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Learning Styles and Ontological Approach for Information Security e-Learning System
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In Japanese higher educational institutions as in universities, many studies and practices on e-learning have been reported, but the state of trial and errors are still continuing. Thus, we propose the construction of an e-learning system incorporating not only with learner's consciousness but also with their learning style. Our proposing system is consistent of three individual parts and one integration phase. The first part is composed of tools, methods, and facilities used to provide the e-learning environment. The second part is composed of theoretical or practical works on learning styles. The third part is composed of learner’s consciousness factors on information security which we have studied so far. In the integration phase, the components of e-learning discussed in the first part are evaluated from learning style related psychological aspects. In the paper, we propose a trial version of e-learning system which includes several types of content with proper links to information security factors and to learning styles.
Instructional rubrics help teachers teach as well as evaluate student work. Further, creating rubrics with your students can be powerfully instructive.
The Index of Learning Styles© (ILS) is an instrument designed to assess preferences on the four dimensions of the Felder-Silverman learning style model. The Web-based version of the ILS is taken hundreds of thousands of times per year and has been used in a number of published studies, some of which include data reflecting on the reliability and validity of the instrument. This paper seeks to provide the first comprehensive examination of the ILS, including answers to several questions: (1) What are the dimensions and underlying assumptions of the model upon which the ILS is based? (2) How should the ILS be used and what misuses should be avoided? (3) What research studies have been conducted using the ILS and what conclusions regarding its reliability and validity may be inferred from the data?
The Learning Style Survey is designed to assess your general approach to learning. It does not predict your behavior in every instance, but it is a clear indication of your overall style preferences. For each item, circle the response that represents your approach. Complete all items. There are eleven major activities representing twelve different aspects of your learning style. When you read the statements, try to think about what you generally do when learning. It generally takes about 30 minutes to complete the survey. Do not spend too much time on any item – indicate your immediate feeling and move on to the next item.
: I (Terry) first became interested in the semantic web from reading Berners-Lee's original works
and following first generation developments of semantic web technologies in information science, e-business and health fields. I then began including the ideas in talks I gave at various conferences and forums in 2003. Naturally, I became curious about what other educators were doing with the semantic web and so Googled the term, "education semantic web". Much to my surprise and disappointment, I found that most of the references were to my own admittedly introductory and visionary comments made in these speeches. Where was the real work, innovation and actual prototype development? Fortunately, we were able to locate this type of work and we believe that most of the leading researchers in the area of the educational semantic web have contributed to this special issue. Of course, if we have missed your work, we welcome comments and URLs in the discussion areas of the special issue. Editors: Terry Anderson and Denise Whitelock.
Educational systems are gradually incorporating semantic web technologies aiming to provide a more adaptable, personalized and intelligent learning environment. In fact, there is a significant interest within the AIED community about the evolution of e-learning in this direction. This is driven by the hope that the use of Semantic Web (SW) technologies in educational systems can help the accomplishment of AAAL: Anytime, Anywhere, Anybody Learning where most of the WWW resources are reusable learning objects supported by standard technologies and learning is facilitated by intelligent pedagogical agents. Motivated by this trend, our paper presents an overview of the field of the Semantic Web in Education considering some of the main research challenges, architecture and standards, and showing how the use of ontologies can enhance the potential for making AAAL really meaningful to the learners in the SW era.
To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse—definitions of classes, relations, functions, and other objects—is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems. Definitions written in a standard format for predicate calculus are translated by a system called Ontolingua into specialized representations, including frame-based systems as well as relational languages. This allows researchers to share and reuse ontologies, while retaining the computational benefits of specialized implementations.We discuss how the translation approach to portability addresses several technical problems. One problem is how to accommodate the stylistic and organizational differences among representations while preserving declarative content. Another is how to translate from a very expressive language into restricted languages, remaining system-independent while preserving the computational efficiency of implemented systems. We describe how these problems are addressed by basing Ontolingua itself on an ontology of domain-independent, representational idioms.
Directions Please provide us with your full name. Your name will be printed on the information that is returned to you. Full Name For each of the 44 questions below select either "a" or "b" to indicate your answer. Please choose only one answer for each question. If both "a" and "b" seem to apply to you, choose the one that applies more frequently. When you are finished selecting answers to each question please select the submit button at the end of the form. I understand something better after I (a) try it out. (b) think it through. 1. I would rather be considered (a) realistic. (b) innovative. 2. When I think about what I did yesterday, I am most likely to get (a) a picture. (b) words. 3. I tend to 4.
An example is given of an inclusive learning environment built on the cornerstone of new learning technologies that is conducive to reaching students with diverse learning styles.
The aim of Semantic Web is to add machineprocessable information to the Web. Our focus is on information related to people. This problem in Semantic Web is addressed by the FOAF Vocabulary. FOAF Vocabulary describes people, their activities and the people they know. The terms defined in this vocabulary let us say general things about us and people we know. But the terms in FOAF define people generally, and for example don't let us talk about professional achievements and bring us near to specific academic communities of our interest. The entire social network is composed of communities, and we have chosen to contribute on academic community. In this article we introduce a new vocabulary, FOAF-Academic, which we have built up on the OAF vocabulary by restricting it to communication in academic communities (e.g., exclude personal data), as well as extending it were required to cover academic-specific terms and relationships (e.g., add the co-author relationship). We have described this ontology and the technologies under which it is implemented. This ontology will help the academic community in saying anything about their achievements, their qualifications, activities and the communities that are near to them, in a machine readable format in order to be processed by both human and machine.
Many challenges of bringing communicating multi-agent systems to the World Wide Web require ontologies. The integration of agent technology and ontologies could significantly affect the use of Web services and the ability to extend programs to perform tasks for users more efficiently and with less human intervention.
The e-learning system become one of main important tool in current educations, and several types of systems are proposed or developed on commercial or non-commercial base. Some of them are still remained at the level of only displaying materials and giving tests on them. There are off course some user oriented systems proposed by researchers where learners' skill or educational experiences are considered then personalized curriculum is proposed. In this paper, we consider user's consciousness and characteristic base e-learning system outline of which we have already proposed from motivation and skill perspectives by referring some learning or studying system theories.
In an advance information society, the information security related issues are very important subject to be handled in any types of companies or organizations. Some companies introduce a technology based security system in order to solve these problems, however most of information related problems many organization have been facing are caused by humans. There are many risks of becoming perpetrators as well as victims. Therefore the education on information security is very important not only for business person but also for ordinary people live in the highly information oriented society. Some Universities or Colleges have lectures on information security or ethics. However, these lectures are tend to uniform and do not address characteristics of individuals, and seemed not to be effective especially if he/she grew up in legal and social environment different from Japan. We try to construct a multilingual e-learning system for complementing such problems by reflecting individual's consciousness cultivated in their countries' environment.
Learning styles are increasingly being incorporated into technology-enhanced learning. Appropriately, a great deal of recent research work is occurring in this area. As more information and details about learning styles becomes available, learning styles can be better accommodated and integrated into all aspects of educational technology. The aim of this paper is to analyse data about learning styles with respect to the Felder-Silverman learning style model (FSLSM) in order to provide a more detailed description of learning style dimensions. The analyses show the most representative characteristics of each learning style dimension as well as how representative these characteristics are. As a result, we provide additional information about the learning style dimensions of FSLSM. This information is especially important when learning styles are incorporated in technology-enhanced learning. (Keywords: learning styles, Felder-Silverman model, data mining, student modelling.)
4MAT is an eight-step instructional cycle that capitalizes on individual learning styles and brain dominance processing preferences. The four major learners (imaginative, analytic, common sense, and dynamic) can use 4MAT to engage their whole brain. Learners use their most comfortable style while being challenged to function in less comfortable modes. Includes 13 references. (MLH)
Although learning style theory is widely accepted amongst educational theorists in the context of traditional classroom environments, there is still little research on the adaptation to individual styles in an e-learning environment. In particular the possibility of fluctuations in a learning style with changing tasks or content has not yet been addressed. The described PhD project named iWeaver was designed to provide a flexible, yet manageable environment for the learner by implementing adaptive hypermedia techniques. iWeaver draws upon the widely recognised Dunn & Dunn learning styles model and derived learning strategies. It uses database-driven JavaServer Pages, which generate 'media experiences' (e.g. interactive Flash animations or streaming audio) and other specifically developed 'learning tools' to teach the Java programming language. This paper describes the system architecture of iWeaver and gives technical details on the implementation of specific media experiences and learning tools. An approach to predict and accommodate fluctuations in a learning style profile that will be integrated in a future version of the environment is discussed.
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