Breaking the Rules: writing reflectively for yourself.

The rules which epitomise good writing may on occasions be broken, deliberately and with what the writers judge to be good purpose. This can well occur when students or staff set out to engage effectively with their personal and professional development, through personal reflection on and in experiences. They may do this in what has been called “stream of consciousness” writing, which is deliberately compiled in a manner at variance with the general rules for best practice. The rationale for such an unusual decision, namely to engage in what is frankly disorderly writing, is set out briefly in this chapter. Its characteristics are summarised, in implicit contrast with more conventional styles of writing. Examples are included of claims for the effectiveness of this style when used for developmental purposes by students and staff; and reference is made to the publications of some of those who have endorsed this approach.

Reflective writing: The student nurse's perspective on reflective writing and poetry writing.

Summary Background Reflective writing is a mandatory part of nurse education but how students develop their skills and use reflection as part of their experiential learning remains relatively unknown. Understanding reflective writing in all forms from the perspective of a student nurse is therefore important. Objectives To explore the use of reflective writing and the use of poetry in pre-registered nursing students. Design A qualitative design was employed to explore reflective writing in pre-registered nursing students. Setting A small university in Scotland. Participants BSc (Hons) Adult and Mental Health Pre-registration Student Nurses. Methods Two focus groups were conducted with 10 student nurses during March 2012. Data was analysed thematically using the framework of McCarthy (1999). Results Students found the process of reflective writing daunting but valued it over time. Current educational methods, such as assessing reflective accounts, often lead to the ‘narrative’ being watered down and the student feeling judged. Despite this, reflection made students feel responsible for their own learning and research on the topic. Some students felt the use of models of reflection constricting, whilst poetry freed up their expression allowing them to demonstrate the compassion for their patient under their care. Conclusions Poetry writing gives students the opportunity for freedom of expression, personal satisfaction and a closer connection with their patients, which the more formal approach to reflective writing did not offer. There is a need for students to have a safe and supportive forum in which to express and have their experiences acknowledged without the fear of being judged.

Writing the War on Terrorism: Language, Politics and Counter-terrorism

Jackson, Richard, Writing the War on Terrorism: Language, Politics and Counter-terrorism (Manchester: Manchester University Press, 2005), pp.viii + 232 RAE2008

Medieval Women's Writing

Watt, P., Medieval Women's Writing (Cambridge: Polity Press, 2007) RAE2008

Women writing woman: representations of gender and sexuality

Pykett, Lyn. 'Women writing woman: representations of gender and sexuality', In: Women and literature in Britain 1800 - 1900 (Cambridge: Cambridge University Press, 2001), pp.78-98, 2008. RAE2008

Writing Home : Martin Walser's Ein fliehendes Pferd as Anti-Tourist Literature

Wilkinson, Jane, 'Writing Home: Martin Walser's Ein fliehendes Pferd as Anti-Tourist Literature', Journal of Tourism and Cultural Change (2006) 4(3) pp.001-017 RAE2008

Quantitative evaluation of electron beam writing in passivated gold nanoclusters

Jenkins, Tudor; Hayton, D.J.; Bedson, T.R.; Palmer, R.E., (2001) 'Quantitative evaluation of electron beam writing in passivated gold nanoclusters', Applied Physics Letters (78) pp.1921-1923 RAE2008

BitBox!: A case study interface for teaching real-time adaptive music composition for video games

Real-time adaptive music is now well-established as a popular medium, largely through its use in video game soundtracks. Commercial packages, such as fmod, make freely available the underlying technical methods for use in educational contexts, making adaptive music technologies accessible to students. Writing adaptive music, however, presents a significant learning challenge, not least because it requires a different mode of thought, and tutor and learner may have few mutual points of connection in discovering and understanding the musical drivers, relationships and structures in these works. This article discusses the creation of ‘BitBox!’, a gestural music interface designed to deconstruct and explain the component elements of adaptive composition through interactive play. The interface was displayed at the Dare Protoplay games exposition in Dundee in August 2014. The initial proof-of- concept study proved successful, suggesting possible refinements in design and a broader range of applications.

A Two-step Statistical Approach for Inferring Network Traffic Demands (Revises Technical Report BUCS-2003-003)

Accurate knowledge of traffic demands in a communication network enables or enhances a variety of traffic engineering and network management tasks of paramount importance for operational networks. Directly measuring a complete set of these demands is prohibitively expensive because of the huge amounts of data that must be collected and the performance impact that such measurements would impose on the regular behavior of the network. As a consequence, we must rely on statistical techniques to produce estimates of actual traffic demands from partial information. The performance of such techniques is however limited due to their reliance on limited information and the high amount of computations they incur, which limits their convergence behavior. In this paper we study a two-step approach for inferring network traffic demands. First we elaborate and evaluate a modeling approach for generating good starting points to be fed to iterative statistical inference techniques. We call these starting points informed priors since they are obtained using actual network information such as packet traces and SNMP link counts. Second we provide a very fast variant of the EM algorithm which extends its computation range, increasing its accuracy and decreasing its dependence on the quality of the starting point. Finally, we evaluate and compare alternative mechanisms for generating starting points and the convergence characteristics of our EM algorithm against a recently proposed Weighted Least Squares approach.

A Quantitative Evaluation of the AVITEWRITE Model of Handwriting Learning

Much sensory-motor behavior develops through imitation, as during the learning of handwriting by children. Such complex sequential acts are broken down into distinct motor control synergies, or muscle groups, whose activities overlap in time to generate continuous, curved movements that obey an intense relation between curvature and speed. The Adaptive Vector Integration to Endpoint (AVITEWRITE) model of Grossberg and Paine (2000) proposed how such complex movements may be learned through attentive imitation. The model suggest how frontal, parietal, and motor cortical mechanisms, such as difference vector encoding, under volitional control from the basal ganglia, interact with adaptively-timed, predictive cerebellar learning during movement imitation and predictive performance. Key psycophysical and neural data about learning to make curved movements were simulated, including a decrease in writing time as learning progresses; generation of unimodal, bell-shaped velocity profiles for each movement synergy; size scaling with isochrony, and speed scaling with preservation of the letter shape and the shapes of the velocity profiles; an inverse relation between curvature and tangential velocity; and a Two-Thirds Power Law relation between angular velocity and curvature. However, the model learned from letter trajectories of only one subject, and only qualitative kinematic comparisons were made with previously published human data. The present work describes a quantitative test of AVITEWRITE through direct comparison of a corpus of human handwriting data with the model's performance when it learns by tracing human trajectories. The results show that model performance was variable across subjects, with an average correlation between the model and human data of 89+/-10%. The present data from simulations using the AVITEWRITE model highlight some of its strengths while focusing attention on areas, such as novel shape learning in children, where all models of handwriting and learning of other complex sensory-motor skills would benefit from further research.