Informatics in Education

The paper aims to present application of Educational Data Mining and particularly Case-Based Reasoning (CBR) for students profiling and further to design a personalised intelligent learning system. The main aim here is to develop a recommender system which should help the learners to create learning units (scenarios) that are the most suitable for them. First of all, systematic literature review on application of CBR and its possible implementation to personalise learning was performed in the paper. After that, methodology on CBR application to personalise learning is presented where learning styles play a dominate role as key factor in proposed personalised intelligent learning system model based on students profiling and personalised learning process model. The algorithm (the sequence of steps) to implement this model is also presented in the paper.

The paper is aimed to present a methodology of learning personalisation based on applying Resource Description Framework (RDF) standard model. Research results are two-fold: first, the results of systematic literature review on Linked Data, RDF "subject-predicate-object" triples, and Web Ontology Language (OWL) application in education are presented, and, second, RDF triples-based learning personalisation methodology is proposed. The review revealed that OWL, Linked Data, and triples-based RDF standard model could be successfully used in education. On the other hand, although OWL, Linked Data approach and RDF standard model are already well-known in scientific literature, only few authors have analysed its application to personalise learning process, but many authors agree that OWL, Linked Data and RDF-based learning personalisation trends should be further analysed. The main scientific contribution of the paper is presentation of original methodology to create personalised RDF triples to further development of corresponding OWL-based ontologies and recommender system. According to this methodology, RDF-based personalisation of learning should be based on applying students' learning styles and intelligent technologies. The main advantages of this approach are analyses of interlinks between students' learning styles according to Felder-Silverman learning styles model and suitable learning components (learning objects and learning activities). There are three RDF triples used while creating the methodology: "student's learning style - requires - suitable learning objects", "student's learning style - requires - suitable learning activities", and "suitable learning activities - require - suitable learning objects". In the last triple, "suitable learning activities" being the object in the 2nd triple, becomes the subject in the 3rd triple. The methodology is based on applying pedagogically sound vocabularies of learning components (i.e. learning objects and learning activities), experts' collective intelligence to identify learning objects and learning methods / activities that are most suitable for particular students, and intelligent technologies (i.e. ontologies and recommender system). This methodology based on applying personalised RDF triples is aimed at improving learning quality and effectiveness.

The paper aims to present research results on using Web 2.0 tools for learning personalisation. In the work, personalised Web 2.0 tools selection method is presented. This method takes into account student's learning preferences for content and communication modes tailored to the learning activities with a view to help the learner to quickly and accurately find the right educational tools, and to implement this method in prototype of knowledge-based recommender system. In the research, first of all, personalised e-learning technological peculiarities i.e. recommender systems applications for learning personalisation and those systems components were investigated. After that, selection methods for Web 2.0 tools suitable for implementing learning activities were analysed. The novel method of integrating Web 2.0 tools into personalised learning activities according to students learning styles was created, and prototype of the recommender system that implements the method proposed was developed. Finally, the expert evaluation of the developed system prototype that implements the method proposed was performed.

The paper is aimed to analyse the external expert evaluation results of eContentplus programme's iCOPER (Interoperable Content for Performance in a Competency-driven Society) project's deliverables, especially quality control and Web 2.0 technologies report. It is a suitability report for better practice concerning the use of Web 2.0 technologies and associated quality control mechanisms within the iCOPER best practice network. It aims to outline the key topics and associated standards and specifications found in this community. These illustrate a set of best practice issues for developing educational resources open for remixing and repurposing, tailored to a European dimension. Information relating to both the evidence and experience of using standards and specifications for the delivery of Web 2.0 tools in the community has also been captured. This includes an indication of the most popular technical platforms for content development, sharing and reuse with respect to the new media as well as an indication of quality control methods for them if used. The paper is also aimed to analyse the first results of Lifelong Learning Programme's (LLP) te@ch.us project. The project plans to set up a web community for teachers interested in integrating Web 2.0 in classes at school.

The paper aims to analyse several scientific approaches how to evaluate, implement or choose learning content and software suitable for personalised users/learners needs. Learning objects metadata customisation method as well as the Method of multiple criteria evaluation and optimisation of learning software represented by the experts' additive utility function are analysed in more detail. The value of the experts' additive utility function depends on the learning software quality evaluation criteria, their ratings and weights. The Method is based on the software engineering Principle which claims that one should evaluate the learning software using the two different groups of quality evaluation criteria - `internal quality' criteria defining the general software quality aspects, and `quality in use' criteria defining software personalisation possibilities. The application of the Method and Principle for the evaluation and optimisation of learning software is innovative in technology enhanced learning theory and practice. Application of the method of the experts' (decision makers') subjectivity minimisation analysed in the paper is also a new aspect in technology enhanced learning science. All aforementioned approaches propose an efficient practical instrumentality how to evaluate, design or choose learning content and software suitable for personalised learners needs.

Currently virtual learning environments (VLEs) and learning objects (LOs) repositories are under active implementation into general education and vocational training system in Lithuania. The article aims to review LOs interoperability standards development tendencies as well as to compare VLEs under existing well-developed pedagogical and technical evaluation frameworks in order to suggest the most suitable one for wider implementation to support active socio-constructivist pedagogies in in-service teacher training and overall in Lithuanian general education and vocational training systems.

Solution of the problem of optimal school scheduling is very important to make the

The study is the first attempt to systematically gather information about what is happening in research and education in the ICT field in the Baltic countries and Northwest Russia, so it is mostly a general investigation and fact-finding project, leading to possible future research and activities in the field.