eLearning

Abstract: The great diffusion of Web 2.0 is having a tremendous effect and change on the way people search, find, collaboratively develop and consume information and knowledge. Education and learning are not an exception of Web 2.0 trends, as the number of Web 2.0 empowered e-learning environments are booming. Although research in Web 2.0 applications in learning is rising, the studies tend to be very descriptive failing to identify and discuss the pedagogical theories and models that support and enhance the exploitation of Web 2.0 tools in (e)-learning environments. This paper aims to first discuss the use of Web 2.0 in (e)-learning and the new skills that they enable, and then, debate the pedagogical theories that support the exploitation of Web 2.0 for creating personalised and collaborative learning environments. To achieve that, a socio-technical approach is suggested.

 eLearning;  

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Abstract: With vigorous development of the Internet, especially the web page interaction technology, distant E-learning has become more and more realistic and popular. Digital courses may consist of many learning units or learning objects and, currently, many learning objects are created according to SCORM standard. It can be seen that, in the near future, a vast amount of SCORM-compliant learning objects will be published and distributed cross the Internet. Facing huge volumes of learning objects, learners may be lost in selecting suitable and favorite learning objects. In this paper, an adaptive personalized recommendation model is proposed in order to help recommend SCORM-compliant learning objects from repositories in the Internet. This model adopts an ontological approach to perform semantic discovery as well as both preference-based and correlation-based approaches to rank the degree of relevance of learning objects to a learner’s intension and preference. By implementing this model, a tutoring system is able to provide easily and efficiently suitable learning objects for active learners

 Learning Object;  eLearning;  SCORM;  Personalized recommendation;  Learner Pattern;  Semantic Discovery;  LOM;  

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Abstract: 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

 Ontologies;  eLearning;  context;  

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Abstract: Abstract Recent developments of e-learning specifications such as Learning Object Metadata (LOM), Sharable Content Object Reference Model (SCORM), Learning Design and other pedagogy research in semantic e-learning have shown a trend of applying innovative computational techniques, especially Semantic Web technologies, to promote existing content-focused learning services to semantic-aware and personalised learning services. To facilitate this transforming process, this paper presents a novel context-aware semantic e-learning approach to integrate content provision, learning process and learner personality in an integrated semantic e-learning framework. As the basis of the computational framework, a scalable and extensible generic context model is proposed to structure the semantics of contextual relations and concepts in various contexts, such as learning content description, learning model, knowledge object representation and learner personality. Corresponding technical and pedagogical developments of this framework also consider compatibility issues with existing technologies (eg, XML/Resource Description Framework) and specifications (eg, IEEE LOM) in order to achieve the best interoperability.

 eLearning;  

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Abstract: This paper describes our idea for personalized e-Learning in the Semantic Web which is based on configurable, re-usable personalization services. To realize our ideas, we have developed a framework for designing, implementing and maintaining personal learning object readers, which enable the learners to study learning objects in an embedding, personalized context. We describe the architecture of our Personal Reader framework, and discuss the implementation of personalization services in the Semantic Web. We have realized two Personal Readers for e-Learning: one for learning Java programming, and another for learning about the Semantic Web.

 eLearning;  

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Abstract: Current standardized e-learning systems are centred on the concept of learning object. Unfortunately, specifications and standards in the field do not provide details about the use of well-known knowledge representations for the sake of automating some processes, like selection and composition of learning objects, or adaptation to the user or platform. Precise usage specifications for ontologies in e-learning would foster automation in learning systems, but this requires concrete, machine-oriented interpretations for metadata elements. This chapter focuses on ontologies as shared knowledge representations that can be used to obtain enhanced learning object metadata records in order to enable automated or semi-automated consistent processes inside Learning Management Systems. In particular, two efforts towards enhancing automation are presented: a contractual approach based on pre- and post-conditions, and the so-called process conformance profiles.

 Ontologies;  Learning Object;  eLearning;  

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Abstract: The fast development of technologies requires specialized and complex skills that need to be renewed frequently. Thus the role of continuing education and lifelong learning is becoming even more important. E-learning adapts well to continued education, as it can be done in parallel to other workd. This in turn sets new requirements for universities: they have to build e-learning infrastructures and course material has to be in digital form. Moreover, the e-learning systes should be designed in a way that they provide easy access to courses and course material. A cornerstone of easy access is the metadata attached to courses and other relevant elemtns. However, the mere metadata itself is not very useful without the ontology that gives the semantics for the metadata. In this chapter, we will give an overview of the role of metadata and ontologies in e-learning systems. We will consider the standards of educational metadata and consider the utilization of metadata and ontologies in three e-learning systems

 eLearning;  metadata;;  

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Abstract: Current systems used in education follow a consistent design pattern, not supportive of lifelong learning or personalization, is asymmetric in terms of user capability, and which is disconnected from the global ecology of Internet services. In this paper we propose an alternative design pattern for educational systems thatemphasizes symmetric connections with a range of services both in formal and informal learning, worstrategies for implementation and experimentation.

 eLearning;  Personalized digital library;  

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Abstract: This paper describes our idea for personalized e-Learning in the Semantic Web which is based on configurable, re-usable personalization services. To realize our ideas, we have developed a framework for designing, implementing and maintaining personal learning object readers, which enable the learners to study learning objects in an embedding, personalized context. We describe the architecture of our Personal Reader framework, and discuss the implementation of personalization services in the Semantic Web. We have realized two Personal Readers for e-Learning: one for learning Java programming, and another for learning about the Semantic Web.

 eLearning;  

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Abstract: In spite of the fact that the field of applying ontological research in education is fairly young it is already quite broad and fuzzy. The set of technologies used and developed there have roots in a variety of diverse areas of information and pedagogical sciences. To facilitate the process of scientific and scholastic search the domain needs to be structured. This paper presents two main results: an ontological overview of the Ontologies for Education field and an initial report on the development of an ontology-driven web portal providing a single network place, where researchers, students, and practitioners can find information about available research projects and successful practices in this field.

 eLearning;  

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Abstract: The motivation for this discussion is to look at the cognitive and logical rationales of e-Learning objects, which reside in computer-based e-Learning artefacts. e-Learning objects, the system to which they belong, and the sequence of messages that form a discourse between the system and its environment are inseparable. Altogether, they formulate the “Universe of Discourse” (Wieringa, 2003, p. 14). When we talk about systems, we equally refer the discourse to e-Learning objects because they are the “workers” of the system. e-Learning is “a combination of content and instructional methods delivered by media elements such as words and graphics on a computer intended to build job-transferable knowledge and skills linked to individual learning goals or organizational performance” (Clark & Mayer, 2002, p. 311). The sciences of instruction, learning, and knowledge are intricate and the “e-” before “Learning” adds another dimension of complexity while paving new learning paths for e-Learning.

 eLearning;  Cognitive Learning Theories;  eLearning Artifacts;  eLearning Object Metadata;  

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Abstract: Nowadays, the leading e-learning platforms are converging towards standardization. This paper presents an extension to the SCORM, today's most well acclaimed e-learning standard, enabling the modelling of course related entities that surround learning objects and content aggregations, therefore increasing the standard's modelling scope and allowing for gains in efficiency in knowledge dissemination. A prototype is being implemented and tested on VIANET, an original e-learning platform with extensible support for the SCORM. content aggregations.

 eLearning;  SCORM;  

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Abstract: Sorry no abstract available for this article

 eLearning;  learning objects;  

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Abstract: By 2020, micro p rocessors will likely be as cheap and plentiful as scrap paper, s c a t t e red by the millions into the environment, allowing us to place intelligent systems eve ry w h e re. This will change eve rything around us, including the nature of commerce, the wealth of nations, and the way we communicate, work, play, and live. This will give us smart homes, cars, T V s , j e we l l e ry, and money. We will speak to our appliances, and they will speak back. Scientists also expect the In t e rnet will wire up the entire planet and evo l ve into a membrane consisting of millions of computer networks, creating an “intelligent planet.” The In t e rnet will eventually become a “Magic Mi r ro r” that appears in fairy tales, able to speak with the wisdom of the human ra c e . Michio Kaku, Visions: How Science Will Re vo l u t i o n i ze the Twe n t y - Fi r s t C e n t u ry, 1998 If the semantic web needed a symbol, a good one to use would be a Na va h o d ream-catcher: a small we b, lovingly hand-crafted, [easy] to look at, and ru m o red to catch dreams; but really more of a symbol than a re a l i t y. Pat Ha yes, Catching the Dreams, 2002

 eLearning;  

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Abstract: The World Wide Web offers an increasing amount of complex and rich educational Web resources that are available for free in various domains. Unfortunately, it is difficult today to have a Web agent that answers precisely a simple query. Semantic Web aims to make Web resources meaningful to automated agents. Ontologies are proposed to provide a formal representation of a shared and common conceptualization of a specific domain. For the description of educational resources several communities are working on the definition of metadata elements. The Learning Technology Standards Committee (LTSC) specifies the Learning Object Metadata (LOM), a set of elements describing the relevant characteristics for learning resources. The goal of this paper is to give a formal and more comprehensive content description of learning resources in order to allow better reusability and retrievals. This description is particularly focused on the semantic relationships between learning resources which constitute an important aspect to access information. It uses OWL, an ontology language for the semantic Web, recently developed by the W3C. OWL provides powerful expressiveness combined with desirable computational properties for reasoning systems due to its correspondence with description logics. The query of the corresponding knowledge base is illustrated using OWL Query Language OWL-QL.

 Ontologies;  semantic Web;  eLearning;  IEEE LOM;  query languages;  OWL Query Language;  OWL-QL;  automated agent;  educational Web resources;  learning object querying;  ontology language;  

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Abstract: Recent developments in Web technologies and using AI techniques to support efforts in making the Web more intelligent and provide higher-level services to its users have opened the door to building the Semantic Web. That fact has a number of important implications for Web-based education, since Web-based education has become a very important branch of educational technology. Classroom independence and platform independence of Web-based education, availability of authoring tools for developing Web-based courseware, cheap and efficient storage and distribution of course materials, hyperlinks to suggested readings, digital libraries, and other sources of references relevant for the course are but a few of a number of clear advantages of Web-based education. However, there are several challenges in improving Web-based education, such as providing for more adaptivity and intelligence. Developments in the Semantic Web, while contributing to the solution to these problems, also raise new issues that must be considered if we are to progress. This paper surveys the basics of the Semantic Web and discusses its importance in future Web-based educational applications.

 semantic Web;  eLearning;  

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Abstract: The big question for many researchers in the area of educational systems now is what is the next step in the evolution of e-learning? Are we finally moving from a scattered intelligence to a coherent space of collaborative intelligence? How close we are to the vision of the Educational Semantic Web and what do we need to do in order to realize it? Two main challenges can be seen in this direction: on the one hand, to achieve interoperability among various educational systems and on the other hand, to have automated, structured and unified authoring support for their creation. In the spirit of the Semantic Web a key to enabling the interoperability is to capitalize on the (1) semantic conceptualization and ontologies, (2) common standardized communication syntax, and (3) large-scale service-based integration of educational content and functionality provision and usage. A central role in achieving unified authoring support plays the process-awareness of authoring tools, which should reflect the semantic evolution of e-learning systems. The purpose of this paper is to outline the state-of-the-art research along those lines and to suggest a realistic way towards the Educational Semantic Web. With regard to the latter we first propose a modular semantic-driven and service-based interoperability framework, in order to open up, share and reuse educational systems’ content and knowledge components. Then we focus on content creation by proposing ontology-driven authoring tools that reflect the modularization in the educational systems, maintain a consistent view on the entire authoring process, and provide wide (semi-) automation of the complex authoring tasks

 eLearning;  

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Abstract: The term Learning Object, first popularized by Wayne Hodgins in 1994 when he named the CedMA working group Learning Architectures, APIs and Learning Objects, has become the Holy Grail of content creation and aggregation in the computer-mediated learning field. The terms Learning Objects (LOs) and Reusable Learning Objects are frequently employed in uncritical ways, thereby reducing them to mere slogans. The serious lack of conceptual clarity and reflection is evident in the multitude of definitions and uses of LOs. The objectives of this paper are to assess current definitions of the term Learning Object, to articulate the foundational principles for developing a concept of LOs, and to provide a methodology and broad set of guidelines for creating LOs.

 eLearning;  learniing;  learning objects;  

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Abstract: Meta-data is the fundamental building block of the Semantic Web. However, the meta-data concept is too loosely defined to provide architectural guidelines for its use. This paper analyzes important uses of meta-data in the e-learning domain, from a pedagogical and philosophical point of view, and abstracts from them a set of fundamental architectural requirements for Semantic Web meta-data. It also describes some flexible generic techniques for working with meta-data, following these requirements. Finally, the paper describes a Semantic Web-based e-learning architecture based in these requirements and techniques currently under development at the Knowledge Management Research Group at CID (Centre for user oriented IT Design) at KTH, the Royal Institute of Technology in Stockholm. This architecture builds on Edutella, a peer-to-peer meta-data exchange network, and a technique called conceptual modeling using the Conzilla concept browser, a new kind of knowledge management tool for conceptual navigation and exploration.

 metadata;  eLearning;  Edutella;  Knowledge Manifolds;  

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Abstract: This white paper analyzes some of the reasons why e-learning has failed, thus far, to deliver on its promise of anytime, anywhere learning. We focus on online self-study courseware as the best example of e-learning content implementation to date and uncover some underlying challenges to adoption of initiatives such as interactivity, a learning- and learner-centered model, learning objects, the emerging e-learning standards and the use of metadata to solve the search and retrieval problem. We recommend a renewed focus on ontologies as machine representations of knowledge domains, and a blended meta data management model as critical parts of an emerging e-learning infrastructure.

 Ontologies;  metadata;  eLearning;  knowledge management;  

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Abstract: Technologically, researchers are making rapid progress realizing the personalized learning dream with object architecture and adaptive learning technology. However, a whole-person understanding of how individuals want or intend to learn (more than just building, processing, and storing knowledge) is still missing from most online solutions. Primarily cognitive solutions that overlook the power of emotions and intentions may be insufficient for online learning, especially when instructors are unavailable to facilitate instruction. This paper describes a study that examines how individuals learn in adaptive Web learning environments. Included are guidelines that have evolved from the study’s results for designing interactive learning environments from an alternative perspective. Offering a whole-perspective perspective about learning, this paper introduces (a) profiles that describe fundamental differences in how people learn, (b) specific reasons why some learners may be more successful than others, (c) strategies for helping learners improve Web learning ability, and (d) design guidelines that tap into the dominant influence of emotions, intentions, and social factors on learning.

 eLearning;  Distance Learning;  Adaptive Learning;  Personalized learning;;  

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Abstract: In the last few years the (semi-) automatic sequencing of course material has become an important research issue, particularly the standardization of metadata for educational resources. Sequencing can help to generate hypermedia documents which, at their best. match the learner’s needs. To perform (semi-) automatic course sequencing, a knowledge library as well as modular resources can be used. Both must be described by metadata. First, metadata standards (IEEE Learning Objects Metadata, Instructional Management Systems Global Learning Consortium, Dublin Core) are analyzed with regard to course sequencing. As an application example, Multibook, an adaptive hypermedia system used to teach multimedia technology, is described. Multibook uses metadata to create course sequences semi-automatically. In this article we explain how a knowledge library can be used to create exercises automatically. We give an example of how courses can be sequenced in general by analyzing the creation of exercises. An evaluation of our system shows the advantages and drawbacks of the automatic course sequencing approach.

 metadata;  eLearning;  Dublin Core Metadata;  IEEE LOM;  

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Abstract: Building repositories for e-learning is an iterative process and course content and course structure are always changing. We realized the necessity to separate content from structure of a given course during the conception of our first e-learning repository, which we called KBS-Hyperbook, several years ago at our institute. This system has been built around a conceptual model for structure and contents of the domain, which is expressed in the O-Telos conceptual modelling language. To ease exchange of metadata between such repositories, the Open Learning Repository (OLR), an e-learning repository we built during the last year to experiment with various features useful for such repositories, has been developed using RDF/RDFS as modelling language. In the first part of this paper, we describe the OLR system in more detail, and show how it uses RDF/RDFS as its underlying modelling language to express information about the learning objects contained in the repository, as well as information about the relationships between these learning objects. Based on our experience in meta-modelling using different modelling languages, we will in the second part of this paper discuss RDF/RDFS and O-Telos modelling in more depth and will analyse similarities and differences of these two modelling languages.

 eLearning;  rdf;  

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Abstract: Sorry no abstract available for this article

 eLearning;  Digital Immigrants;  Digital Natives;  

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Abstract: Despite the plethora of teaching materials that are available on the Internet to enhance geography higher education, few assessments of the effectiveness of these materials exist. This symposium collects papers that provide guidelines for using the Internet effectively for teaching geography. Students must learn how to use the Internet effectively to promote learning; instructors need to learn how to use the Internet effectively to promote good practice in higher education; instructors need to learn how to use the Internet effectively to enhance learning; and higher educators need to learn how to use the Internet effectively not only in traditional classroom settings, but in new, non-traditional settings such as those used for distance learning. These papers provide some assessment of these various aspects of using the Internet for teaching geography in higher education.

 Geography;  eLearning;  

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Abstract: When McLuhan and Fiore (1967) boldly declared that “the medium is the message,” they were calling our attention to the subtle and complex roles of the medium in shaping our thoughts and behaviors. Today, people seem to be unable to discuss anything without mentioning the Internet-the latest electronic medium for communication. The Internet’s explosive growth during the past five years has raised numerous issues regarding fundamental geographic concepts such as space, place, and time (Adams and Warf 1997, Brunn 1998). As more geography departments offer virtual field trips, on-line courses, and even on-line degree programs, the Internet is also changing the way we teach geography (0 Tuathail and McCormack 1998). Similar to previous technical advances, the current episode has generated both enormous enthusiasm and serious concerns (Hiltz 1994, Talbott 1995, Rochlin 1996, Tapscott 1998). This special issue addresses conceptual, cognitive, and pedagogic issues in the age of the Internet, and this introduction situates the current transformation and its implications for geography and geographic education in a broader historical and conceptual context. We hope to provoke geographers to think beyond technical issues and stimulate further discussion about how the Internet will transform traditional geographic concepts and how cognitive and pedagogical theories can be incorporated into the e-merging virtual geography department.

 Geography;  eLearning;  education;  

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Abstract: This paper starts from the assumption that any evaluation of educational software should focus on whether or not, and the extent to which, it maximizes learning. It is particularly concerned with the impact of software on the quality of learning. The paper reviews key texts in the literature on learning, including some which relate directly to software development, and suggests ways in which a range of learning theories can inform the process of software design. The paper sets out to make a contribution to both the design and the evaluation of educational software.

 eLearning;  mental schma;  

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Abstract: In this paper, we examine the semantic aspects of e-learning from both pedagogical and technological points of view. We suggest that if semantics are to fulfil their potential in the learning domain then a paradigm shift in perspective is necessary, from information-based content delivery to knowledge-based collaborative learning services. We propose a semantics driven Knowledge Life Cycle that characterises the key phases in managing semantics and knowledge, show how this can be applied to the learning domain and demonstrate the value of semantics via an example of knowledge reuse in learning ssessment management.

 eLearning;  

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Abstract: The Personal Reader framework implements a service-based architecture for developing and maintaining personalization functionalities on the Semantic Web, stemming from disciplines like e.g. adaptive hypermedia systems or collaborative filtering systems. A modular framework of components / services - for providing the user interface, for mediating between user requests and available personalization services, for user modeling, for providing personal recommendations and context information, et cetera, is the core of the Personal Reader framework. When a user is viewing some Web Content (the "Reader" part of the Personal Reader) s/he receives additional, personal information on the context of this particular Web content (the "Personal" part of the Personal Reader). Personal Readers have been developed for the area of e-Learning (Java, Semantic Web), and for browsing scientific publications.

 eLearning;  

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Abstract: Sorry no abstract available for this article

 eLearning;  

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Abstract: “People are our most important assets”. Intellectual capital has become the primary factor of production. To raise their “corporate IQ”, managers treat workers as if they were customers of learning. This article explores why people learn much more about their jobs in the coffee room than in the classroom. It hypothesizes that equipping people intellectually to prosper will become a corporate discipline every bit as important as marketing or finance. Web services will mark the advent of workflow learning in real-time organizations.

 metadata;  eLearning;  peer-to-peer learning;  knowledge management;  

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