Solo life to Second Life : the design of physical and virtual learning spaces inspired by the drama classroom

This paper explores the design of virtual and physical learning spaces developed for students of drama and theatre studies. What can we learn from the traditional drama workshop that will inform the design of drama and theatre spaces created in technology-mediated learning environments? The authors examine four examples of spaces created for online, distance and on-campus students and discuss the relationship between the choice of technology, the learning and teaching methods, and the outcomes for student engagement. Combining insights from two previous action research projects, the discussion focuses on the physical space used for contemporary drama workshops, supplemented by Web 2.0 technologies; a modular online theatre studies course; the blogging space of students creating a group devised play; and the open and immersive world of Second Life, where students explore 3D simulations of historical theatre sites. The authors argue that the drama workshop can be used as inspiration for the design of successful online classrooms. This is achieved by focusing on students’ contributions to the learning as individuals and group members, the aesthetics and mise-en-scene of the learning space, and the role of mobile and networked technologies. Students in this environment increase their capacity to become co-creators of knowledge and to achieve creative outcomes. The drama workshop space in its physical and virtual forms is seen as a model for classrooms in other disciplines, where dynamic, creative and collaborative spaces are required.

Learning landscapes 2.0 : warning - assembly required

Twenty first century learners operate in organic, immersive environments. A pedagogy of student-centred learning is not a recipe for rooms. A contemporary learning environment is like a landscape that grows, morphs, and responds to the pressures of the context and micro-culture. There is no single adaptable solution, nor a suite of off-the-shelf answers; propositions must be customisable and infinitely variable. They must be indeterminate and changeable; based on the creation of learning places, not restrictive or constraining spaces. A sustainable solution will be un-fixed, responsive to the life cycle of the components and materials, able to be manipulated by the users; it will create and construct its own history. Learning occurs as formal education with situational knowledge structures, but also as informal learning, active learning, blended learning social learning, incidental learning, and unintended learning. These are not spatial concepts but socio-cultural patterns of discovery. Individual learning requirements must run free and need to be accommodated as the learner sees fit. The spatial solution must accommodate and enable a full array of learning situations. It is a system not an object. Three major components: 1. The determinate landscape: in-situ concrete 'plate' that is permanent. It predates the other components of the system and remains as a remnant/imprint/fossil after the other components of the system have been relocated. It is a functional learning landscape in its own right; enabling a variety of experiences and activities. 2. The indeterminate landscape: a kit of pre-fabricated 2-D panels assembled in a unique manner at each site to suit the client and context. Manufactured to the principles of design-for-disassembly. A symbiotic barnacle like system that attaches itself to the existing infrastructure through the determinate landscape which acts as a fast growth rhizome. A carapace of protective panels, infinitely variable to create enclosed, semi-enclosed, and open learning places. 3. The stations: pre-fabricated packages of highly-serviced space connected through the determinate landscape. Four main types of stations; wet-room learning centres, dry-room learning centres, ablutions, and low-impact building services. Entirely customised at the factory and delivered to site. The stations can be retro-fitted to suit a new context during relocation. Principles of design for disassembly: material principles • use recycled and recyclable materials • minimise the number of types of materials • no toxic materials • use lightweight materials • avoid secondary finishes • provide identification of material types component principles • minimise/standardise the number of types of components • use mechanical not chemical connections • design for use of common tools and equipment • provide easy access to all components • make component size to suite means of handling • provide built in means of handling • design to realistic tolerances • use a minimum number of connectors and a minimum number of types system principles • design for durability and repeated use • use prefabrication and mass production • provide spare components on site • sustain all assembly and material information

Embedded tax liabilities and portfolio choice

his study presents an improved method of dealing with embedded tax liabilities in portfolio choice. We argue that using a risk-free discount rate is appropriate for calculating the present value of future tax liabilities. Supportive of recent research, our results found a taxation-induced preference of holding equities over bonds, and a location preference of holding equities in the taxable account and bonds in retirement accounts. These important findings contrast with traditional investment advice which suggests a greater capacity for risk in retirement accounts.

Heteroscedastic probabilistic linear discriminant analysis for manifold learning in video-based face recognition

To recognize faces in video, face appearances have been widely modeled as piece-wise local linear models which linearly approximate the smooth yet non-linear low dimensional face appearance manifolds. The choice of representations of the local models is crucial. Most of the existing methods learn each local model individually meaning that they only anticipate variations within each class. In this work, we propose to represent local models as Gaussian distributions which are learned simultaneously using the heteroscedastic probabilistic linear discriminant analysis (PLDA). Each gallery video is therefore represented as a collection of such distributions. With the PLDA, not only the within-class variations are estimated during the training, the separability between classes is also maximized leading to an improved discrimination. The heteroscedastic PLDA itself is adapted from the standard PLDA to approximate face appearance manifolds more accurately. Instead of assuming a single global within-class covariance, the heteroscedastic PLDA learns different within-class covariances specific to each local model. In the recognition phase, a probe video is matched against gallery samples through the fusion of point-to-model distances. Experiments on the Honda and MoBo datasets have shown the merit of the proposed method which achieves better performance than the state-of-the-art technique.

The OO files : providing online formative feedback on Contract Law learning in a narrative setting

Feedback, both formative and summative, enables students to reflect on their understandings and to restructure their thinking to develop their capabilities. It can also encourage positive motivation and help boost self-esteem. Online multiple choice questions can be an efficient and effective means of providing timely formative feedback. At the same time, locating learning in a narrative environment can facilitate engaging and effective learning experiences. Narratives can help learners to navigate through information and support cognitive and imaginative engagement. This article will discuss The 00 Files, an online suite of modules containing multiple choice questions situated in the narrative of a fictional law firm. It notes student responses to the program and discusses lessons that may be learnt from its development which may be of assistance to academics considering the development of similar programs for their courses.

Host selection in phytophagous insects: a new explanation for learning in adults

Insect learning can change the preferences an egg laying female displays towards different host plant species. Current hypotheses propose that learning may be advantageous in adult host selection behaviour through improved recognition, accuracy or selectivity in foraging. In this paper, we present a hypothesis for when learning can be advantageous without such improvements in adult host foraging. Specifically, that learning can be an advantageous strategy for egg laying females when larvae must feed on more than one plant in order to complete development, if the fitness of larvae is reduced when they switch to a different host species. Here, larvae benefit from developing on the most abundant host species, which is the most likely choice of host for an adult insect which increases its preference for a host species through learning. The hypothesis is formalised with a mathematical model and we provide evidence from studies on the behavioural ecology of a number of insect species which demonstrate that the assumptions of this hypothesis may frequently be fulfilled in nature. We discuss how multiple mechanisms may convey advantages in insect learning and that benefits to larval development, which have so far been overlooked, should be considered in explanations for the widespread occurrence of learning.

Insect odour perception: recognition of odour components by flower foraging moths

Odours emitted by flowers are complex blends of volatile compounds. These odours are learnt by flower-visiting insect species, improving their recognition of rewarding flowers and thus foraging efficiency. We investigated the flexibility of floral odour learning by testing whether adult moths recognize single compounds common to flowers on which they forage. Dual choice preference tests on Helicoverpa armigera moths allowed free flying moths to forage on one of three flower species; Argyranthemum frutescens (federation daisy), Cajanus cajan (pigeonpea) or Nicotiana tabacum (tobacco). Results showed that, (i) a benzenoid (phenylacetaldehyde) and a monoterpene (linalool) were subsequently recognized after visits to flowers that emitted these volatile constituents, (ii) in a preference test, other monoterpenes in the flowers' odour did not affect the moths' ability to recognize the monoterpene linalool and (iii) relative preferences for two volatiles changed after foraging experience on a single flower species that emitted both volatiles. The importance of using free flying insects and real flowers to understand the mechanisms involved in floral odour learning in nature are discussed in the context of our findings.

Can mechanism help explain insect host choice?

Evolutionary theory predicts that herbivorous insects should lay eggs on plants in a way that reflects the suitability of each plant species for larval development. Empirical studies, however, often fail to find any relationship between an adult insect’s choice of host–plant and offspring fitness, and in such cases, it is generally assumed that other ‘missing’ factors (e.g. predation, host–plant abundance, learning and adult feeding sites) must be contributing to overall host suitability. Here, I consider an alternative theory – that a fitness cost inherent in the olfactory mechanism could constrain the evolution of insect host selection. I begin by reviewing current knowledge of odour processing in the insect antennal lobe with the aid of a simple schematic: the aim being to explain the workings of this mechanism to scientists who do not have prior knowledge in this field. I then use the schematic to explore how an insect’s perception of host and non-host odours is governed by a set of processing rules, or algorithm. Under the assumptions of this mechanistic view, the perception of every plant odour is interrelated, and seemingly bad host choices can still arise as part of an overall adaptive behavioural strategy. I discuss how an understanding of mechanism can improve the interpretation of theoretical and empirical studies in insect behaviour and evolution.

Process model comprehension : the effects of cognitive abilities, learning style, and strategy

Process models are used to convey semantics about business operations that are to be supported by an information system. A wide variety of professionals is targeted to use such models, including people who have little modeling or domain expertise. We identify important user characteristics that influence the comprehension of process models. Through a free simulation experiment, we provide evidence that selected cognitive abilities, learning style, and learning strategy influence the development of process model comprehension. These insights draw attention to the importance of research that views process model comprehension as an emergent learning process rather than as an attribute of the models as objects. Based on our findings, we identify a set of organizational intervention strategies that can lead to more successful process modeling workshops.

Practical Advice to Entrepreneurs Series by ACE Adjunct Professor Dean Shepherd: Practical advice on learning the most from project failure

The author, Dean Shepherd, is of entrepreneurship—how entrepreneurs think, decide to act, and feel. He recently realized that while his publications in academic journals have implications for entrepreneurs, those implications have remained relatively hidden in the text of the articles and hidden in articles published in journals largely inaccessible to those involved in the entrepreneurial process. This series is designed to bring the practical implications of his research to the forefront.

A question of agency : applying Sen’s theory of human capability to the concept of secondary school student career ‘choice’

In this paper, we seek to operationalize Amartya Sen's concept of human capability to guide a scholarly investigation of student career choice capability. We begin by outlining factors affecting youth labour markets in Australia; a prosperous country that is affected by a ‘two-speed’ national economy. We then examine recent government initiatives that have been designed to combat youth unemployment and cyclical disadvantage by enhancing the aspirations and career knowledge of secondary school students. We argue that these policy measures are based on four assumptions: first, that career choice capability is a problem of individual agency; second, that the dissemination of career information can empower students to act as ‘consumers’ in an unequal job market; third, that agency is simply a question of will; and finally, that school education and career advice – as a means to freedom in the space of career development – is of equal quality, distribution and value to an increasingly diverse range of upper secondary school students. The paper concludes by outlining a conceptual framework capable of informing an empirical research project that aims to test these assumptions by measuring and comparing differences between groups in the range of freedom to achieve and, therefore, to choose.

Who struggles most in making a career choice and why?Findings from a cross-sectional survey of highschool students

This paper reports findings from an empirical study examining the influence of student background and educational experiences on the development of career choice capability. Secondary school students attending years 9-12 (N = 706) in New South Wales (NSW), Australia, were invited to participate in an online survey that sought to examine factors influencing their career choices. The survey included questions relating to student demographics, parental occupation, attitudes to school and to learning, student aspirations, and students’ knowledge of the further education or skills required to achieve their desired goal. We found no significant differences in the proportions of students who were “uncertain” of their future career aspirations with respect to their socio-educational background. There were, however, significantly more students struggling with career decision making from an English-speaking background in comparison to households where children spoke a language other than English. Those students were proportionally present in government and non-government schools and had some behavioural and attitudinal characteristics in common.

A threshold concepts focus to curriculum design: supporting student learning through application of variation theory

This project develops and evaluates a model of curriculum design that aims to assist student learning of foundational disciplinary ‘Threshold Concepts’. The project uses phenomenographic action research, cross-institutional peer collaboration and the Variation Theory of Learning to develop and trial the model. Two contrasting disciplines (Physics and Law) and four institutions (two research-intensive and two universities of technology) were involved in the project, to ensure broad applicability of the model across different disciplines and contexts. The Threshold Concepts that were selected for curriculum design attention were measurement uncertainty in Physics and legal reasoning in Law. Threshold Concepts are key disciplinary concepts that are inherently troublesome, transformative and integrative in nature. Once understood, such concepts transform students’ views of the discipline because they enable students to coherently integrate what were previously seen as unrelated aspects of the subject, providing new ways of thinking about it (Meyer & Land 2003, 2005, 2006; Land et al. 2008). However, the integrative and transformative nature of such threshold concepts make them inherently difficult for students to learn, with resulting misunderstandings of concepts being prevalent...

Editorial : Action research, action learning and community services

This edition of ALARj has a focus on the contribution of action learning and action research to the development of community services, particularly nonprofits. The landscape of community services has been changing rapidly in recent decades, and can be typified by the notion of complexity. Complexity in the nature of issues that services seek to respond to, complexity in the policy environment and systems of support that have tended to silo and compartmentalise problems and people, and complexity in the institutional location non-profit services occupy in ‘helping’ those who are seen as ‘in need’ or marginalised. In addition to being typified by complexity the environment in which community services are located is dynamic, undergoing profound and ongoing change as neo-liberal approaches to understanding and responding to human need, which emphasise the individualisation of risk, and market principles such as choice, competition and innovation, drive social policy. How can long held values of empowerment, care, inclusivity and benefit to individuals and communities have expression in community services as they grapple with the challenges of being viable and relevant in such a dynamically changing environment? This edition brings together a range of contributions which speak to these challenges. The thematic through these is that processes are needed which engage services and communities in ongoing processes of inquiry about how they can best proceed in contexts typified by complexity and change. Action learning and action research can provide processes of this character.

Automated classification of limb fractures from free-text radiology reports using a clinician-informed gazetteer methodology

Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.