Identifying Best Practices in Financing Next Generation Networks

Governments throughout the world have determined that next generation network (NGN) development serves the national interest. The strategies used to achieve progress vary greatly, as does the extent to which governments perceive the need to get actively involved through direct ownership or subsidization of carriers. No government has unlimited funds to invest in new networks, or to subsidize private ventures promising to improve access to essential services at affordable rates. Accordingly, nations must determine whether and how to use limited taxpayer funds to expedite the access to inexpensive and ubiquitous wired and wireless broadband networks. Baseline factors such as geography, income, demographics, and market penetration of existing networks have a significant impact on what works best. However, nations with similar physical and economic characteristics have pursued significantly different strategies. This article identifies best practices in NGN development using both case studies and a review of the current literature assessing government strategies. While it cannot confirm a theoretical basis for achieving success in NGN development, the article provides a toolkit of confirmed best practices.     

Assessing Anonymous Communication on the Internet: Policy Deliberations

Anonymous communication on the Internet offers new opportunities but has ill-understood risks. This article helps to ground the policy debates by examining some fundamental aspects of anonymous social behavior and current controversies over anonymous communications. It is a companion to the article in this issue, "Anonymous Communication Policies for the Internet: Results and Recommendations of the AAAS Conference." It examines the social character of anonymous communication and the ways that anonymous communication has played important roles for professionals such as journalists and the police. It also explains some of the new technological supports for anonymous communication on the Internet. The openness, decentralization, and transnational character of the Internet challenge the efficacy of traditional control mechanisms and have raised issues related to accountability, law enforcement, security and privacy, governmental empowerment, and e-commerce. Yet, to ban or restrict all anonymous communication online because of the harms it could bring would deny its benefits to those people who may legitimately gain from it. This article helps to understand how to balance these positions.     

New directions for lifelong learning using network technologies

The requirements placed on learning technologies to support lifelong learning differ considerably from those placed on technologies to support particular fragments of a learning lifetime. The time scales involved in lifelong learning, together with its multi‐institutional and episodic nature are not reflected in today’s mainstream learning technologies and their associated architectures. The article presents an integrated model and architecture to serve as the basis for the realisation of networked learning technologies serving the specific needs and characteristics of lifelong learners. The integrative model is called a ‘Learning Network’ (LN) and its requirements and architecture are explored, together with the ways in which its application can help in reducing barriers to lifelong learning.     

Outlier Detection in High-Stakes Certification Testing

Recent developrnents of person-Jit analysis in computerized adaptive testing (CAT) are discussed. Methods from stutistical process control are presented that have been proposed to classify an item score pattern as fitting or misjitting the underlying item response theory model in CAT. Most person-fit research in CAT is restricted to simulated data. In this study, empirical data from a certification test were used, Alternatives are discussed to generate norms so that bounds can be determined to classify an item score pattern as fitting or misfitting. Using bounds determined from a sample of a high-stakes certification test, the empirical analysis showed that dizerent types of misfit can be distinguished. Further applications using statistical process control methods to detect misfitting item score patterns are discussed.     

What can Interpersonal Process Recall (IPR) offer academic development?

Abstract

Academic development is often seen as a compliance activity, divorced from the teaching context and what teachers are trying to achieve in their classroom. In this case study, we researched Interpersonal Process Recall (IPR) as a reflective, non-judgmental approach to help tutors identify coherence between their teaching intentions and practice. Our results provided evidence that IPR helped tutors reflect on ways to improve their teaching. It also led to unexpected ‘discoveries’ not typically afforded by conventional academic development. We conclude that IPR offers a formative, teacher-focussed and contextual approach that has not been clearly defined in the literature. We offer the IPR model followed in this study for academic developers and researchers alike.     

Towards multimodal emotion recognition in e-learning environments

This paper presents a framework (FILTWAM (Framework for Improving Learning Through Webcams And Microphones)) for real-time emotion recognition in e-learning by using webcams. FILTWAM offers timely and relevant feedback based upon learner's facial expressions and verbalizations. FILTWAM's facial expression software module has been developed and tested in a proof-of-concept study. The main goal of this study was to validate the use of webcam data for a real-time and adequate interpretation of facial expressions into extracted emotional states. The software was calibrated with 10 test persons. They received the same computer-based tasks in which each of them were requested 100 times to mimic specific facial expressions. All sessions were recorded on video. For the validation of the face emotion recognition software, two experts annotated and rated participants’ recorded behaviours. Expert findings were contrasted with the software results and showed an overall value of kappa of 0.77. An overall accuracy of our software based on the requested emotions and the recognized emotions is 72%. Whereas existing software only allows not-real time, discontinuous and obtrusive facial detection, our software allows to continuously and unobtrusively monitor learners' behaviours and converts these behaviours directly into emotional states. This paves the way for enhancing the quality and efficacy of e-learning by including the learner's emotional states.