Problem-based learning : does accounting education need it?

Problem-based learning (PBL) has been used successfully in disciplines such as medicine, nursing, law and engineering. However a review of the literature shows that there has been little use of this approach to learning in accounting. This paper extends the research in accounting education by reporting the findings of a case study of the development and implementation of PBL at the Queensland University of Technology (QUT) in a new Accountancy Capstone unit that began in 2006. The fundamentals of the PBL approach were adhered to. However, one of the essential elements of the approach adopted was to highlight the importance of questioning as a means of gathering the necessary information upon which decisions are made. This approach can be contrasted with the typical ‘give all the facts’ case studies that are commonly used. Another feature was that students worked together in the same group for an entire semester (similar to how teams in the workplace operate) so there was an intended focus on teamwork in solving unstructured, real-world accounting problems presented to students. Based on quantitative and qualitative data collected from student questionnaires over seven semesters, it was found that students perceived PBL to be effective, especially in terms of developing the skills of questioning, teamwork, and problem solving. The effectiveness of questioning is very important as this is a skill that is rarely the focus of development in accounting education. The successful implementation of PBL in accounting through ‘learning by doing’ could be the catalyst for change to bring about better learning outcomes for accounting graduates.

Evaluation of implementation of a healthy food and drink supply strategy throughout the whole school environment in Queensland state schools, Australia

BACKGROUND/OBJECTIVES: This paper reports on the evaluation of the Smart Choices healthy food and drink supply strategy for Queensland schools (Smart Choices) implementation across the whole school environment in state government primary and secondary schools in Queensland, Australia. SUBJECTS/METHODS: Three concurrent surveys using different methods for each group of stakeholders that targeted all 1275 school Principals, all 1258 Parent and Citizens’ Associations (P&Cs) and a random sample of 526 tuckshop convenors throughout Queensland. Nine hundred and seventy-three Principals, 598 P&Cs and 513 tuckshop convenors participated with response rates of 78%, 48% and 98%, respectively. RESULTS: Nearly all Principals (97%), P&Cs (99%) and tuckshop convenors (97%) reported that their school tuckshop had implemented Smart Choices. The majority of Principals and P&Cs reported implementation, respectively, in: school breakfast programs (98 and 92%); vending machine stock (94 and 83%); vending machine advertising (85 and 84%); school events (87 and 88%); school sporting events (81 and 80%); sponsorship and advertising (93 and 84%); fundraising events (80 and 84%); and sporting clubs (73 and 75%). Implementation in curriculum activities, classroom rewards and class parties was reported, respectively, by 97%, 86% and 75% of Principals. Respondents also reported very high levels of understanding of Smart Choices and engagement of the school community. CONCLUSIONS: The results demonstrated that food supply interventions to promote nutrition across all domains of the school environment can be implemented successfully.

Intractable differences : artistic research and the problem of practice

The purpose of this paper is to analyse the complex nature of practice within Artistic research. This will be done by considering practice through the lens of Bourdieu’s conceptualisation of practice. The focus of the paper is on developing an understanding of practice-led approaches to research and how these are framed by what Coessens et al. (2009) call the artistic turn in research. The paper begins with a brief introduction to the nature of practice and then continues on to discuss the broader field of artistic research, describing the environment which has shaped its evolution and foregrounding several of its key dispositions. The paper aims to not simply describe existing methodology but to rethink what is meant by artistic research and practice-led strategies.

Identities and transformational experiences for quantitative problem solving : gender comparisons of first-year university science students

Women are underrepresented in science, technology, engineering and mathematics (STEM) areas in university settings; however this may be the result of attitude rather than aptitude. There is widespread agreement that quantitative problem-solving is essential for graduate competence and preparedness in science and other STEM subjects. The research question addresses the identities and transformative experiences (experiential, perception, & motivation) of both male and female university science students in quantitative problem solving. This study used surveys to investigate first-year university students’ (231 females and 198 males) perceptions of their quantitative problem solving. Stata (statistical analysis package version 11) analysed gender differences in quantitative problem solving using descriptive and inferential statistics. Males perceived themselves with a higher mathematics identity than females. Results showed that there was statistical significance (p<0.05) between the genders on 21 of the 30 survey items associated with transformative experiences. Males appeared to have a willingness to be involved in quantitative problem solving outside their science coursework requirements. Positive attitudes towards STEM-type subjects may need to be nurtured in females before arriving in the university setting (e.g., high school or earlier). Females also need equitable STEM education opportunities such as conversations or activities outside school with family and friends to develop more positive attitudes in these fields.

The exemplification of governance principles within state asset management laws and policies : the case of Indonesia

This chapter reviews aspects of the challenge of reviewing and reforming Indonesian practice within state asset management law and policy specifically related to public housing, public buildings, parklands, and vacant land. A critical issue in beginning this review is how Indonesia currently conceptualizes the notion of asset governance and how this meaning is embodied in recent changes in law and policy and importantly in options for future change. This chapter discusses the potential complexities uniquely Indonesian characteristics such as decentralisation and regional autonomy regime, political history, and bureaucratic culture.

Dynamic equivalent state estimation for multi-area power systems with synchronized phasor measurement units

This paper proposes a new approach for state estimation of angles and frequencies of equivalent areas in large power systems with synchronized phasor measurement units. Defining coherent generators and their correspondent areas, generators are aggregated and system reduction is performed in each area of inter-connected power systems. The structure of the reduced system is obtained based on the characteristics of the reduced linear model and measurement data to form the non-linear model of the reduced system. Then a Kalman estimator is designed for the reduced system to provide an equivalent dynamic system state estimation using the synchronized phasor measurement data. The method is simulated on two test systems to evaluate the feasibility of the proposed method.

Non-invasive identification of proteoglycans and chondrocyte differentiation state by Raman microspectroscopy

Proteoglycans (PGs) are crucial extracellular matrix (ECM) components that are present in all tissues and organs. Pathological remodeling of these macromolecules can lead to severe diseases such as osteoarthritis or rheumatoid arthritis. To date, PG-associated ECM alterations are routinely diagnosed by invasive analytical methods. Here, we employed Raman microspectroscopy, a laser-based, marker-free and non-destructive technique that allows the generation of spectra with peaks originating from molecular vibrations within a sample, to identify specific Raman bands that can be assigned to PGs within human and porcine cartilage samples and chondrocytes. Based on the non-invasively acquired Raman spectra, we further revealed that a prolonged in vitro culture leads to phenotypic alterations of chondrocytes, resulting in a decreased PG synthesis rate and loss of lipid contents. Our results are the first to demonstrate the applicability of Raman microspectroscopy as an analytical and potential diagnostic tool for non-invasive cell and tissue state monitoring of cartilage in biomedical research. ((c) 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

Enhancing opportunities to feed forward ; developing problem solving skills using web based scenarios

Universities often struggle to satisfy students’ need for feedback. This is an area where student satisfaction with courses of study can be low. Yet it is clear that one of the properties of good teaching is giving the highest quality feedback on student work. The term ‘feedback’ though is most commonly associated with summative assessment given by a teacher after work is completed. The student can often be a passive participant in the process. This paper looks at the implementation of a web based interactive scenario completed by students prior to summative assessment. It requires students to participate actively to develop and improve their legal problem solving skills. Traditional delivery of legal education focuses on print and an instructor who conveys the meaning of the written word to students. Today, mixed modes of teaching are often preferred and they can provide enhanced opportunities for feeding forward with greater emphasis on what students do. Web based activities allow for flexible delivery; they are accessible off campus, at a time that suits the student and may be completed by students at their own pace. This paper reports on an online interactive activity which provides valuable formative feedback necessary to allow for successful completion of a final problem solving assignment. It focuses on how the online activity feeds forward and contributes to the development of legal problem solving skills. Introduction to Law is a unit designed and introduced for completion by undergraduate students from faculties other than law but is focused most particularly on students enrolled in the Bachelor of Entertainment Industries degree, a joint initiative of the faculties of Creative Industries, Business and Law at the Queensland University of Technology in Australia. The final (and major) assessment for the unit is an assignment requiring students to explain the legal consequences of particular scenarios. A number of cost effective web based interactive scenarios have been developed to support the unit’s classroom activities. The tool commences with instruction on problem solving method. Students then view the stimulus which is a narrative produced in the form of a music video clip. A series of questions are posed which guide students through the process and they can compare their responses with sample answers provided. The activity clarifies the problem solving method and expectations for the summative assessment and allows students to practise the skill. The paper reports on the approach to teaching and learning taken in the unit including the design process and implementation of the activity. It includes an evaluation of the activity with respect to its effectiveness as a tool to feed forward and reflects on the implications for the teaching of law in higher education.

Untanglings: A novel approach to analyzing concurrent systems

Substantial research efforts have been expended to deal with the complexity of concurrent systems that is inherent to their analysis, e.g., works that tackle the well-known state space explosion problem. Approaches differ in the classes of properties that they are able to suitably check and this is largely a result of the way they balance the trade-off between analysis time and space employed to describe a concurrent system. One interesting class of properties is concerned with behavioral characteristics. These properties are conveniently expressed in terms of computations, or runs, in concurrent systems. This article introduces the theory of untanglings that exploits a particular representation of a collection of runs in a concurrent system. It is shown that a representative untangling of a bounded concurrent system can be constructed that captures all and only the behavior of the system. Representative untanglings strike a unique balance between time and space, yet provide a single model for the convenient extraction of various behavioral properties. Performance measurements in terms of construction time and size of representative untanglings with respect to the original specifications of concurrent systems, conducted on a collection of models from practice, confirm the scalability of the approach. Finally, this article demonstrates practical benefits of using representative untanglings when checking various behavioral properties of concurrent systems.

Blogging the 2009 Queensland State Election

The internet has become important in political communication in Australia. Using Habermas' ideal types, it is argued that political blogs can be viewed as public spheres that might provide scope for the expansion of deliberative democratic discussion. This hypothesis is explored through analysis of the group political blog Pineapple Party Time. It is evident that the bloggers and those who commented on their posts were highly knowledgeable about and interested in politics. Form an examination of these posts and the comments on them, Pineapple Party Time did act as a public sphere to some degree, and did provide for the deliberative discussion essential for a democracy, but it was largely restricted to Crikey readers. For a deliberative public sphere and democratic discussion to function to any extent, the public sphere must be open to all citizens, who need to have the access and knowledge to engage in deliberative discussion.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Machine prognostics based on health state estimation using SVM

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation, and can also improve productivity and enhance system safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

When does change begin following screening and brief intervention among depressed problem drinkers?

Brief interventions are effective for problem drinking and reductions are known to occur in association with screening and assessment. The present study sought to assess, among participants (N=202) in a clinical trial, how much change occurred between baseline assessment and a one-session brief intervention (S1), and the predictors of early change. The primary focus was on changes in the Beck Depression Inventory Fast Screen scores and alcohol consumption (standard drinks per week) prior to random allocation to nine further sessions addressing either depression, alcohol, or both problems. There were large and clinically significant reductions between baseline and S1, with the strongest predictors being baseline scores in the relevant domain and change in the other domain. Client engagement was also predictive of early depression changes. Monitoring progress in both domains from first contact, and provision of empathic care, followed by brief intervention appear to be useful for this high prevalence comorbidity.

How to design extended finite state machine test models in Java

This chapter is a tutorial that teaches you how to design extended finite state machine (EFSM) test models for a system that you want to test. EFSM models are more powerful and expressive than simple finite state machine (FSM) models, and are one of the most commonly used styles of models for model-based testing, especially for embedded systems. There are many languages and notations in use for writing EFSM models, but in this tutorial we write our EFSM models in the familiar Java programming language. To generate tests from these EFSM models we use ModelJUnit, which is an open-source tool that supports several stochastic test generation algorithms, and we also show how to write your own model-based testing tool. We show how EFSM models can be used for unit testing and system testing of embedded systems, and for offline testing as well as online testing.