the Jess expert system shell. The central idea of the JessGUI project was to make building, revising, updating, and testing Jess-based expert systems easier, more flexible, and more user friendly. There are many other expert system building tools providing a rich and comfortable integrated development environment to expert system builders. However, they are all either commercial or proprietary products. Jess and JessGUI are open-source freeware, and yet they are well suited for building even complex expert system applications, both stand-alone and Web-based ones. An important feature of JessGUI is its capability of saving knowledge bases in XML format (in addition to the original Jess format), thus making them potentially easy to interoperate with other knowledge bases on the Internet. Jess and JessGUI are also used as practical knowledge engineering tools to support both introductory and advanced university courses on expert systems. The paper presents design details of JessGUI, explains its links with the underlying Jess knowledge representation and reasoning tools, and shows examples of using JessGUI in expert system development. It also discusses some of the current efforts in extending Jess/JessGUI in order to provide intelligent features originally not supported in Jess. q
The paper presents an ontology-based framework for capturing learning context related information... more The paper presents an ontology-based framework for capturing learning context related information important for personalization of both learning objects (LOs) and learning designs (LDs). The central part of the framework is the LO Context ontology, that bridges a learning content ontology and a LD ontology. The LO context ontology is aimed at capturing information about the actual usage of a LO inside a LD, such as the learning activity the LO was used in, the pedagogical role assumed by the LO (e.g. exercise), the learner's features (represented in the form of the learner model) and the like. Furthermore we suggest the architecture of an adaptive educational system that leverages the proposed approach to enable personalization and reuse of LOs and LDs.
This paper gives a proposal to enhance learning object (LO) content using ontologies and semantic... more This paper gives a proposal to enhance learning object (LO) content using ontologies and semantic Web languages. In the previous work on using ontologies to describe LOs, researchers have built ontologies for description of metadata. However, these ontologies do not improve an LO's content. We suggest creating LOs that have content marked up in accordance with domain ontologies. Accordingly, LOs can be used not only as learning materials, but they can also be used in real-world applications.
E-Learning meets the Social Semantic Web
Abstract The social semantic Web has recently emerged as a paradigm in which ontologies (aimed at... more Abstract The social semantic Web has recently emerged as a paradigm in which ontologies (aimed at defining, structuring and sharing information) and collaborative software (used for creating and sharing knowledge) have been merged together. Ontologies provide an effective means of capturing and integrating knowledge for feedback provisioning, while using collaborative activities can support pedagogical theories, such as social constructivism. Both technologies have developed separately in the e-learning domain; ...
International Journal on Semantic Web and Information Systems, 2006
. Here we mainly report on the content-mining algorithms and heuristics applied for determining v... more . Here we mainly report on the content-mining algorithms and heuristics applied for determining values of certain metadata elements used to annotate content units. Specifically, the focus is on the following elements: title, description, unique identifier, subject (based on a domain ontology), and pedagogical role (based on an ontology of pedagogical roles). Additionally, as TANGRAM is grounded on an LO content structure ontology that drives the process of an LO decomposition into its constituent content units, each thus generated content unit is implicitly semantically annotated with its role/position in the LO's structure. Employing such semantic annotations, TANGRAM allows assembling content units into new LOs personalized to the users' goals, preferences, and learning styles. In order to provide the evaluation of the proposed solution, we describe our experiences with automatic annotation of slide presentations, one of the most common LO types. and Montenegro. His main research interests include software engineering, intelligent systems, knowledge representation, ontologies, Semantic Web, intelligent reasoning, and applications of artificial intelligence techniques to education and medicine. So far, he has authored/co-authored more than 260 research papers, several book chapters and books. He has been severing on editorial and reviewing boards of several international journals. He has also been a chair, PC member, referee and for many international and conferences.
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Papers by Jelena Jovanovic