Standards that we can 'own' : Threshold Learning Outcomes for Journalism, Public Relations, and Media & Communication Studies

This paper outlines the progress by the JoMeC (Journalism, Media & Communication) Network in developing TLO (Threshold Learning Outcome) statements for Bachelor-level university programs in the disciplines of Journalism, Public Relations and Media & Communications Studies. The paper presents the finalised TLO statement for Journalism, and outlines moves to engage discipline-based groups to further develop preliminary TLOs for Public Relations and Media & Communication Studies. The JoMeC Network was formed in 2011, in response to requirements that from 2014 all degrees and qualifications at Australian universities would be able to demonstrate that they comply with the threshold learning standards set by the Australian Qualifications Framework (AQF). The AQF’s threshold standards define the minimum types and levels of knowledge, skills and capabilities that a student must demonstrate in order to graduate. The Tertiary Education Quality and Standards Agency (TEQSA) will use the AQF’s threshold standards as a key tool in recording and assessing the performance of higher educational institutions, and determining whether they should be registered as Australian Higher Education Providers under the Higher Education Standards Framework. The Office of Learning & Teaching (OLT) places the onus on discipline communities to collaborate in order to develop and ‘own’ the threshold learning standards that can be considered the minimum learning outcomes of university-level programs in that field. With the support of an OLT Grant, the JoMeC Network’s prime goal has been to develop three sets of discipline-specific TLOs – one each for the Journalism, Public Relations, and Media & Communications Studies disciplines. This paper describes the processes of research, consultation, drafting and ongoing revision of the TLO for Journalism. It outlines the processes that the JoMeC Network has taken in developing a preliminary TLO draft to initiate discussion of Public Relations and Media & Communication Studies. The JoMeC Network plans to hand management of further development of these TLOs to scholars within the discipline who will engage with academics and other stakeholders to develop statements that the respective disciplines can embrace and ‘own’.

Achieving superior innovation-based performance outcomes in SMEs through innovation resource–capability complementarity

Firms are increasingly identifying new avenues to enhance their market position. One such effort involves the firms' ability to continuously learn. Learning has the capacity to enable firms to develop and implement more efficient and effective innovation-focused strategies, resulting in the ability to develop and deliver more products in a timelier manner. This study tests the relationship between innovation resource–capability complementarity and innovation-based performance. This study further elaborates that while innovation resource–capability complementarity drives innovation-based performance; their relationship will be enhanced via the firms' possession of superior learning capability. The findings show a significant effect of innovation resource–capability complementarity on innovation-based performance. The results also show that firms that possess superior learning capability are willing to question their operational processes and routines and make adjustments following the feedback obtained from customers and channels; thereby enhancing their abilities to develop more new products and increase their speed in delivering products to the customers.

The dynamics of expertise acquisition in sport : the role of affective learning design

Objectives The aim of this position paper is to discuss the role of affect in designing learning experiences to enhance expertise acquisition in sport. The design of learning environments and athlete development programmes are predicated on the successful sampling and simulation of competitive performance conditions during practice. This premise is captured by the concept of representative learning design, founded on an ecological dynamics approach to developing skill in sport, and based on the individual-environment relationship. In this paper we discuss how the effective development of expertise in sport could be enhanced by the consideration of affective constraints in the representative design of learning experiences. Conclusions Based on previous theoretical modelling and practical examples we delineate two key principles of Affective Learning Design: (i) the design of emotion-laden learning experiences that effectively simulate the constraints of performance environments in sport; (ii) recognising individualised emotional and coordination tendencies that are associated with different periods of learning. Considering the role of affect in learning environments has clear implications for how sport psychologists, athletes and coaches might collaborate to enhance the acquisition of expertise in sport.

From policy borrowing to implementation : an illuminative evaluation of learning and teaching in higher education in Australia (2002 to 2008)

This study documents and theorises the consequences of the 2003 Australian Government Reform Package focussed on learning and teaching in Higher Education during the period 2002 to 2008. This is achieved through the perspective of program evaluation and the methodology of illuminative evaluation. The findings suggest that the three national initiatives of that time, Learning and Teaching Performance Fund (LTPF), Australian Learning and Teaching Council (ALTC), and Australian Universities Quality Agency (AUQA), were successful in repositioning learning and teaching as a core activity in universities. However, there were unintended consequences brought about by international policy borrowing, when the short-lived nature of LTPF suggests a legacy of quality compliance rather than one of quality enrichment.

Evaluation of assessment in the context of work-based learning: Qualitative perspectives of new graduates

Aim Evaluation or assessment of competence is an important step to ensure the safety and efficacy of health professionals, including dietitians. Most competency-based assessment studies are focussed on valid and reliable methods of assessment for the preparation of entry-level dietitians, few papers have explored student dietitians’ perceptions of these evaluations. This study aimed to explore the perceptions of recent graduates from accredited nutrition and dietetics training programs in Australia. It also aimed to establish the relevance of competency-based assessment to adequately prepare them for entry-level work roles. Methods A purposive sample of newly-graduated dietitians with a range of assessment experiences and varied employment areas was recruited. A qualitative approach, using in-depth interviews with 13 graduates, with differing assessment experiences was undertaken. Graduates were asked to reflect upon their competency-based assessment experiences whilst a student. Data was thematically analysed by multiple authors. Results Four themes emerged from the data analysis: (i) Transparency and consistency are critical elements of work-based competency assessment. (ii) Students are willing to take greater responsibility in their assessment process. (iii) Work-based competency assessment prepares students for employment. (iv) The relationship between students and their assessors can impact on the student experience and their assessment performance. Conclusions Understanding this unique perspective of students can improve evaluation of future health professionals and assist in designing valid competency-based assessment approaches.

Factors influencing robustness and effectiveness of conditional random fields in active learning frameworks

Active learning approaches reduce the annotation cost required by traditional supervised approaches to reach the same effectiveness by actively selecting informative instances during the learning phase. However, effectiveness and robustness of the learnt models are influenced by a number of factors. In this paper we investigate the factors that affect the effectiveness, more specifically in terms of stability and robustness, of active learning models built using conditional random fields (CRFs) for information extraction applications. Stability, defined as a small variation of performance when small variation of the training data or a small variation of the parameters occur, is a major issue for machine learning models, but even more so in the active learning framework which aims to minimise the amount of training data required. The factors we investigate are a) the choice of incremental vs. standard active learning, b) the feature set used as a representation of the text (i.e., morphological features, syntactic features, or semantic features) and c) Gaussian prior variance as one of the important CRFs parameters. Our empirical findings show that incremental learning and the Gaussian prior variance lead to more stable and robust models across iterations. Our study also demonstrates that orthographical, morphological and contextual features as a group of basic features play an important role in learning effective models across all iterations.

Unsupervised online learning of condition-invariant images for place recognition

This paper presents an online, unsupervised training algorithm enabling vision-based place recognition across a wide range of changing environmental conditions such as those caused by weather, seasons, and day-night cycles. The technique applies principal component analysis to distinguish between aspects of a location’s appearance that are condition-dependent and those that are condition-invariant. Removing the dimensions associated with environmental conditions produces condition-invariant images that can be used by appearance-based place recognition methods. This approach has a unique benefit – it requires training images from only one type of environmental condition, unlike existing data-driven methods that require training images with labelled frame correspondences from two or more environmental conditions. The method is applied to two benchmark variable condition datasets. Performance is equivalent or superior to the current state of the art despite the lesser training requirements, and is demonstrated to generalise to previously unseen locations.

Workplace Learning in Physical Education : Emerging Teachers’ Stories from the Staffroom and Beyond

Pre-service and beginning teachers have to negotiate an unfamiliar and often challenging working environment, in both teaching spaces and staff spaces. Workplace Learning in Physical Education explores the workplace of teaching as a site of professional learning. Using stories and narratives from the experiences of pre-service and beginning teachers, the book takes a closer look at how professional knowledge is developed by investigating the notions of ‘professional’ and ‘workplace learning’ by drawing on data from a five year project. The book also critically examines the literature associated with, and the rhetoric that surrounds ‘the practicum’, ‘fieldwork’ ‘school experience’ and the ‘induction year’. The book is structured around five significant dimensions of workplace learning: Social tasks of teaching and learning to teach Performance, practice and praxis Identity, subjectivities and the profession/al Space and place for, and of, learning Micropolitics As well as identifying important implications for policy, practice and research methodology in physical education and teacher education, the book also shows how research can be a powerful medium for the communication of good practice. This is an important book for all students, pre-service and beginning teachers working in physical education, for academics researching teacher workspaces, and for anybody with an interest in the wider themes of teacher education, professional practice and professional learning in the workplace.

The learning capability of construction organisations engaged in collaborative contracting - Literature Review [industry report]

Background Value for money (VfM) on collaborative construction projects is dependent on the learning capabilities of the organisations and people involved. Within the context of infrastructure delivery, there is little research about the impact of organisational learning capability on project value. The literature contains a multiplicity of often un-testable definitions about organisational learning abilities. This paper defines learning capability as a dynamic capability that participant organisations purposely develop to add value to collaborative projects. The paper reports on a literature review that proposes a framework that conceptualises learning capability to explore the topic. This work is the first phase of a large-scale national survey funded by the Alliancing Association of Australasia and the Australian Research Council. Methodology Desk-top review of leading journals in the areas of strategic management, strategic alliances and construction management, as well as recent government documents and industry guidelines, was undertaken to synthesise, conceptualise and operationalise the concept of learning capability. The study primarily draws on the theoretical perspectives of the resource-based view of the firm (e.g. Barney 1991; Wernerfelt 1984), absorptive capacity (e.g. Cohen and Levinthal 1990; Zahra and George 2002); and dynamic capabilities (e.g. Helfat et al. 2007; Teece et al. 1997; Winter 2003). Content analysis of the literature was undertaken to identify key learning routines. Content analysis is a commonly used methodology in the social sciences area. It provides rich data through the systematic and objective review of literature (Krippendorff 2004). NVivo 9, a qualitative data analysis software package, was used to assist in this process. Findings and Future Research The review process resulted in a framework for the conceptualisation of learning capability that shows three phases of learning: (1) exploratory learning, (2) transformative learning and (3) exploitative learning. These phases combine both internal and external learning routines to influence project performance outcomes and thus VfM delivered under collaborative contracts. Sitting within these phases are eight categories of learning capability comprising knowledge articulation, identification, acquisition, dissemination, codification, internationalisation, transformation and application. The learning routines sitting within each category will be disaggregated in future research as the basis for measureable items in a large-scale survey study. The survey will examine the extent to which various learning routines influence project outcomes, as well as the relationships between them. This will involve identifying the routines that exist within organisations in the construction industry, their resourcing and rate of renewal, together with the extent of use and perceived value within the organisation. The target population is currently estimated to be around 1,000 professionals with experience in relational contracting in Australia. This future research will build on the learning capability framework to provide data that will assist construction organisations seeking to maximise VfM on construction projects.

Evaluation of knowledge management performance: An organic approach

Knowledge management (KM) strategy is the planned or actual coordination of a firm's major goals and learning in time; this coordination continually co-aligns the firm's knowledge-based resources with the environment. Based on the organic perspective of strategy, a KM performance evaluation approach should be able to 1) review the knowledge governance mechanisms and learning routines that underpin the KM strategy, as well as the performance outcomes driven by the strategy, and 2) predict the evolution of performance drivers and outcomes into the future to facilitate strategic planning. This study combined a survey study and a system dynamics (SD) simulation to demonstrate the transformation from a mechanistic to an organic perspective on KM strategy and performance evaluation. The survey study was conducted based on a sample of 143 construction contractors and used structural equation modeling (SEM) techniques to develop a KM performance index for reviewing the key elements that underpin KM strategy. The SD simulation predicted the development of KM strategy configurations and the evolution of KM performance over time. The organic KM performance evaluation approach demonstrated by this study has significant potential to improve the alignment of KM strategy within an increasingly dynamic business environment.

Leading or managing? Assistant Regional Directors, School Performance, in Queensland

Purpose Education reform aimed at achieving improved student learning is a demanding challenge for leaders and managers at all levels of education across the globe. In 2010, the position of Assistant Regional Directors, School Performance (ARD-SP), was established to positively impact upon student learning across public schools in Queensland, Australia. This study explores the perceptions of the role and leadership understandings of ARDs in Queensland in order to understand more fully the tensions and opportunities they face within this reasonably newly created position. Design/methodology/approach This qualitative study is based on interviews with 18 Assistant Regional Directors and two of their supervisors to gauge a better understanding of the nature of the role as it relates to leadership and management in the Queensland context. Findings Interview data revealed three key themes pertaining to the nature of the role and these were performance, supervision, and professional challenges. A key finding was that the notion of supervision was experienced as problematic for ARDs-SP. Research limitations/implications This study has limitations and these include a sample that focused on Assistant Regional Directors within one State of Australia and one schooling system (i.e. public education); and interviews were the primary data collection source. Originality/value Although there have been studies of supervisors of principals (referred to as superintendents, directors) in other countries and other systems, this study is a first to explore the tensions and opportunities faced by executive leaders in Queensland.

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.

Locally weighted learning methods for non-rigid robot control

This thesis develops a novel approach to robot control that learns to account for a robot's dynamic complexities while executing various control tasks using inspiration from biological sensorimotor control and machine learning. A robot that can learn its own control system can account for complex situations and adapt to changes in control conditions to maximise its performance and reliability in the real world. This research has developed two novel learning methods, with the aim of solving issues with learning control of non-rigid robots that incorporate additional dynamic complexities. The new learning control system was evaluated on a real three degree-of-freedom elastic joint robot arm with a number of experiments: initially validating the learning method and testing its ability to generalise to new tasks, then evaluating the system during a learning control task requiring continuous online model adaptation.

Learning to lead: The development and testing of a model of leadership learning

Drawing upon an action learning perspective, we hypothesized that a leader’s learning of project leadership skills would be related to facilitative leadership, team reflexivity, and team performance. Secondly, we proposed that new and experienced leaders would differ in the amount they learn from their current and recent experience as project managers, and in the strength of the relationship between their self-reported learning, facilitative leadership, and team reflexivity. We conducted a 1-year longitudinal study of 50 R&D teams, led by 25 new and 25 experienced leaders, with 313 team members and 22 project customers, collecting both quantitative and qualitative data. We found evidence of a significant impact of the leader’s learning on subsequent facilitative leadership and team performance 8 and 12 months later, suggesting a lag between learning leadership skills and translating these skills into leadership behavior. The findings contribute to an understanding of how leaders consolidate their learned experience into facilitative leadership behavior.