Understanding carers' intention for their child to walk to school : further application of the theory of reasoned action

One quarter of Australian children are overweight or obese (ABS, 2010), putting them at increased risk of physical and psychological health problems (Reilly et al., 2003). Overweight and obesity in childhood tends to persist into adulthood and is associated with premature death and morbidity (Reilly & Kelly, 2011). Increases in Australian children’s weight have coincided with declines in active transportation, such as walking, to school (Salmon et al., 2005). Investigating the factors which influence walking to school is therefore important, particularly since walking to school is a low cost and effective means of reducing excess weight (Rosenberg et al., 2006) that can be easily integrated into daily routine (Brophy et al., 2011). While research in this area has expanded (e.g., Brophy et al., 2011; Giles-Corti et al., 2010), it is largely atheoretical (exceptions Napier et al., 2011). This is an important gap from a social marketing perspective given the use of theory lies at the foundation of the framework (NSMC, 2006) and a continued lack of theory use is observed (Luca & Suggs, 2013). The aim of this paper is to empirically examine a widely adopted theory, the deconstructed Theory of Reasoned Action (TRA) (Fishbein & Azjen, 1975), to understand the relative importance of attitude and subjective norms in determining intentions to increase walk to school behaviour.

Understanding caregivers’ intentions for their child to walk to school : further application of the theory of planned behaviour

Increases in childhood obesity have coincided with declines in active transportation to school. This research builds on largely atheoretical extant literature examining factors that influence walk to school behavior through application of the Theory of Planned Behavior (TPB). Understanding caregivers’ decision for their child to walk to/from school is key to developing interventions to promote this cost-effective and accessible health behavior. The results from an online survey of 512 caregivers provide support for the TPB, highlighting the important role of subjective norms. This suggests marketers should nurture caregivers’ perception that important others approve of walking to school.

Knowledge gain or system benefit in environmental decision making?

The quality of environmental decisions are gauged according to the management objectives of a conservation project. Management objectives are generally about maximising some quantifiable measure of system benefit, for instance population growth rate. They can also be defined in terms of learning about the system in question, in such a case actions would be chosen that maximise knowledge gain, for instance in experimental management sites. Learning about a system can also take place when managing practically. The adaptive management framework (Walters 1986) formally acknowledges this fact by evaluating learning in terms of how it will improve management of the system and therefore future system benefit. This is taken into account when ranking actions using stochastic dynamic programming (SDP). However, the benefits of any management action lie on a spectrum from pure system benefit, when there is nothing to be learned about the system, to pure knowledge gain. The current adaptive management framework does not permit management objectives to evaluate actions over the full range of this spectrum. By evaluating knowledge gain in units distinct to future system benefit this whole spectrum of management objectives can be unlocked. This paper outlines six decision making policies that differ across the spectrum of pure system benefit through to pure learning. The extensions to adaptive management presented allow specification of the relative importance of learning compared to system benefit in management objectives. Such an extension means practitioners can be more specific in the construction of conservation project objectives and be able to create policies for experimental management sites in the same framework as practical management sites.

Learning through modelling in the primary years

Many nations are highlighting the need for a renaissance in the mathematical sciences as essential to the well-being of all citizens (e.g., Australian Academy of Science, 2006; 2010; The National Academies, 2009). Indeed, the first recommendation of The National Academies’ Rising Above the Storm (2007) was to vastly improve K–12 science and mathematics education. The subsequent report, Rising Above the Gathering Storm Two Years Later (2009), highlighted again the need to target mathematics and science from the earliest years of schooling: “It takes years or decades to build the capability to have a society that depends on science and technology . . . You need to generate the scientists and engineers, starting in elementary and middle school” (p. 9). Such pleas reflect the rapidly changing nature of problem solving and reasoning needed in today’s world, beyond the classroom. As The National Academies (2009) reported, “Today the problems are more complex than they were in the 1950s, and more global. They’ll require a new educated workforce, one that is more open, collaborative, and cross-disciplinary” (p. 19). The implications for the problem solving experiences we implement in schools are far-reaching. In this chapter, I consider problem solving and modelling in the primary school, beginning with the need to rethink the experiences we provide in the early years. I argue for a greater awareness of the learning potential of young children and the need to provide stimulating learning environments. I then focus on data modelling as a powerful means of advancing children’s statistical reasoning abilities, which they increasingly need as they navigate their data-drenched world.

Learning the learning rate for prediction with expert advice

Most standard algorithms for prediction with expert advice depend on a parameter called the learning rate. This learning rate needs to be large enough to fit the data well, but small enough to prevent overfitting. For the exponential weights algorithm, a sequence of prior work has established theoretical guarantees for higher and higher data-dependent tunings of the learning rate, which allow for increasingly aggressive learning. But in practice such theoretical tunings often still perform worse (as measured by their regret) than ad hoc tuning with an even higher learning rate. To close the gap between theory and practice we introduce an approach to learn the learning rate. Up to a factor that is at most (poly)logarithmic in the number of experts and the inverse of the learning rate, our method performs as well as if we would know the empirically best learning rate from a large range that includes both conservative small values and values that are much higher than those for which formal guarantees were previously available. Our method employs a grid of learning rates, yet runs in linear time regardless of the size of the grid.

Open problem: Shifting experts on easy data

A number of online algorithms have been developed that have small additional loss (regret) compared to the best “shifting expert”. In this model, there is a set of experts and the comparator is the best partition of the trial sequence into a small number of segments, where the expert of smallest loss is chosen in each segment. The regret is typically defined for worst-case data / loss sequences. There has been a recent surge of interest in online algorithms that combine good worst-case guarantees with much improved performance on easy data. A practically relevant class of easy data is the case when the loss of each expert is iid and the best and second best experts have a gap between their mean loss. In the full information setting, the FlipFlop algorithm by De Rooij et al. (2014) combines the best of the iid optimal Follow-The-Leader (FL) and the worst-case-safe Hedge algorithms, whereas in the bandit information case SAO by Bubeck and Slivkins (2012) competes with the iid optimal UCB and the worst-case-safe EXP3. We ask the same question for the shifting expert problem. First, we ask what are the simple and efficient algorithms for the shifting experts problem when the loss sequence in each segment is iid with respect to a fixed but unknown distribution. Second, we ask how to efficiently unite the performance of such algorithms on easy data with worst-case robustness. A particular intriguing open problem is the case when the comparator shifts within a small subset of experts from a large set under the assumption that the losses in each segment are iid.

Interrogating Creative Theory and Creative Work: Inside the Games Studio

The expansion of creative and cultural industries has provided a rich source for theoretical claims and commentary. Much of this reproduces and extends the idea that autonomy is the defining feature of both enterprises and workers. Drawing on evidence from research into Australian development studios in the global digital games industry, the article interrogates claims concerning autonomy and related issues of insecurity and intensity, skill and specialisation, work–play boundaries, identity and attachments. In seeking to reconnect changes in creative labour to the wider production environment and political economy, an argument is advanced that autonomy is deeply contextual and contested as a dimension of the processes of capturing value for firms and workers.

Using a theory of planned behaviour framework to explore hand hygiene beliefs at the ‘5 critical moments’ among Australian hospital-based nurses

Background Improving hand hygiene among health care workers (HCWs) is the single most effective intervention to reduce health care associated infections in hospitals. Understanding the cognitive determinants of hand hygiene decisions for HCWs with the greatest patient contact (nurses) is essential to improve compliance. The aim of this study was to explore hospital-based nurses’ beliefs associated with performing hand hygiene guided by the World Health Organization’s (WHO) 5 critical moments. Using the belief-base framework of the Theory of Planned Behaviour, we examined attitudinal, normative, and control beliefs underpinning nurses’ decisions to perform hand hygiene according to the recently implemented national guidelines. Methods Thematic content analysis of qualitative data from focus group discussions with hospital-based registered nurses from 5 wards across 3 hospitals in Queensland, Australia. Results Important advantages (protection of patient and self), disadvantages (time, hand damage), referents (supportive: patients, colleagues; unsupportive: some doctors), barriers (being too busy, emergency situations), and facilitators (accessibility of sinks/products, training, reminders) were identified. There was some equivocation regarding the relative importance of hand washing following contact with patient surroundings. Conclusions The belief base of the theory of planned behaviour provided a useful framework to explore systematically the underlying beliefs of nurses’ hand hygiene decisions according to the 5 critical moments, allowing comparisons with previous belief studies. A commitment to improve nurses’ hand hygiene practice across the 5 moments should focus on individual strategies to combat distraction from other duties, peer-based initiatives to foster a sense of shared responsibility, and management-driven solutions to tackle staffing and resource issues. Hand hygiene following touching a patient’s surroundings continues to be reported as the most neglected opportunity for compliance.

Career counseling : joint contributions of contextual action theory and the systems theory framework

The influence of constructivism and the ongoing drive for convergence, both of career theories and between theory and practice, have been key drivers in the career development literature for two decades (Patton, International Handbook of Career Guidance, 2008). Both contextual action theory and systems theory are derived from the root metaphor of contextualism, which has been proffered as a worldview to assist scientists and practitioners in organizing day-to-day experiential data. This chapter identifies the theoretical contributions of the Systems Theory Framework (STF) (Patton and McMahon, Career development and systems theory: A new development, 1999, Career psychology in South Africa, 2006) and Contextual Action Theory (Young and Valach, The future of career, 2000, Journal of Vocational Behavior 64:499–514, 2004; Young et al., Career choice and development, 1996, Career choice and development, 2002), each of which has advanced thinking in theory integration and in the integration between theory and practice in the career development and counseling field. Young et al. (Career development in childhood and adolescence, 2007) noted the connections between the Patton and McMahon systems theory approach and the contextual action theory approach and these connections will be highlighted in terms of the application of these theoretical developments to practice in career counseling, with a particular focus on the commonalities between the two approaches and what counselors can learn from each of them. In particular, this chapter will discuss common conceptual understandings and practice dimensions.

The mathematical modelling of cheese ripening

A mathematical model is developed for the ripening of cheese. Such models may assist predicting final cheese quality using measured initial composition. The main constituent chemical reactions are described with ordinary differential equations. Numerical solutions to the model equations are found using Matlab. Unknown parameter values have been fitted using experimental data available in the literature. The results from the numerical fitting are in good agreement with the data. Statistical analysis is performed on near infrared data provided to the MISG. However, due to the inhomogeneity and limited nature of the data, not many conclusions can be drawn from the analysis. A simple model of the potential changes in acidity of cheese is also considered. The results from this model are consistent with cheese manufacturing knowledge, in that the pH of cheddar cheese does not significantly change during ripening.

Understanding the behavior of workshop facilitators in systems analysis and design projects: Developing theory from process modeling projects

Organizational and technological systems analysis and design practices such as process modeling have received much attention in recent years. However, while knowledge about related artifacts such as models, tools, or grammars has substantially matured, little is known about the actual tasks and interaction activities that are conducted as part of analysis and design acts. In particular, key role of the facilitator has not been researched extensively to date. In this paper, we propose a new conceptual framework that can be used to examine facilitation behaviors in process modeling projects. The framework distinguishes four behavioral styles in facilitation (the driving engineer, the driving artist, the catalyzing engineer, and the catalyzing artist) that a facilitator can adopt. To distinguish between the four styles, we provide a set of ten behavioral anchors that underpin facilitation behaviors. We also report on a preliminary empirical exploration of our framework through interviews with experienced analysts in six modeling cases. Our research provides a conceptual foundation for an emerging theory for describing and explaining different behaviors associated with process modeling facilitation, provides first preliminary empirical results about facilitation in modeling projects, and provides a fertile basis for examining facilitation in other conceptual modeling activities.

Folk theory of social change

People have a folk theory of social change (FTSC). A typical Western FTSC stipulates that as a society becomes more industrialized, it undergoes a natural course of social change, in which a communal society marked by communal relationships becomes a qualitatively different, agentic society where market-based exchange relationships prevail. People use this folk theory to predict a society’s future and estimate its past, to understand contemporary cross-cultural differences, and to make decisions about social policies. Nonetheless, the FTSC is not particularly consistent with the existing cross-cultural research on industrialization and cultural differences, and needs to be examined carefully.

Enhancing the teaching and learning of mathematical visual images

The literacy demands of mathematics are very different to those in other subjects (Gough, 2007; O'Halloran, 2005; Quinnell, 2011; Rubenstein, 2007) and much has been written on the challenges that literacy in mathematics poses to learners (Abedi and Lord, 2001; Lowrie and Diezmann, 2007, 2009; Rubenstein, 2007). In particular, a diverse selection of visuals typifies the field of mathematics (Carter, Hipwell and Quinnell, 2012), placing unique literacy demands on learners. Such visuals include varied tables, graphs, diagrams and other representations, all of which are used to communicate information.

Methods for the illumination of multilevel buildings with vertical light pipes

This paper examines the feasibility of using vertical light pipes to naturally illuminate the central core of a multilevel building not reached by window light. The challenges addressed were finding a method to extract and distribute equal amounts of light at each level and designing collectors to improve the effectiveness of vertical light pipes in delivering low elevation sunlight to the interior. Extraction was achieved by inserting partially reflecting cones within transparent sections of the pipes at each floor level. Theory was formulated to estimate the partial reflectance necessary to provide equal light extraction at each level. Designs for daylight collectors formed from laser cut panels tilted above the light pipe were developed and the benefits and limitations of static collectors as opposed to collectors that follow the sun azimuth investigated. Performance was assessed with both basic and detailed mathematical simulation and by observations made with a five level model building under clear sky conditions.