Standing brave in the face of rapid curriculum change : EAL/D teachers speak about critical literacy and its place in senior English teaching

Critical literacy (CL) has been the subject of much debate in the Australian public and education arenas since 2002. Recently, this debate has dissipated as literacy education agendas and attendant policies shift to embrace more hybrid models and approaches to the teaching of senior English. This paper/presentation reports on the views expressed by four teachers of senior English about critical literacy and it’s relevance to students who are from culturally and linguistically diverse backgrounds who are learning English while undertaking senior studies in high school. Teachers’ understandings of critical literacy are important, esp. given the emphasis on Critical and Creative Thinking and Literacy as two of the General Capabilities underpinning the Australian national curriculum. Using critical discourse analysis, data from four specialist ESL teachers in two different schools were analysed for the ways in which these teachers construct critical literacy. While all four teachers indicated significant commitment to critical literacy as an approach to English language teaching, the understandings they articulated varied from providing forms of access to powerful genres, to rationalist approaches to interrogating text, to a type of ‘critical-aesthetic’ analysis of text construction. Implications are also discussed.

The SCOOT experience : games in place : collaborative interventions in socio-spatial practices

The principal focus of this thesis is the representation of a significant creative practice in relation to the design and installation of the Location-Based Game, SCOOT. This project demonstrates new understandings relating to the contingencies and potentials for transferring positive aspects of digital gameplay to everyday physical environments in an effort to reveal hidden histories and revitalise peoples’ interactions with their local urban spaces.

Making space and place for knowledge communities : lessons for Australian practice

This paper aims to shed light on the planning and development processes of the knowledge-based urban development phenomenon, with respect to the construction of knowledge community precincts. We undertake policy and best practice analyses to learn from the planning and development processes of internationally renowned knowledge community precincts—from Copenhagen, Eindhoven and Singapore. In the light of this, we scrutinise major Australian knowledge community precinct initiatives—from Sydney, Melbourne and Brisbane—to better understand the dynamics of national practices, and benchmark them against the international best practice cases. The paper concludes with a discussion on the study findings and successfully establishing space and place for both knowledge economy and society in Australian cities.

No hiding place

As public and private space becomes a focus for development values, contests occur between the unequal parties having a stake in the use of public space, such as central and local government, young people, communities and site developers. It is within the monitoring, recording and control procedures that young people’s use of public space is constructed as a threat to social order in need of surveillance and exclusion. This forms a major and contemporary feature in shaping thinking about urban and rural working class young people in the UK.

Vision-based place recognition : how low can you go?

In this paper we use the algorithm SeqSLAM to address the question, how little and what quality of visual information is needed to localize along a familiar route? We conduct a comprehensive investigation of place recognition performance on seven datasets while varying image resolution (primarily 1 to 512 pixel images), pixel bit depth, field of view, motion blur, image compression and matching sequence length. Results confirm that place recognition using single images or short image sequences is poor, but improves to match or exceed current benchmarks as the matching sequence length increases. We then present place recognition results from two experiments where low-quality imagery is directly caused by sensor limitations; in one, place recognition is achieved along an unlit mountain road by using noisy, long-exposure blurred images, and in the other, two single pixel light sensors are used to localize in an indoor environment. We also show failure modes caused by pose variance and sequence aliasing, and discuss ways in which they may be overcome. By showing how place recognition along a route is feasible even with severely degraded image sequences, we hope to provoke a re-examination of how we develop and test future localization and mapping systems.

Place psychology: Engaging with notions of 'home'

Psychology of place is theoretical territory shared by a wide range of disciplines. Currently, while environmental psychology addresses such questions as how people interact with and make meaning in places, clinical psychology has paid scant attention to the role of place in mental health. This paper focuses on two concepts from place psychology - place attachment and place identity. Place attachment is here defined as a sense of positively-valanced emotional connection to a familiar place (Morgan 2010). Place identity implies a stronger sense of belonging: the person as part of the place and the place as part of the person (Memmot & Long 2002). Both place attachment and place identity can be seen as relating to notions of ‘home’. My PhD is a work of interdisciplinary practice-based research using creative writing as a methodology to explore how place attachment, place identity and notions of home may support recovery from psychological trauma. A novel provides a site of imaginative encounter between author and reader, in which the two parties collaboratively create place and character through the medium of language. This paper links theory with practice by outlining some choices involved in exploring psychological constructs through narrative fiction.

Hybrid place : blurring the edge between the digital and physical layers of urban environments

The purpose of this paper is to investigate the edge condition between the digital layers and the physical layers of the city and how tangible expressions of the interrelationships between them to create and define new experiences of place, creating hybrid place. To date there has been discussion and investigation into understanding the importance of place, similarly into defining hybrid space. This paper explores principles of place and space to question how they can be applied into defining and proposing the notion of hybrid place in urban environments. The integration of media spaces into architecture provide infrastructure for the development of hybrid place. The physical boundaries of urban spaces become blurred through the integration of media such as computer technologies connecting the physical environment with the digital. Literature and case studies that reflect the current trends of use of technology by people in space and place within urban environments are examined.

Sensing place : embodiment, sensoriality, kinesis, and children behind the camera

This article is a call to literacy teachers and researchers to embrace the possibility of attending more consciously to the senses in digital media production. Literacy practices do not occur only in the mind, but involve the sensoriality, embodiment, co-presence, and movement of bodies. This paper theorises the sensorial and embodied dimension of children’s filmmaking about place in two communities in Australia. The films were created by pre-teen Indigenous and non-Indigenous children in Logan, Queensland, and by Indigenous teenagers at the Warralong campus of the Strelley Community School in remote Western Australia. The films were created through engagement in cross-curricular units that sensitised the students’ experience of local places, gathering corporeal information through their sensing bodies as they interacted with the local ecology. The analysis highlights how the sensorial and bodily nature of literacy practice through documentary filmmaking was central to the children’s formation and representation of knowledge, because knowledge and literacy practices are not only acquired through the mind, but are also reliant on embodiment, sensoriality, co-presence, and kinesics of the body in place.

Literacy, place-based pedagogies and social justice

Our long-term program of research has considered the relationships between teachers’ work and identities, literacy pedagogies and schooling, particularly in high-poverty communities. Over the past decade, we have worked with teachers to consciously explore with them the possible productive synergies between critical literacy and place-based pedagogies, and the affordances of multimodal and digital literacies for students’ engagement with the places where they live and learn. These studies have been undertaken with teachers working and living in various locales—from the urban fringe to inner suburban areas undergoing urban renewal, to rural and regional communities where poverty and the politics of place bring certain distinctive opportunities and constraints to bear on pedagogy for social justice. There is now wider recognition that “social justice” may need rethinking to foreground the nonhuman world and the relation between people and politics of places, people, and environments in terms of “eco-social justice” (Green 2010; Gruenewald 2003b) or spatial justice (Soja 2011). In this chapter, we explore place as a site of knowing and as an object of study as developed through the Special Forever project by teachers in schools located in the Murray-Darling Basin bioregion. Putting the environment at the center of the literacy curriculum inevitably draws teachers into the politics of place and raises questions concerning what is worth preserving and what should be transformed. We consider how the politics of place both constrains and opens up possibilities for pedagogy for eco-social justice and review the pedagogical work that one teacher, Hannah, undertook with her upper primary class.

Ensuring sessional academic success by rethinking the place of academic development

There has been growing recognition of the contribution that Sessional Academics make to student learning in higher education; with recent studies concluding that around half Australian university teaching is now performed by casual staff [Red Report 2008; May, 2013]. However, sector-wide research and institutional audits continue to raise concerns about academic development and quality assurance, as well as the recognition and retention of Sessional Academics. In response, universities offer academic development programs. However, while such centrally offered programs are undoubtedly useful, they are necessarily generic and cannot address the local contexts of faculties or provide ‘on the ground’ support. This paper presents a new, distributed model of academic support and development for Sessional academics at Queensland University of Technology. Entitled the Sessional Academic Success program, it employs the principles of distributed leadership. Experienced Sessional academics are trained and supported to assume roles as Sessional Academic Success Advisors within their schools. Complementing our central programs, they design bespoke, locally situated, peer-to-peer academic development for new Sessional teachers; provide ‘just in time’, safe and reliable advice; and build supportive communities of teaching practice in their local contexts. This distributed model re-envisages the forms and places of academic development and support. It helps ensure that new Sessional Academics are embraced by faculty life. And, recognizing that experienced Sessional Academics have much to contribute to the advancement of learning and teaching, it builds their capacity through leadership opportunities. As the designer/facilitator of the program and a Sessional Academic Success Advisor, the authors take a dialogic approach and together describe the design, implementation and outcomes of the program.

Autonomous movement-driven place recognition calibration for generic multi-sensor robot platforms

In this paper we present a method for autonomously tuning the threshold between learning and recognizing a place in the world, based on both how the rodent brain is thought to process and calibrate multisensory data and the pivoting movement behaviour that rodents perform in doing so. The approach makes no assumptions about the number and type of sensors, the robot platform, or the environment, relying only on the ability of a robot to perform two revolutions on the spot. In addition, it self-assesses the quality of the tuning process in order to identify situations in which tuning may have failed. We demonstrate the autonomous movement-driven threshold tuning on a Pioneer 3DX robot in eight locations spread over an office environment and a building car park, and then evaluate the mapping capability of the system on journeys through these environments. The system is able to pick a place recognition threshold that enables successful environment mapping in six of the eight locations while also autonomously flagging the tuning failure in the remaining two locations. We discuss how the method, in combination with parallel work on autonomous weighting of individual sensors, moves the parameter dependent RatSLAM system significantly closer to sensor, platform and environment agnostic operation.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Towards bio-inspired place recognition over multiple spatial scales

This paper presents a new multi-scale place recognition system inspired by the recent discovery of overlapping, multi-scale spatial maps stored in the rodent brain. By training a set of Support Vector Machines to recognize places at varying levels of spatial specificity, we are able to validate spatially specific place recognition hypotheses against broader place recognition hypotheses without sacrificing localization accuracy. We evaluate the system in a range of experiments using cameras mounted on a motorbike and a human in two different environments. At 100% precision, the multiscale approach results in a 56% average improvement in recall rate across both datasets. We analyse the results and then discuss future work that may lead to improvements in both robotic mapping and our understanding of sensory processing and encoding in the mammalian brain.

Towards condition-invariant, top-down visual place recognition

In this paper we present a novel place recognition algorithm inspired by recent discoveries in human visual neuroscience. The algorithm combines intolerant but fast low resolution whole image matching with highly tolerant, sub-image patch matching processes. The approach does not require prior training and works on single images (although we use a cohort normalization score to exploit temporal frame information), alleviating the need for either a velocity signal or image sequence, differentiating it from current state of the art methods. We demonstrate the algorithm on the challenging Alderley sunny day – rainy night dataset, which has only been previously solved by integrating over 320 frame long image sequences. The system is able to achieve 21.24% recall at 100% precision, matching drastically different day and night-time images of places while successfully rejecting match hypotheses between highly aliased images of different places. The results provide a new benchmark for single image, condition-invariant place recognition.