Semantic web technology for web-based teaching and learning: A roadmap

The World-Wide Web has become the predominant platform for computer-aided instruction. Contentorientation, access and interactive features have made the Web a successful technology. The Web, however, is still evolving. We expect in particular Semantic Web technology to substantially impact Web-based teaching and learning. In this paper, we examine the potential of this technology and how we expect it to influence content representation and the work of the instructor and the learner

The effect of using facebook markup language (fbml) for designing an e-learning model in higher education

This study examines the use of Facebook Markup Language (FBML) to design an e-learning model to facilitate teaching and learning in an academic setting. The qualitative research study presents a case study on how, Facebook is used to support collaborative activities in higher education. We used FBML to design an e-learning model called processes for e-learning resources in the Specialist Learning Resources Diploma (SLRD) program. Two groups drawn from the SLRD program were used; First were the participants in the treatment group and second in the control group. Statistical analysis in the form of a t-test was used to compare the dependent variables between the two groups. The findings show a difference in the mean score between the pre-test and the post-test for the treatment group (achievement, the skill, trends). Our findings suggest that the use of FBML can support collaborative knowledge creation and improved the academic achievement of participatns. The findings are expected to provide insights into promoting the use of Facebook in a learning management system (LMS).Comment: Mohammed Amasha, Salem Alkhalaf, "The Effect of using Facebook Markup Language (FBML) for Designing an E-Learning Model in Higher Education". International Journal of Research in Computer Science, 4 (5): pp. 1-9, January 201

Language technologies and the evolution of the semantic web

The availability of huge amounts of semantic markup on the Web promises to enable a quantum leap in the level of support available to Web users for locating, aggregating, sharing, interpreting and customizing information. While we cannot claim that a large scale Semantic Web already exists, a number of applications have been produced, which generate and exploit semantic markup, to provide advanced search and querying functionalities, and to allow the visualization and management of heterogeneous, distributed data. While these tools provide evidence of the feasibility and tremendous potential value of the enterprise, they all suffer from major limitations, to do primarily with the limited degree of scale and heterogeneity of the semantic data they use. Nevertheless, we argue that we are at a key point in the brief history of the Semantic Web and that the very latest demonstrators already give us a glimpse of what future applications will look like. In this paper, we describe the already visible effects of these changes by analyzing the evolution of Semantic Web tools from smart databases towards applications that harness collective intelligence. We also point out that language technology plays an important role in making this evolution sustainable and we highlight the need for improved support, especially in the area of large-scale linguistic resources

Reusing adaptation strategies in adaptive educational hypermedia systems

Due to the difficulty and thus effort and expenses involved in creating them, personalization strategies in learning environments have to demonstrate a higher return-on-investment (ROI), if they are to be a viable component of the learning setting of the future. One feature that can increase this ROI is the reusability of adaptation strategies in Adaptive Educational Hypermedia Systems. This research looks into various ways of enhancing this reusability. Using multiple modular adaptation strategies (MAS) with a controlling meta-strategy is proposed as a more efficient way of authoring adaptation strategies. This renders the reuse of adaptation strategies faster and easier for course authors. A method for semi-automatically breaking down complex adaptation strategies into smaller modular adaptation strategies is described. Potential problems with using multiple strategies are described and ways to solve them are discussed. Finally, some evaluation points are illustrated, conclusions are drawn and further research areas are identified