A Virtual Environment for Distance Education and Training

The paper aims at developing a model for a Virtual Environment for Distance Education and Training (VEDET) that offers a comprehensive metaphor to be used both for humancomputer interface and instructional design purposes. It also gives a paradigm for restructuring traditional education and training by complementing them with a virtual component. Thus the VEDET would not replace the traditional school, university or training department of a organisation but rather extend their facilities and tools and make their activities more flexible and technologically enriched

Generic Arguments: a framework for supporting online deliberative discourse

In this paper we propose a framework based on argumentation that can be used to support deliberative discourse on line. Online communities have several distinct advantages as very open forums but they also have some deep disadvantages. We argue that the proposed framework and web application GAAMtalk permits and encourages the positive elements of online deliberation that will enhance discussions

Case Study of Using a Social Annotation Tool to Support Collaboratively Learning

The purpose of the study was to understand student interaction and learning supported by a collaboratively social annotation tool — Diigo. The researcher examined through a case study how students participated and interacted when learning an online text with the social annotation tool — Diigo, and how they perceived their experience. The findings suggested that students participated actively in the collaborative learning activity and were engaged in a variety of behaviors including self-reflection, elaboration, internalization, and showing support. Although students generally had a moderately positive attitude toward using the social annotation tool for collaborative learning, a few problems were identified. In particular, students found it distracting to navigate through a large amount of annotation while reading the text. The study has implications for future research on using or developing social annotation tools for educational purposes

USING SOCIAL ANNOTATIONS TO IMPROVE WEB SEARCH

Web-based tagging systems, which include social bookmarking systems such as Delicious, have become increasingly popular. These systems allow participants to annotate or tag web resources. This research examined the use of social annotations to improve the quality of web searches. The research involved three components. First, social annotations were used to index resources. Two annotation-based indexing methods were proposed: annotation based indexing and full text with annotation indexing. Second, social annotations were used to improve search result ranking. Six annotation based ranking methods were proposed: Popularity Count, Propagate Popularity Count, Query Weighted Popularity Count, Query Weighted Propagate Popularity Count, Match Tag Count and Normalized Match Tag Count. Third, social annotations were used to both index and rank resources. The result from the first experiment suggested that both static feature and similarity feature should be considered when using social annotations to re-rank search result. The result of the second experiment showed that using only annotation as an index of resources may not be a good idea. Since social Annotations could be viewed as a high level concept of the content, combining them to the content of resource could add some more important concepts to the resources. Last but not least, the result from the third experiment confirmed that the combination of using social annotations to rank the search result and using social annotations as resource index augmentation provided a promising rank of search results. It showed that social annotations could benefit web search

The design and study of pedagogical paper recommendation

For learners engaging in senior-level courses, tutors in many cases would like to pick some articles as supplementary reading materials for them each week. Unlike researchers ‘Googling’ papers from the Internet, tutors, when making recommendations, should consider course syllabus and their assessment of learners along many dimensions. As such, simply ‘Googling’ articles from the Internet is far from enough. That is, learner models of each individual, including their learning interest, knowledge, goals, etc. should be considered when making paper recommendations, since the recommendation should be carried out so as to ensure that the suitability of a paper for a learner is calculated as the summation of the fitness of the appropriateness of it to help the learner in general. This type of the recommendation is called a Pedagogical Paper Recommender.In this thesis, we propose a set of recommendation methods for a Pedagogical Paper Recommender and study the various important issues surrounding it. Experimental studies confirm that making recommendations to learners in social learning environments is not the same as making recommendation to users in commercial environments such as Amazon.com. In such learning environments, learners are willing to accept items that are not interesting, yet meet their learning goals in some way or another; learners’ overall impression towards each paper is not solely dependent on the interestingness of the paper, but also other factors, such as the degree to which the paper can help to meet their ‘cognitive’ goals.It is also observed that most of the recommendation methods are scalable. Although the degree of this scalability is still unclear, we conjecture that those methods are consistent to up to 50 papers in terms of recommendation accuracy. The experiments conducted so far and suggestions made on the adoption of recommendation methods are based on the data we have collected during one semester of a course. Therefore, the generality of results needs to undergo further validation before more certain conclusion can be drawn. These follow up studies should be performed (ideally) in more semesters on the same course or related courses with more newly added papers. Then, some open issues can be further investigated. Despite these weaknesses, this study has been able to reach the research goals set out in the proposed pedagogical paper recommender which, although sounding intuitive, unfortunately has been largely ignored in the research community. Finding a ‘good’ paper is not trivial: it is not about the simple fact that the user will either accept the recommended items, or not; rather, it is a multiple step process that typically entails the users navigating the paper collections, understanding the recommended items, seeing what others like/dislike, and making decisions. Therefore, a future research goal to proceed from the study here is to design for different kinds of social navigation in order to study their respective impacts on user behavior, and how over time, user behavior feeds back to influence the system performance

Building a semantic blog support system for gene Learning Objects on Web 2.0 environment / by Wei Yuan.

Blogging has become a popular practice on Internet in recent years, and it has been used as information publishing and participate platforms. In recent years, a style of blog called 'semantic blogs' have been introduced into the field. Semantic blogs are blogs enriched with machine-understandable metadata (Mller, Breslin, & Decker, 2005). They are an extension of regular blogs. Recently, a new web technology theory was proposed called Web 2.0. Unlike traditional web technology which only allows web users to accept information passively, Web 2.0 provides web users the option to actively modify web information. Learning Objects are digital entities deliverable over the Internet. Any number of people can access and use them simultaneously. Moreover, users can collaborate on learning objects and benefit immediately from adding their information or appending others' work to Learning Objects and share with other users over the Internet. This thesis is dedicated to the development of a semantic blog prototype for Gene Ontology annotation and navigation as a Web 2.0 support system. We are developing this semantic blog specifically because we did not find an effective system already in place that can provide support for biomedical researchers. The existing Gene Ontology systems can be classified into various categories: offline applications, client-server applications, web search engines, portals, and FTP servers. Researchers face a number of bottlenecks within the current system; all of them are based on traditional web technology with no collaboration among individual gene ontology researchers, and annotation can only be published by certain organizations. This thesis seeks the possibility to use Learning Object with Gene Ontology along with the semantic of how researchers collaborate as represented by FOAF. We have therefore introduced a new Gene ontology Annotation and navigation System. Colloquially referred to as GAS, it is based on Web 2.0 technologies with extended semantic capabilities that include Gene Ontology semantics, SCORM semantics, FOAF semantics, RSS syndication, aggregation semantics, as well as a useful and important gene ontology and annotation navigation system - Gene Ontology Navigation (GON). Our evaluation of the GAS prototype has proven to be extremely effective

Aprendizaje con dispositivos móviles para la resolución de problemas contextualizados de física en Educación Secundaria Obligatoria

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Formación de Profesorado y Educación, Departamento de Didáctica y Teoría de la Educación. Fecha de lectura: 11-09-201