Jelena Jovanovic

Ontology-Based Automatic Annotation of Learning Content

This paper presents an ontology-based approach to automatic annotation of learning objects’ (LOs) content units that we tested in TANGRAM, an integrated learning environment for the domain of Intelligent Information Systems. The approach does not primarily focus on automatic annotation of entire LOs, as other relevant solutions do. Instead, it provides a solution for automatic metadata generation for LOs’ components (i.e., smaller, potentially reusable, content units). 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.

Using Semantic Web Technologies to Analyze Learning Content

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.

Effect of different physicochemical properties of hydrophobic zeolites on the pervaporation properties of PDMS-membranes

The paper describes the investigation of the effect of three different types of hydrophobic zeolites (ultrastable zeolite type Y, pentasyl type zeolite (ZSM-5), and ALPO-5 type zeolite) on the pervaporation properties of zeolite-filled polydimethylsiloxane membranes. The procedure of obtaining membranes of various thicknesses varying in zeolite content was mastered. The physicochemical properties of the utilized zeolites were investigated and determined. The effect of zeolite type and concentration, as well as the membrane thickness and pervaporation temperature on the membrane permeability and selectivity were investigated. The physicochemical properties of the zeolite used, primarily the degree of hydrophobicity, as well as the sorption capacity for ethanol, the specific pore volume, specific area and mean crystallite size of the zeolite, significantly influence the membranes pervaporation properties. An increase in the zeolite content results in an increase of both membrane permeability and selectivity, while an increase in the pervaporation temperature results in an increase of the permeability and a decrease of selectivity, as opposed to the effect of membrane thickness.

The Pragmatics of Current E-Learning Standards

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 Web-based education system developers will have the tips necessary to approach, implement, and reuse standards-based distance learning applications

Student modeling and assessment in intelligent tutoring of software patterns

This paper presents the design, implementation, and evaluation of a student model in DEPTHS (Design Pattern Teaching Help System), an intelligent tutoring system for learning software design patterns. There are many approaches and technologies for student modeling, but choosing the right one depends on intended functionalities of an intelligent system that the student model is going to be used in. Those functionalities often determine the kinds of information that the student model should contain. The student model used in DEPTHS is a result of combining two widely known modeling approaches, namely, stereotype and overlay modeling. The model is domain independent and can be easily applied in other learning domains as well. To keep student model update during the learning process, DEPTHS makes use of a knowledge assessment method based on fuzzy rules (i.e., a combination of production rules and fuzzy logics). The evaluation of DEPTHS performed with the aim of assessing the systems overall effectiveness and the accuracy of its student model, indicated several advantages of the DEPTHS system over the traditional approach to learning design patterns, and encouraged us to move on further with this research.

Repurposing learning object components

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.

E-Learning meets the Social Semantic Web

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; representing respectively a teacher-centered and a learner-centered approach for learning environments. In this paper we bridge the gap between these two approaches by leveraging the social semantic Web paradigm, and propose a collaborative semantic-rich learning environment in which folksonomies created from studentspsila collaborative tags contribute to ontology maintenance, and teacher-directed feedback.

The Social Semantic Web in Intelligent Learning Environments: state of the art and future challenges

Todays technology-enhanced learning practices cater to students and teachers who use many different learning tools and environments and are used to a paradigm of interaction derived from open, ubiquitous, and socially oriented services. In this context, a crucial issue for education systems in general, and for Intelligent Learning Environments (ILEs) in particular, is related to the ability of leveraging these new paradigms for creating, maintaining and sharing the knowledge that these systems embed. This will enable ILEs to benefit from shared information from disparate systems, which is related to learning content and student activities, so that the overall complexity of system development and maintenance would be reduced while at the same time improving the capability of personalization, context-awareness, and interaction. In this article, we investigate how the Social Semantic Web can be leveraged for enabling and easing this process. We first analyze each module of a typical ILE, showing how it can benefit from the Social Semantic Web paradigm and then proceed to investigate how this new paradigm can be leveraged for increasing interactivity level of ILEs.

Collaborative Learning in Online Study Groups: An Evolutionary Game Theory Perspective.

Educational benefits of online collaborative group work have been confirmed in numerous research studies. Most frequently cited advantages include the development of skills of critical thinking and problem solving as well as skills of self-reflection and co-construction of knowledge and meaning. However, the establishment and maintenance of active collaboration in online study groups is a challenging task, primarily due to students’ inability (e.g., owing to time constraints or lack of collaboration skills) or reluctance (e.g., due to the lack of or low participation of other group members) to participate actively in the group work. Aiming to better understand and contribute to the resolution of the problems of effective online group work, we followed a novel approach based on Evolutionary Game Theory (EGT). While EGT has been used extensively as a framework for studying the emergence and maintenance of cooperation in many disciplines, to the best of our knowledge, it has not yet been applied to understanding and facilitating group collaboration in online learning settings. In this paper, we present a study we have conducted in order to investigate whether, and to what extent, EGT can be applied to explain students’ participation in collaborative study groups.

Ontology-based learning content repurposing

This paper investigates basic research issues that need to be addressed for developing an architecture that enables repurposing of learning objects in a flexible way. Currently, there are a number of Learning Object Content Models (e.g. the SCORM Content Aggregation Model) that define learning objects and their components in a more or less precise way. However, these models do not allow repurposing of fine-grained components (sentences, images). We developed an ontology-based solution for content repurposing. The ontology is a solid basis for an architecture that will enable on-the-fly access to learning object components and that will facilitate repurposing these components.