“Do I really need a nap?”: The role of sleep science in informing sleep practices in early childhood education and care settings

A compelling body of studies identifies the importance of sleep for children’s learning, behavioral regulation, and health. These studies have primarily focused on nighttime sleep or on total sleep duration. The independent contribution of daytime sleep, or napping, in childhood is an emerging research focus. Daytime sleep is particularly pertinent to the context of early childhood education and care (ECEC) where, internationally, allocation of time for naps is commonplace through to the time of school entry. The biological value of napping varies with neurological maturity and with individual circumstance. Beyond the age of 3 years, when monophasic sleep patterns become typical, there is an increasing disjuncture between children’s normative sleep requirements and ECEC practice. At this time, research evidence consistently identifies an association between napping and decreased quality and duration of night sleep. We assess the implications of this evidence for educational practice and health policy. We identify the need to distinguish the functions of napping from those of rest, and assert the need for evidence-based guidelines on sleep–rest practices in ECEC settings to accommodate individual variation in sleep needs. Given both the evidence on the impact of children’s nighttime sleep on long-term trajectories of health and well-being and the high rates of child attendance in ECEC programs, we conclude that policy and practice regarding naptime have significant implications for child welfare and ongoing public health.

Improving the teaching and learning of steel structural design

Engineering students are best able to understand theory when one explains it in relation to realistic problems and its practical applications. Teaching theory in isolation has led to lower levels of comprehension and motivation and a correspondingly higher rate of failure. At Queensland University of Technology, a number of new methods have been introduced recently to improve the teaching and learning of steel structural design at undergradt1ate level. In the basic steel structures subject a project-based teaching method was introduced in which the students were required to analyse, design and build the lightest I most efficient steel columns for a given target capacity. A design assignment involving simple, but real structures was also introduced in the basic steel structures subject. Both these exercises simulated realistic engineering problems from the early years of the course and produced a range of benefits. Improvements to the teaching and learning was also made through integration of a number of related structural engineering subjects and by the introduction of animated computer models and laboratory models. This paper presents the details of all these innovative methods which improved greatly the students' understanding of the steel structures design process.

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.

Learning analytics beyond the LMS : the Connected Learning Analytics toolkit

We present a Connected Learning Analytics (CLA) toolkit, which enables data to be extracted from social media and imported into a Learning Record Store (LRS), as defined by the new xAPI standard. Core to the toolkit is the notion of learner access to their own data. A number of implementational issues are discussed, and an ontology of xAPI verb/object/activity statements as they might be unified across 7 different social media and online environments is introduced. After considering some of the analytics that learners might be interested in discovering about their own processes (the delivery of which is prioritised for the toolkit) we propose a set of learning activities that could be easily implemented, and their data tracked by anyone using the toolkit and a LRS.

Situating learning : (re)examining the notion of apprenticeship in coach education

The last two decades has seen a proliferation in the provision of, and importance attached to, coach education in many Western countries [1]. Pivotal to many coach education programmes is the notion of apprenticeship [2,3,4]. Increasingly, mentoring is being positioned as a possible tool for enhancing coach education and consequently professional expertise [5]. However, there is a paucity of empirical data on interventions in, and evaluations of, coach education programmes. In their recent evaluation of a coach education programme Cassidy, Potrac & McKenzie [6] conclude that the situated learning literature could provide coach educators with a generative platform for the (re)examinationof apprenticeships and mentoring in a coach education context. This paper consequently discusses the merits of using situated learning theory [7] and the associated concept of Communities of Practice (CoP) [8] to stimulate discussion on developing new understandings of the practices of apprenticeship and mentoring in coach education.

Critical success factors in distance learning construction programs at Central Queensland University : students’ perspective

Distance education has gone through rapid expansion over the years. Many Australian universities are pushing the use of distance education in delivering construction education programs. However, the critical success factors (CSFs) in distance learning construction programs (DLCPs) are not fully understood. More importantly, students’ demographic features may affect the selection of distance education technologies. Situation-matching strategies should therefore be taken by universities or institutions with different student cohorts. A survey is adopted in Central Queensland University (CQU) to identify and rank the critical success factors in a DLCP in Australia where there is a significant number of earner-learners and students with low socioeconomic background. The findings suggest that the most important CSFs include access to computers and internet, reliability of web-based learning sites, high relevance and clarity of learning materials and assessment items, the availability of web-based learning sites that can be easily manipulated, and the capability of the instructors to provide well-structured courses. The findings also suggest that students with low socioeconomic background have more rigorous requirements on interface design, instructors’ support, and the integration of practical components into courses. The results provide good guidance of the design and delivery of DLCPs and will be useful for universities and institutions that are seeking to implement the distance mode in construction education.

Analysing reflective text for learning analytics : an approach using anomaly recontextualisation

Reflective writing is an important learning task to help foster reflective practice, but even when assessed it is rarely analysed or critically reviewed due to its subjective and affective nature. We propose a process for capturing subjective and affective analytics based on the identification and recontextualisation of anomalous features within reflective text. We evaluate 2 human supervised trials of the process, and so demonstrate the potential for an automated Anomaly Recontextualisation process for Learning Analytics.

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.