As a number of recent studies suggest applications of networked computers in education have very inconsistent results ranging from success stories to complete failures. Literally, thousands of e‑learning projects have been carried out that greatly differ in their outcomes. Until now, however, there is no systematic or a standardized way of planning, comparing and evaluating e‑learning projects, their outcomes, and their effectiveness. Therefore, the main objective of this research was an investigation of possible approaches to systematic planning, development and evaluation of e‑learning initiatives and their corresponding e‑learning projects. The result of this work is a multidimensional model of e‑learning Indicators that are defined as the important concepts and factors that are used to communicate information about the level of e‑learning and used to make management decisions when planning e‑learning strategy. The lack of knowledge of the learner audience as well as of the factors influencing that audience and e‑learning projects overall results in failing to provide satisfactory support in the decision making process. In order to address this issue, an approach dealing with e‑learning indicators is proposed. Having a standardised guide of e‑learning indicators accepted by the scientific community enables comparison and evaluation of different initiatives regarding e‑learning in a standardised manner. The proposed E‑learning Indicators Methodology enables successful planning, comparison and evaluation of different e‑learning projects. It represents an empirical methodology that gives concrete results expressed through numbers that could be analysed and later used to compare and conclude its e‑learning efficiency. A practical value of this approach was analyzed in the realized comparative analyses of two different institutions using different LMS tools: Angel and Moodle focusing on comparison and evaluation of e‑learning indicators of these two e‑learning projects. With the application of this methodology in e‑learning projects it is more likely to achieve better results and higher efficiency as well as higher Return on Investment‑ROI. 

The readwrite web, or Web 2.0, offers ways for users to personalise their online existence, and to develop their own critical identities though their control of a range of tools. Exerting control enables those users to forge new contexts, profiles and content through which to represent themselves, based upon the user‑centred, participative, social networking affordances of specific technologies. In turn these technologies enable learners to integrate their own contexts, profiles and content, in order to develop informal associations or communities of inquiry. Within educational contexts these tools enable spaces for learners to extend their own formal learning into more informal places though the fusion of web‑based tools into a task‑oriented personal learning environment. Where students are empowered to make decisions about the tools that support their personal approaches to learning, they are able develop further control over their learning experiences and move towards their own subject‑based mastery. Critically, they are able to define with whom to share their personal approaches, and how they can best connect the informal learning that occurs across their life to their formal, academic work. The personal definition or fusion of tools and tasks is afforded through individual control over the learning environment. The flowering of personal learning aims, mediated by technologies and rules of engagement, occurs within task‑specific loops where learners can interpret and process epistemological signals. In turn, where those loops are located within broader, personalised environments students can make contextual sense of their learning and extend their own educational opportunities. Moreover, they can extend their own academic decision‑making through application in other contexts, and as a result manage their own academic uncertainties. This is evidenced through a thematic study of the voices of both learners and tutors, which highlights how the readwrite web can be used proactively by educators, using specific tasks to enable learners to fuse their informal and formal learning spaces, and thereby enhance their decision‑making confidence. The structuring of learning spaces that enable users and social networks to manage their educational processes is enhanced by readwrite web approaches and tools, and in this paper is defined through a Fused Learner Integration model. 

In 2007, a small team of university and secondary school teachers jointly developed and piloted an e‑class for 4 and 5 grade students (age: 16‑17yrs) at both pre‑university and general vocational level. The goal was to develop and try out innovative ways of teaching mathematics that would enable schools to offer optional courses for small numbers of students. The e‑class can be summarized as web‑supported instruction in a blended learning approach. The instructional material consisted of the chapter on discrete dynamical models from a brand‑new mathematics textbook, supplemented by investigative activities. Students could build and simulate dynamical models with the computer learning environment Coach. Instructions for learning to work with software were given through screen casts created by the teacher to gear with students' needs and made available in the Sakai‑based virtual learning environment. Students got weekly on‑line assignments, which they submitted digi‑ tally. At home they could get assistance from peers and the teacher in a chat room. We discuss some of the e‑ ingredients of the e‑class and their potential for teaching and learning mathematics and science in terms of principled design approaches to multimedia learning and pedagogical arrangements. We report the experiences of the participants of the project and present the future plans based on this work. 

The word "wisdom" is rarely seen in contemporary technology and learning discourse. This conceptual paper aims to provide some clear principles that answer the question: How can we establish wisdom in complex learning networks? By considering the nature of contemporary calls for wisdom the paper provides a metatheoretial framework to evaluate the appropriateness of the characteristics of learning technologies in the postmodern context. By taking into account the complexities of paradox and uncertainty in contemporary life, the paper also indicates where future research would be best directed and considers how wisdom might practically be applied via use of learning technologies. 

This paper reports the observations made and experience gained from developing and delivering an online quantitative methods course for Business undergraduates. Inspired by issues and challenges experienced in developing the online course, a model is advanced to address the question of how to guide the design, development, and delivery of successful e‑learning initiatives based on theories of a user‑centered information systems development paradigm. The benefits of using the proposed model for e‑learning success assessment is demonstrated through four cycles of action research after two action research cycles of pilot study. Findings from our empirical study confirm the value of an action research methodology for promoting e‑learning success. The paper concludes with a discussion on the merits of the proposed model in furthering our understanding of how to define, assess, and promote e‑learning success. 

At present, it is difficult to assess the quality of learning in Computer‑Supported Collaborative Learning (CSCL) environments, because standard pretest and posttest measures do not capture the differences in the learner's ability to engage in the material, pose interesting new questions, engage others in learning and work collaboratively. This research investigates the impact of communication patterns, network positions and social dynamics factors on students' self‑perception of learning in a CSCL environment. The study involved a combination of methodologies combining questionnaires, and archiving of communication logs for data collection. Social network analysis tools were used to analyze relational data, map emergent student communication patterns and calculate centrality scores based on the electronic and face‑to‑face communication patterns among class members in the CSCL environment. Structural equation modeling was then performed on the hypotheses model to determine the impact of these centrality measures and the social factors on students' perceptions of knowledge gained and their satisfaction with their performance in the course.