Organic.Edunet Web Portal: User Satisfaction Analysis

The Organic.Edunet Web portal is a multilingual federation of educational repositories, developed in order to enhance the availability and retrieval of quality educational resources about Organic Agriculture (OA) and Agroecology (AE). This paper presents the results of an online survey that took place from March to August 2010 in order to evaluate the user satisfaction from the Organic.Edunet Web portal. A standard methodology was followed in this survey, which was based on the WebQual questionnaire with the required modifications. The collected results were analyzed and statistically processed in order to lead to the corresponding conclusions

Studying How E-Markets Evaluation Can Enhance Trust in Virtual Business Communities

One of the major drawbacks of conducting business online is the raised level of risk associated with business transactions. Potential business partners usually have limited information about each others reliability or product / service quality before an online transaction. In this paper, we focus on the problem of selecting a trustful electronic market (e-market), in order to perform business transactions with it. In particular, we examine how the decision of selecting an appropriate e-market can be facilitated by an e-market recommendation algorithm. For this purpose, a metadata model for collecting and storing e-market evaluations from the members of a virtual business community in a reusable and interoperable manner is introduced. Then, an e-market recommendation algorithm that can synthesize existing e-market evaluations stored using the metadata model, is designed. Finally, a scenario of how the presented e-market recommendation algorithm can support a virtual agribusiness community of the organic agriculture sector is discussed.E-market, metadata, recommender system, virtual community, Institutional and Behavioral Economics, Marketing,

Layered evaluation of multi-criteria collaborative filtering for scientific paper recommendation

Recommendation algorithms have been researched extensively to help people deal with abundance of information. In recent years, the incorporation of multiple relevance criteria has attracted increased interest. Such multi-criteria recommendation approaches are researched as a paradigm for building intelligent systems that can be tailored to multiple interest indicators of end-users – such as combinations of implicit and explicit interest indicators in the form of ratings or ratings on multiple relevance dimensions. Nevertheless, evaluation of these recommendation techniques in the context of real-life applications still remains rather limited. Previous studies dealing with the evaluation of recommender systems have outlined that the performance of such algorithms is often dependent on the dataset – and indicate the importance of carrying out careful testing and parameterization. Especially when looking at large scale datasets, it becomes very difficult to deploy evaluation methods that may help in assessing the effect that different system components have to the overall design. In this paper, we study how layered evaluation can be applied for the case of a multi-criteria recommendation service that we plan to deploy for paper recommendation using the Mendeley dataset. The paper introduces layered evaluation and suggests two experiments that may help assess the components of the envisaged system separately. Keywords: Recommender systems; Multi-Criteria Decision Making (MCDM); Evaluatio

A Survey of Greek Agricultural E-Markets

The role that information technology plays in today’s business activities has led to an increase in firms using and/or deploying e-markets online. This development undoubtedly affects the agri-food sector, since a large number of agricultural firms are demonstrating or are expected to demonstrate e-commerce activities. This paper aims to provide an overview of the current status of agricultural e-markets in Greece, by presenting results from an analysis of 100 cases. Results indicate that Greek e-markets may still have a rather low degree of sophistication, but they demonstrate a strong B2B orientation, as well as an outreach for international customer bases.Internet, e-commerce, e-markets, agriculture, agri-food sector, survey, Consumer/Household Economics, Marketing,

Evaluating a Personal Learning Environment for Digital Storytelling

The evaluation of flexible and personal learning environments is extremely challenging. It should not be limited to the assessment of products, but should address the quality of educative experience with close monitoring. The evaluation of a PLE using digital storytelling is even more complicated, due to the unpredictability of the usage scenarios. This paper presents an evaluation methodology for PLEs using digital storytelling, using a participatory design approach. The results from an open validation trial indicate that this methodology is able to incorporate all necessary factors and that the selected evaluation tools are appropriate for addressing the quality of educative experience

Training resources and e-Government services for rural SMEs : the rural inclusion platform

Rural Inclusion, a project supported by the Information and Communication Technologies Policy Support Programme of the European Commission, aims to adopt, adapt, and deploy a Web infrastructure, in rural settings, combining semantics with a collaborative training and networking approach, offering e-Government services that will be supported by a rigorous and reusable service process analysis and modeling, and facilitating the disambiguation of the small businesses needs and requirements when trying to carry out the particular transactions. This paper, presents an overview of the architecture of RuralObservatory2.0 which will play the critical role of training content and eGovernment services repository of the overall Rural Inclusion platform.</jats:p

Preface to Proceedings of the 1st Workshop on Recommender Systems in Technology Enhanced Learning (RecSysTEL 2010)

AbstractTechnology enhanced learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of both individuals and organisations. It is an application domain that generally addresses all types of technology research & development aiming to support teaching and learning activities. Information retrieval is a pivotal activity in TEL, and the deployment of recommender systems has attracted increased interest during the past years.Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. There are plenty of resources available on the Web, both in terms of digital learning content and people resources (e.g. other learners, experts, tutors) that can be used to facilitate teaching and learning tasks. The challenge is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.The 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL) builds upon the tradition of a series of workshops on Social Information Retrieval for Technology Enhanced Learning (SIRTEL), Context-Aware Recommendation for Learning and Towards User Modelling and Adaptive Systems for All (TUMAS-A)a. RecSysTEL was organised jointly by the 4th ACM Conference on Recommender Systems (RecSys 2010) and the 5th European Conference on Technology Enhanced Learning (EC-TEL 2010), on 29–30 September 2010 in Barcelona, Spain. Its main goal was to bring together researchers and practitioners who are working on topics related to the design, development and testing of recommender systems in educational settings as well as present the current status of research in this area and create cross-disciplinary liaisons between the RecSys and ECTEL communities. Overall, its contributions outline the rich potential of TEL as an application area for recommender systems and identify the challenges of developing such systems in a TEL context

Proceedings of the 3rd Workshop on Social Information Retrieval for Technology-Enhanced Learning

Learning and teaching resource are available on the Web - both in terms of digital learning content and people resources (e.g. other learners, experts, tutors). They can be used to facilitate teaching and learning tasks. The remaining challenge is to develop, deploy and evaluate Social information retrieval (SIR) methods, techniques and systems that provide learners and teachers with guidance in potentially overwhelming variety of choices. The aim of the SIRTEL’09 workshop is to look onward beyond recent achievements to discuss specific topics, emerging research issues, new trends and endeavors in SIR for TEL. The workshop will bring together researchers and practitioners to present, and more importantly, to discuss the current status of research in SIR and TEL and its implications for science and teaching

Online sharing educational content on biodiversity topics: a case study from organic agriculture and agroecology

E-Learning Technologies and Standards are emerging as the dominant way to make educational content widely available. Approaches to these technologies should be domain-independent and easily adaptable to different contexts. Organic.Edunet aims at making content on Organic Agriculture and Agroecology widely available through a single point of reference. To achieve this, the project has adopted and adapted Open Software solutions and has built upon them to offer the Organic.Edunet Web Federation Portal and the Repository Suite of Tools. This paper presents the tools that were developed in the frame of Organic.Edunet project, serving as a guide for all individuals that aim at establishing similar tools in a field such as the biodiversity