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This paper aims to provide a methodological road for the next generation of e‐learning environments.

This paper considers a survey of recent publications (1995‐2002), which aim to provide practical and theoretical indications and advice, which are coupled with practical experimentations.

The paper provides road‐mapping elements, indicating the impact on services and systems to be expected by this design approach.

The survey is based on a selection of sources and it is not exhaustive. The methodology experiments that are used for argumentation are based on the authors’ platform.

The paper presents a useful source of knowledge for researchers and advanced students.

This paper identifies a road for advanced e‐learning systems, and can help researchers and those in industry who desire to introduce and understand the design methodological context of advanced e‐learning systems.

The purpose of this paper is to illustrate the advantages of using intelligent agents to facilitate the location and customization of appropriate e‐learning resources and to foster collaboration in e‐learning environments.

This paper proposes an e‐learning environment that can be used to provide customized learning. It utilizes a set of interacting agents that can personalize instruction based on an individual's prior knowledge as well as their cognitive and learning needs. The e‐learning agents monitor the e‐learning environment and improve learning and collaboration based on learners' prior knowledge, social characteristics and learning style.

E‐learning agents should allow the discovery of new learning objects more easily, allow learners to customize materials presented to improve learning outcomes, and improve collaboration in the e‐learning environment.

Little prior research has been done on the use of agents in e‐learning environments. This paper proposes a set of e‐learning agents that, if implemented in online education or training environments, should provide tangible benefits to organizations.

The purpose of this paper is to integrate previous research findings on the factors which affect e‐learning effectiveness. To do this, a model is developed which proposes that the effects of individual learner characteristics and technology characteristics on e‐learning outcomes are partially mediated by the metacognitive learning processes in which the learner engages.

A survey of 914 individuals in an online introductory information systems course examines the relations between general computer self‐efficacy (GCSE), locus of control, age, peer interaction, technology reliability, social presence, media synchronicity, and metacognitive activity and the e‐learning outcomes of course, performance, course utility, and course satisfaction.

The results indicate that GCSE, age, social presence, reliability, media synchronicity, and metacognitive activity are related to course satisfaction and utility judgments. In addition, age, metacognitive activity, and reliability are related to course performance and interaction is related to satisfaction. Finally, metacognitive activity partially mediates the relationship between social presence, media synchronicity and satisfaction, and utility judgments.

This paper represents one of the first to investigate a model of e‐learning effectiveness which integrates research on metacognitive activity as well as the role of technology and trainee characteristics.

This paper aims to present part of the work of an ongoing research project that is looking at socio‐ cultural and technological developments from a mobile technology convergence view; in order to show how culturally aware convergence developments in mobile technology can be adopted and employed for the betterment of society.

The paper presents a scenario for a mobile technology enabled learning environment in support of the conventional learning approach with a focus on enabling parental involvement and contribution to the daily learning objectives of their children and hence enhancing a quality learning experience. It further critically discusses issues of interface design – at both the device and application levels – that will have an impact on the quality of e‐learning, with a focus on mobile technology.

The paper shows how interface design can positively enhance the quality defining characteristics of learning in an e‐learning environment. Ways of achieving these characteristics of learning through effective e‐learning are reported. This is done by addressing requirements for quality‐learning through effective interface‐design considerations, towards meeting the overall quality requirements of learning that should be intrinsic to a holistic e‐learning environment. The value of human computer interaction and the critical factors of promoting productive interaction are addressed.

There are several factors affecting quality of e‐learning as a tool and approach to flexible and independent learning. The advent and use of mobile technology has been investigated in this work from a socio‐cultural and technological perspectives in two continents. The limitations lie in the depth of investigations and how far the findings can be applied to the diversity of learners.

As the effects of cultures and the rapid technological advancements take toll on teaching and learning the findings reported in this paper have far reaching implications for learners from different cultures and also for attempts at bridging existing digital divide.

The approach adopted in the research is unique by virtue of new findings and ideas presented. The paper highlights the opportunities for mobile devices and technology to play a role in the development of communities through technology aided learning (e‐learning), with a focus on e‐learning systems and technology requirements for delivering a quality learning experience.

The purpose of this paper is to study the limitations, opportunities and conditions for the development of e-learning in the inclusive education system in the universities.

The paper reviews the literature dedicated to e-learning, its application and adaptation in higher inclusive education. Systemic and social approaches were applied to the perception of higher inclusive education for the purposes of this study. The principles of evolutionary economics and institutional theory were used for determining the possibility of using e-learning in higher inclusive education. The findings are confirmed by an empirical study of the integration of e-learning into the higher inclusive education system by the example of Russia.

It has been shown that the development of e-learning in the national higher education system and its perception by the higher inclusive education system depends on the level of development of social and information interrelation in the society. In addition, e-learning can only be used in higher inclusive education when it is interrelated with traditional learning. The efficiency of e-learning in higher inclusive education depends on the systemic institutional environment which was formed both at the level of the state and at the level of a particular university. In this case, the institutional environment should be focused not only on the development of e-learning and inclusive education, but also on their collaboration.

The results of the study, which identified special aspects, opportunities and limitations of e-learning in higher inclusive education, can be applied to improve its effectiveness both at the level of individual universities and at the level of formation of national strategies for the development of higher education.

Given the growing relevance of higher inclusive education in the contemporary world and the limited number of studies of adaptation and the use of e-learning in it, the results obtained can contribute to the implementation of strategic planning of this direction at the national and local levels.

Technological improvements in broadband and distributed computing are making it possible to distribute live media content cost‐effectively. Because of this, organizations are looking into cost‐effective approaches to implement e‐Learning initiatives. Indeed, computing resources are not enough by themselves to promote better e‐Learning experiences. Hence, our goal is to share preliminary results on testing a holistic evaluation method for e‐Learning environments. To this end, we have built an experience within class dynamics using an open source Learning Virtual Environment integrated with webcast and video archive features. Our proposed evaluation method capyures user feedback by classifying it according to motivation to e‐learn in groups, since we have found this approach simpler than using classic behavioural methods. This helped us to define practical design guidelines to yield faster and more efficient e‐Learning development processes. Our results show that consistent communication both online and offline, translates into efficiency. It also dampens negative perceptions during the transition from traditional to online learning environments. These results will contribute in designing intervention strategies to optimize organizational investments in e‐Learning across user groups and contexts.

This paper aims to introduce the concepts and key issues surrounding the development of personalised learning environments.

This is a distillation of core research material gathered from a detailed literature review covering the concepts and issues surrounding the development of personalised learning environments (PLE).

This paper finds that most e‐learning applications are rather static and represent a generic approach to tutoring. Therefore, by default, they do not fully embrace learners' needs (i.e. learning styles). This paper also highlights key issues of incorporating learning styles into a PLE; and, has identified a “roadmap” for shaping and identifying the rubrics for further work in this field.

This paper is a very useful source in developing a PLE incorporating learning styles for learners.

The potentialities of information technology, together with economic concerns, have been forcing various organizations to go electronic in order to reposition themselves toward a sustainable future. This has also happened to libraries, whose primary value lies not only in their collections but also in their contribution to education through smart organization and management of collected information, which they make easily usable and accessible to users. The paper addresses these issues and discusses such aspects as what is meant by “learning”, how can it be pursued and managed in the library environment, what is the functionality of the e‐learning library, and how the e‐learning resources are included and organized in the e‐learning library.

The purpose of this paper is to provide a holistic view on e-learning-related concepts as a basis for an e-learning strategy. Furthermore, it aims to shed light on the level of application of existing open-source learning management systems (LMS) by the public and private universities of Cyprus. Due to a currently existing information gap in the field, the study should rather be seen as an exploratory descriptive snapshot to create initial awareness based on which further hypotheses can be derived for future studies.

Quantitative research has been conducted in this study with an online questionnaire distributed to all the public and private universities in Cyprus.

The conducted research analysis results clearly illustrate the comparisons among different features and services of an e-learning platform. Additionally, the analysis results highlighted the tendency of the participants toward a social learning environment which was considerably high in using social networks and other collaboration platforms, as students were more attracted to those e-learning platforms that integrate social learning elements such as various social media tools.

The only data collection method used was the online questionnaire. Even though it provided the researchers with sound and useful outcomes in a considerably short time, the validity of the results was not properly justified. The findings cannot claim to be representative. The main reason of selecting only one type of data collection method, i.e. questionnaire was the limited time of completing the research. Another significant limitation was the very low co-operation level of some of the universities under study which resulted in having less reliable results, as the response rates of some universities were merely 1 per cent.

This research study provides a comprehensive body of knowledge about LMS and e-learning, in general, within the public and private universities in Cyprus. In other terms, the results of this study enhance the existing knowledge about the e-learning features as well as demonstrating the tendency of the students toward social learning within an LMS.

The purpose of this paper is to explore the determinants of pre‐service teachers' perceived usefulness of e‐learning for teaching and learning.

A total of 189 pre‐service teachers completed a survey questionnaire measuring their responses to four constructs which explain perceived usefulness in the context of e‐learning: learning environment (LE), course delivery (CD), tutor attribute (TA), and facilitating conditions (FC). These were administered during the teaching term where participants were attending a technology course. Structural equation modeling (SEM) was employed for modeling and data analysis.

Results revealed that 62.5 percent of the total variance in the pre‐service teachers' perceived usefulness of e‐learning was explained by the four variables. Among them, learning environment did not have a significant influence on perceived usefulness. Overall, the data in this study provided evidence to support the notion that perceived usefulness is a multidimensional construct.

Perceived usefulness is often employed as an independent variable within a model (technology acceptance model) or theory (theory of planned behavior) in many acceptance studies. This study provides an alternative perspective and new insights of perceived usefulness by positioning it as a dependent variable. Methodologically, this study employed structural equation modeling as the technique to assess the effect of each of the four variables on perceived usefulness, something that conventional techniques (e.g. t‐test, ANOVA) cannot do because the latter are not capable of analyzing latent and observed indicators simultaneously.