Online we are all able bodied : Online psychological sense of community and social support found through membership of disability-specific websites promotes well-being for people living with a physical disability

People with a physical disability are a population who for a number of reasons may be vulnerable to social isolation. Research into Internet-based support sites has found that social support and an online sense of community can be developed through computer mediated communication channels. This study aims to gain an understanding of the benefits that membership of disability-specific online communities may have for people with a physical disability. An online survey was administered to a sample of users of such sites (N = 160). Results indicated that users did receive moral support and personal advice through participating in such online communities. Further, results indicated that online social support and feeling a sense of community online were positively associated with participants' well-being in the areas of personal relations and personal growth.

Beware of geeks bearing gifts? Online latent and untapped outlets for farmers' markets in South East Wales

This chapter sets out to identify related issues surrounding the use of Information and Computer Technology (ICT) in developing relationships between local food producers and consumers (both individuals and businesses). Three surveys were conducted in South- East Wales to consider the overlapping issues. The first concerned the role of ICT in relationships between farmers’ market (FMs) vendors and their traditional customers. The second survey examined potential new markets for farmers in the propensity of restaurants and hotels to buy locally, the types and sources of purchases made and the modes of advertising of these businesses. The final survey focused on the potential to expand local web- based selling of farmers’ produce in the future, by examining the potential market of high ICT- use small hotels. Despite the development of tailored ICT facilities, farmers’ market vendors and current individual customers are antipathetic to them. In addition, whilst there is a desire for more local produce particularly amongst independent local restaurants and hotels, this has not been capitalised upon and there is much work to be done even amongst high ICT-use small hotels, to expand the range and scope of farmers’ markets. This raises the need for creation and utilisation of enhanced logistics, payment and marketing management capacity available through a web- based presence, linked to promotion of FMs in business- to- business (B2B) links with local restaurants and hotels. This linked quantitative research highlights the potential value in substantial development of both web portals and supporting logistics to exploit this potential in the future.

Developing shared understandings of standards-based assessment : online moderation practices across geographically diverse contexts

This thesis investigates the place of online moderation in supporting teachers to work in a system of standards-based assessment. The participants of the study were fifty middle school teachers who met online with the aim of developing consistency in their judgement decisions. Data were gathered through observation of the online meetings, interviews, surveys and the collection of artefacts. The data were viewed and analysed through sociocultural theories of learning and sociocultural theories of technology, and demonstrates how utilising these theories can add depth to understanding the added complexity of developing shared meaning of standards in an online context. The findings contribute to current understanding of standards-based assessment by examining the social moderation process as it acts to increase the reliability of judgements that are made within a standards framework. Specifically, the study investigates the opportunities afforded by conducting social moderation practices in a synchronous online context. The study explicates how the technology affects the negotiation of judgements and the development of shared meanings of assessment standards, while demonstrating how involvement in online moderation discussions can support teachers to become and belong within a practice of standards-based assessment. This research responds to a growing international interest in standards-based assessment and the use of social moderation to develop consistency in judgement decisions. Online moderation is a new practice to address these concerns on a systemic basis.

Managing the online news revolution : the UK experience

Newspapers and, if to a lesser extent as yet, linear broadcast news providers on TV and radio are in the process of being replaced as the dominant carrier media of journalism by an emerging network of online outlets.

Building support for learning within a Doctor of Education programme

Professional doctorates were introduced in the 1990s for practitioners to research ‘real-world’ problems relevant to their respective workplace communities and contexts. An array of difficulties faces professional doctoral students as they transition from professionals to practitioner researchers. This study sought to understand the learning journey of a cohort of students at an Australian university and to assess whether the cohort approach provided the necessary support for students to reach their scholarly destinations. Throughout the first 18 months of the programme, focus group interviews and surveys were conducted to gauge students’ experiences and to evaluate developments for support within the programme. Utilising a socio-cultural perspective helped identify and explain the importance of shared practice in fostering learning, the development of academic and researcher identities, and the role of communities of practice. Challenges of managing time and overcoming the professional and academe divide were facilitated by the evolving developments of the programme.

“Teaching them a lesson?” : a qualitative exploration of underlying motivations for driver aggression

Aggressive driving is increasingly a concern for drivers in highly motorised countries. However, the role of driver intent in this behaviour is problematic and there is little research on driver cognitions in relation to aggressive driving incidents. In addition, while drivers who admit to behaving aggressively on the road also frequently report being recipients of similar behaviours, little is known about the relationship between perpetration and victimisation or about how road incidents escalate into the more serious events that feature in capture media attention. The current study used qualitative interviews to explore driver cognitions and underlying motivations for aggressive behaviours on the road. A total of 30 drivers aged 18-49 years were interviewed about their experiences with aggressive driving. A key theme identified in responses was driver aggression as an attempt to manage or modify the behaviour of other road users. Two subthemes were identified and appeared related to separate motivations for aggressive responses: ‘teaching them a lesson’ referred to situations where respondents intended to convey criticism or disapproval, usually of unintended behaviours by the other driver, and thus encourage self-correction; and ‘justified retaliation’ which referred to situations where respondents perceived deliberate intent on the part of the other driver and responded aggressively in return. Mildly aggressive driver behaviour appears to be common. Moreover such behaviour has a sufficiently negative impact on other drivers that it may be worth addressing because of its potential for triggering retaliation in kind or escalation of aggression, thus compromising safety.

Learning and teaching from the edge to centre stage : Critical factors in embedding sustainable university-wide engagement in external awards and grants funding initiatives.

Teaching awards, grants and fellowships are strategies used to recognise outstanding contributions to learning and teaching, encourage innovation, and to shift learning and teaching from the edge to centre stage. Examples range from school, faculty and institutional award and grant schemes to national schemes such as those offered by the Australian Learning and Teaching Council (ALTC), the Carnegie Foundation for the Advancement of Teaching in the United States, and the Fund for the Development of Teaching and Learning in higher education in the United Kingdom. The Queensland University of Technology (QUT) has experienced outstanding success in all areas of the ALTC funding since the inception of the Carrick Institute for Learning and Teaching in 2004. This paper reports on a study of the critical factors that have enabled sustainable and resilient institutional engagement with ALTC programs. As a lens for examining the QUT environment and practices, the study draws upon the five conditions of the framework for effective dissemination of innovation developed by Southwell, Gannaway, Orrell, Chalmers and Abraham (2005, 2010): 1. Effective, multi-level leadership and management 2. Climate of readiness for change 3. Availability of resources 4. Comprehensive systems in institutions and funding bodies 5. Funding design The discussion on the critical factors and practical and strategic lessons learnt for successful university-wide engagement offer insights for university leaders and staff who are responsible for learning and teaching award, grant and associated internal and external funding schemes.

Optimal online prediction in adversarial environments

In many prediction problems, including those that arise in computer security and computational finance, the process generating the data is best modelled as an adversary with whom the predictor competes. Even decision problems that are not inherently adversarial can be usefully modeled in this way, since the assumptions are sufficiently weak that effective prediction strategies for adversarial settings are very widely applicable.

Optimal online prediction in adversarial environments

In many prediction problems, including those that arise in computer security and computational finance, the process generating the data is best modelled as an adversary with whom the predictor competes. Even decision problems that are not inherently adversarial can be usefully modeled in this way, since the assumptions are sufficiently weak that effective prediction strategies for adversarial settings are very widely applicable.

Online discovery of similarity mappings

We consider the problem of choosing, sequentially, a map which assigns elements of a set A to a few elements of a set B. On each round, the algorithm suffers some cost associated with the chosen assignment, and the goal is to minimize the cumulative loss of these choices relative to the best map on the entire sequence. Even though the offline problem of finding the best map is provably hard, we show that there is an equivalent online approximation algorithm, Randomized Map Prediction (RMP), that is efficient and performs nearly as well. While drawing upon results from the "Online Prediction with Expert Advice" setting, we show how RMP can be utilized as an online approach to several standard batch problems. We apply RMP to online clustering as well as online feature selection and, surprisingly, RMP often outperforms the standard batch algorithms on these problems.

Implicit online learning

Online learning algorithms have recently risen to prominence due to their strong theoretical guarantees and an increasing number of practical applications for large-scale data analysis problems. In this paper, we analyze a class of online learning algorithms based on fixed potentials and nonlinearized losses, which yields algorithms with implicit update rules. We show how to efficiently compute these updates, and we prove regret bounds for the algorithms. We apply our formulation to several special cases where our approach has benefits over existing online learning methods. In particular, we provide improved algorithms and bounds for the online metric learning problem, and show improved robustness for online linear prediction problems. Results over a variety of data sets demonstrate the advantages of our framework.