Advances in information and communication technologies have contributed to the increasing use of virtual learning environments as support tools in teaching and learning processes. Virtual platforms generate a large volume of educational data, and the analysis of this data allows useful information discoveries to improve learning and assist institutions in reducing disqualifications and dropouts in distance education courses. This article presents the results of a systematic mapping study aiming to identify how educational data mining, learning analytics, and collaborative groups have been applied in distance education environments. Articles were searched from 2010 to June 2020, initially resulting in 55,832 works. The selection of 51 articles for complete reading in order to answer the research questions considered a group of inclusion and exclusion criteria. Main results indicated that 53% of articles (27/51) offered intelligent services in the field of distance education, 47% (24/51) applied methods and analysis techniques in distance education environments, 21% (11/51) applied methods and analysis techniques focused on virtual learning environments logs, and 5% (3/51) presented intelligent collaborative services for identification and creation of groups. This article also identified research interest clusters with highlights for the terms recommendation systems, data analysis, e-learning, educational data mining, e-learning platform and learning management system.
While virtual learning environments (VLEs) present several advantages, such as space-time flexibility, they are still not including proper opportunities and resources for students to engage in collaborative activities with their peers. Recent approaches, for example, are based on resources that are not standard for VLEs or usual for students. Thus, their integration with VLEs is not simple. This paper conducted a theoretical investigation to identify strategies that could induce collaborative behaviours in students. These strategies were implemented as learning objects running in a VLE and a quasi-experimental research design was conducted with 133 students. The results show that the approach promotes collaborative interactions between students and also tend to improve their learning outcomes. Moreover, learning objects use a conceptualization that is already established over the e-learning community, simplifying their integration with VLEs.
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.
Many factors influence teaching nowadays. Numbers of students are increasing, some students pay for studies and require more flexible teaching, more students have access to Internet, the learning material is changing rapidly (especially of subjects, related to information technologies), publishing industry is slow and expensive. All that stimulates usage of modern technologies in education. Virtual Learning Environments (VLEs) is one of the forms of e-learning. They open new ways of teaching and communication such as management of online learning, course delivery mechanism, communication and assessment tools, student tracking, access to electronic resources, etc. All these means correspond to the needs of contemporary teachers and students. VLEs have primarily been used for distance education but they are being used increasingly as supplement of traditional classroom based education. The author is interested in this latter aspect of VLEs.
The paper briefly reviews main types of Virtual Learning Environments and analyses the use of VLEs in Lithuania. The results of the investigation of two different learning environments - traditional (Web CT) and collaborative (FLE3) at the Vilnius Pedagogical University are also discussed in the article.