Paving for diverse pathways : using industry-linked learning to support Performing Arts students in their transition to protean careers

Statistics presented in Australia Council reports such as Don’t Give Up Your Day Job (2003), and Artswork: A Report On Australians Working in the Arts 1 and 2 (1997, 2005), and in other studies on destinations for Performing Arts graduates, demonstrate the diversity of post-graduation pathways for our students, the prevalence of protean careers, and the challenges in developing a sense of professional identity in a context where a portfolio of work across performance making, producing, administration and teaching can make it difficult for young artists to establish career status and capital in conventional terms (cf. Dawn Bennett, “Academy and the Real World: Developing Realistic Notions of Career in the Performing Arts”, Arts & Humanities in Higher Education, 8.3, 2009). In this panel, academics from around Australia will consider the ways in which Drama, Theatre and Performance Studies as a discipline is deploying a variety of practical, professional and work-integrated teaching and learning activities – including performance-making projects, industry projects, industry placements and student-initiated projects – to connect students with the networks, industries and professional pathways that will support their progression into their career. The panellists include Bree Hadley (Queensland University of Technology), Meredith Rogers (La Trobe University), Janys Hayes (Woolongong University) and Teresa Izzard (Curtin University). The panelists will present insights into the activities they have found successful, and address a range of questions, including: How do we introduce students to performance-making and / or producing models they will be able to employ in their future practice, particularly in light of the increasingly limited funds, time and resources available to support students’ participation in full-scale productions under the stewardship of professional artists?; How and when do we introduce students to industry networks?; How do we cater for graduates who will work as performers, writers, directors or administrators in the non-subsidised sector, the subsidised sector, community arts and education?; How do we category cater for graduates who will go on to pursue their work in a practice-as-research context in a Higher Degree?; How do we assist graduates in developing a professional identity? How do we assist graduates in developing physical, professional and personal resilience?; How do we retain our connections with graduates as part of their life-long learning?; Do practices and processes need to differ for city or regionally based / theoretically or practically based degree programs?; How do our teaching and learning activities align with emergent policy and industrial frameworks such as the shift to the “Producer Model” in Performing Arts funding, or the new mentorship, project, production and enterprise development opportunities under the Australia Council for the Arts’ new Opportunities for Young and Emerging Artists policy framework?

Working together for Toby : early childhood student teachers engaging in collaborative problem-based learning around child abuse and neglect

Early childhood teacher education programs have a responsibility, amongst many, to prepare teachers for decision-making on real world issues, such as child abuse and neglect. Their repertoire of skills can be enhanced by engaging with others, either face-to-face or online, in authentic problem-based learning. This paper draws on a study of early childhood student teachers who engaged in an authentic learning experience, which was to consider and to suggest how they would act upon a real-life case of child abuse encountered in an early childhood classroom in Queensland. This was the case of Toby (a pseudonym), who was suspected of being physically abused at home. Students drew upon relevant legislation, policy and resource materials to tackle Toby’s case. The paper provides evidence of students grappling with the complexity of a child abuse case and establishing, through collaboration with others, a proactive course of action. The paper has a dual focus. First, it discusses the pedagogical context in which early childhood student teachers deal with issues of child abuse and neglect in the course of their teacher education program. Second, it examines evidence of students engaging in collaborative problem-solving around issues of child abuse and neglect and teachers’ responsibilities, both legal and professional, to the children and families they work with. Early childhood policy-makers, practitioners and teacher educators are challenged to consider how early childhood teachers are best equipped to deal with child protection and early intervention.

Nonverbal Learning Disability explained : the link to shunted hydrocephalus

A Nonverbal Learning Disability is believed to be caused by damage, disorder or destruction of neuronal white matter in the brain’s right hemisphere and may be seen in persons experiencing a wide range of neurological diseases such as hydrocephalus and other types of brain injury (Harnadek & Rourke 1994). This article probes the relationship between shunted hydrocephalus and Nonverbal Learning Disability. Description of hydrocephalus and intelligence associated with hydrocephalus concludes with explication of the ‘final common pathway’ that links residual damage caused by the hydrocephalic condition to a Nonverbal Learning Disability (Rourke & Del Dotto 1994, p. 37). The paper seeks to assist teachers, teacher aides, psychologists, guidance officers, support workers, parents and disability service providers whose role is to understand and advocate for individuals with shunted hydrocephalus and spina bifida.

Byron's back from the dead? : revenants of Romanticism in contemporary young adult fiction

Often identified as the origin of today’s children’s literature, Romanticism offers a particular context for interrogating boundaries between child and adult. Since the turn of the nineteenth century, however, Western society has “invented” the teenager to figure and to police the boundary between childhood and adulthood. In due course, twenty-first-century young adult (YA) novels such as Susan Davis’s Mad, Bad and Totally Dangerous (2004) and Cara Lockwood’s Wuthering High: A Bard Academy Novel (2006) have combined the Romantic and the adolescent in narratives which turn on supernatural invocation of Romantic authors as “really” present in contemporary adolescent lives. These novels tell stories of adolescence in which the self comes to be known via embodied encounters with dead authors, in particular, with Byron. Where “Byron scholarship has worked hard to disassociate the poet from this kind of pop-Gothic depiction, seeing it as the inevitable but regrettable offspring of nineteenth-century Byromania” (McDayter 30), contemporary YA fiction suggests that it is precisely via pop-Gothic depictions that today’s adolescents may first come to know the Romantic in general and the Byronic in particular. This paper reads these novels in the context of current anxieties about cultural illiteracy and educational “failure” in order to consider what work is being undertaken in the name of Byron, and to shed light on the ways in which cultural education may be taking place far beyond the realms of schools or cemeteries for today’s young readers.

Preparing quality teachers : making learning visible

Teacher quality is recognised as a lynchpin for education reforms internationally, and both Federal and State governments in Australia have turned their attention to teacher education institutions: the starting point for preparing quality teachers. Changes to policy and shifts in expectations impact on Faculties of Education, despite the fact that little is known about what makes a quality teacher preparation program effective. New accountability measures, mandated Professional Standards, and proposals to test all graduates before registration, mean that teacher preparation programs need capacity for flexibility and responsiveness. The risk is that undergraduate degree programs can become ‘patchwork quilts’ with traces of the old and new stitched together, sometimes at the expense of coherence and integrity. This paper provides a roadmap used by one large Faculty of Education in Queensland for reforming and reconceptualising the curriculum for a 4-year undergraduate program, in response to new demands from government and the professional bodies.

Matching cognitive styles to computer-based instruction : an approach for enhanced learning in electrical engineering

An approach aimed at enhancing learning by matching individual students' preferred cognitive styles to computer-based instructional (CBI) material is presented. This approach was used in teaching some components of a third-year unit in an electrical engineering course at the Queensland University of Technology. Cognitive style characteristics of perceiving and processing information were considered. The bimodal nature of cognitive styles (analytic/imager, analytic/verbalizer, wholist/imager and wholist/verbalizer) was examined in order to assess the full ramification of cognitive styles on learning. In a quasi-experimental format, students' cognitive styles were analysed by cognitive style analysis (CSA) software. On the basis of the CSA results the system defaulted students to either matched or mismatched CBI material. The consistently better performance by the matched group suggests potential for further investigations where the limitations cited in this paper are eliminated. Analysing the differences between cognitive styles on individual test tasks also suggests that certain test tasks may better suit certain cognitive styles.

Personalizing the design of computer-based instruction to enhance learning

This paper reports two studies designed to investigate the effect on learning outcomes of matching individuals' preferred cognitive styles to computer-based instructional (CBI) material. Study 1 considered the styles individually as Verbalizer, Imager, Wholist and Analytic. Study 2 considered the bi-dimensional nature of cognitive styles in order to assess the full ramification of cognitive styles on learning: Analytic/Imager, Analytic/ Verbalizer, Wholist/Imager and the Wholist/Verbalizer. The mix of images and text, the nature of the text material, use of advance organizers and proximity of information to facilitate meaningful connections between various pieces of information were some of the considerations in the design of the CBI material. In a quasi-experimental format, students' cognitive styles were analysed by Cognitive Style Analysis (CSA) software. On the basis of the CSA result, the system defaulted students to either matched or mismatched CBI material by alternating between the two formats. The instructional material had a learning and a test phase. Learning outcome was tested on recall, labelling, explanation and problem-solving tasks. Comparison of the matched and mismatched instruction did not indicate significant difference between the groups, but the consistently better performance by the matched group suggests potential for further investigations where the limitations cited in this paper are eliminated. The result did indicate a significant difference between the four cognitive styles with the Wholist/Verbalizer group performing better then all other cognitive styles. Analysing the difference between cognitive styles on individual test tasks indicated significant difference on recall, labelling and explanation, suggesting that certain test tasks may suit certain cognitive styles.

Sequential nonlinear manifold learning

The computation of compact and meaningful representations of high dimensional sensor data has recently been addressed through the development of Nonlinear Dimensional Reduction (NLDR) algorithms. The numerical implementation of spectral NLDR techniques typically leads to a symmetric eigenvalue problem that is solved by traditional batch eigensolution algorithms. The application of such algorithms in real-time systems necessitates the development of sequential algorithms that perform feature extraction online. This paper presents an efficient online NLDR scheme, Sequential-Isomap, based on incremental singular value decomposition (SVD) and the Isomap method. Example simulations demonstrate the validity and significant potential of this technique in real-time applications such as autonomous systems.

A statistical framework for natural feature representation

This paper presents a robust stochastic framework for the incorporation of visual observations into conventional estimation, data fusion, navigation and control algorithms. The representation combines Isomap, a non-linear dimensionality reduction algorithm, with expectation maximization, a statistical learning scheme. The joint probability distribution of this representation is computed offline based on existing training data. The training phase of the algorithm results in a nonlinear and non-Gaussian likelihood model of natural features conditioned on the underlying visual states. This generative model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The instantiated likelihoods are expressed as a Gaussian mixture model and are conveniently integrated within existing non-linear filtering algorithms. Example applications based on real visual data from heterogenous, unstructured environments demonstrate the versatility of the generative models.

Learning articulated motion structures with Bayesian Networks

This paper presents a general methodology for learning articulated motions that, despite having non-linear correlations, are cyclical and have a defined pattern of behavior Using conventional algorithms to extract features from images, a Bayesian classifier is applied to cluster and classify features of the moving object. Clusters are then associated in different frames and structure learning algorithms for Bayesian networks are used to recover the structure of the motion. This framework is applied to the human gait analysis and tracking but applications include any coordinated movement such as multi-robots behavior analysis.

Applying ISOMAP to the learning of hyperspectral image

In this paper, we present the application of a non-linear dimensionality reduction technique for the learning and probabilistic classification of hyperspectral image. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. It gives much greater information content per pixel on the image than a normal colour image. This should greatly help with the autonomous identification of natural and manmade objects in unfamiliar terrains for robotic vehicles. However, the large information content of such data makes interpretation of hyperspectral images time-consuming and userintensive. We propose the use of Isomap, a non-linear manifold learning technique combined with Expectation Maximisation in graphical probabilistic models for learning and classification. Isomap is used to find the underlying manifold of the training data. This low dimensional representation of the hyperspectral data facilitates the learning of a Gaussian Mixture Model representation, whose joint probability distributions can be calculated offline. The learnt model is then applied to the hyperspectral image at runtime and data classification can be performed.

Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.

Animateur : participatory studio-based learning in computer graphics animation

The impact of digital technology within the creative industries has brought with it a range of new opportunities for collaborative, cross-disciplinary and multi-disciplinary practice. Along with these opportunities has come the need to re-evaluate how we as educators approach teaching within this new digital culture. Within the field of animation, there has been a radical shift in the expectations of students, industry and educators as animation has become central to a range of new moving image practices. This paper interrogates the effectiveness of adopting a studio-based collaborative production project as a method for educating students within this new moving-image culture. The project was undertaken, as part of the Creative Industries Transitions to New Professional Environments program at Queensland University of Technology (QUT) in Brisbane Australia. A number of students studying across the Creative Industries Faculty and the Faculty of Science and Technology were invited to participate in the development of a 3D animated short film. The project offered students the opportunity to become actively involved in all stages of the creative process, allowing them to experience informal learning through collaborative professional practice. It is proposed that theoretical principles often associated with andragogy and constructivism can be used to design and deliver programs that address the emerging issues surrounding the teaching of this new moving image culture.

Validation of the Cannabis Expectancy Questionnaire (CEQ) in adult cannabis users in treatment

Background Outcome expectancies are a key cognitive construct in the etiology, assessment and treatment of Substance Use Disorders. There is a research and clinical need for a cannabis expectancy measure validated in a clinical sample of cannabis users. Method The Cannabis Expectancy Questionnaire (CEQ) was subjected to exploratory (n = 501, mean age 27.45, 78% male) and confirmatory (n = 505, mean age 27.69, 78% male) factor analysis in two separate samples of cannabis users attending an outpatient cannabis treatment program. Weekly cannabis consumption was clinically assessed and patients completed the Severity of Dependence Scale-Cannabis (SDS-C) and the General Health Questionnaire (GHQ-28). Results Two factors representing Negative Cannabis Expectancies and Positive Cannabis Expectancies were identified. These provided a robust statistical and conceptual fit for the data. Internal reliabilities were high. Negative expectancies were associated with greater dependence severity (as measured by the SDS) and positive expectancies with higher consumption. The interaction of positive and negative expectancies was consistently significantly associated with self-reported functioning across all four GHQ-28 scales (Somatic Concerns, Anxiety, Social Dysfunction and Depression). Specifically, within the context of high positive cannabis expectancy, higher negative expectancy was predictive of more impaired functioning. By contrast, within the context of low positive cannabis expectancy, higher negative expectancy was predictive of better functioning. Conclusions The CEQ is the first cannabis expectancy measure to be validated in a sample of cannabis users in treatment. Negative and positive cannabis expectancy domains were uniquely associated with consumption, dependence severity and self-reported mental health functioning.

Expression and connection : the integration of the reflective learning process and the writing process into social network sites

A number of instructors have recently adopted social network sites (SNSs) for learning. However, the learning design of SNSs often remains at a preliminary level similar to a personal log book because it does not properly include reflective learning elements such as individual reflection and collaboration. This article looks at the reflective learning process and the public writing process as a way of improving the quality of reflective learning on SNSs. It proposes a reflective learning model on SNSs based on two key pedagogical concepts for social networking: individual expression and collaborative connection. It is expected that the model would be helpful for instructors in designing a reflective learning process on SNSs in an effective and flexible way.