Instructing foreign language learners how to listen through metacognitive strategies : an empirical study

This study uses a mixed method approach to investigate the impact of metacognitive strategies instruction on listening comprehension. An experimental group (N = 30) of university students are guided through a process-approach pedagogy over one semester (10 weeks) in Iran. IELTS listening tests are used to track development of listening comprehension in participants who are then asked to complete a Metacognitive Awareness Listening Questionnaire (MALQ). The questionnaire examines students’ employment of metacognitive strategies in listening comprehension. Finally, interviews are used to explore students’ use of strategies in listening. Results indicate that participants develop listening comprehension, but no metacognitive awareness in listening. Students reported in the interviews that they use multiple strategies (cognitive and metacognitive) to approach listening comprehension.

Novel methods and the maximum likelihood estimation technique for estimating traffic critical gap

Most unsignalised intersection capacity calculation procedures are based on gap acceptance models. Accuracy of critical gap estimation affects accuracy of capacity and delay estimation. Several methods have been published to estimate drivers’ sample mean critical gap, the Maximum Likelihood Estimation (MLE) technique regarded as the most accurate. This study assesses three novel methods; Average Central Gap (ACG) method, Strength Weighted Central Gap method (SWCG), and Mode Central Gap method (MCG), against MLE for their fidelity in rendering true sample mean critical gaps. A Monte Carlo event based simulation model was used to draw the maximum rejected gap and accepted gap for each of a sample of 300 drivers across 32 simulation runs. Simulation mean critical gap is varied between 3s and 8s, while offered gap rate is varied between 0.05veh/s and 0.55veh/s. This study affirms that MLE provides a close to perfect fit to simulation mean critical gaps across a broad range of conditions. The MCG method also provides an almost perfect fit and has superior computational simplicity and efficiency to the MLE. The SWCG method performs robustly under high flows; however, poorly under low to moderate flows. Further research is recommended using field traffic data, under a variety of minor stream and major stream flow conditions for a variety of minor stream movement types, to compare critical gap estimates using MLE against MCG. Should the MCG method prove as robust as MLE, serious consideration should be given to its adoption to estimate critical gap parameters in guidelines.

Inquiries, empirical research and regulatory failure

The paper reveals that regulatory failure, often chronic, has characterised the regulatory environments of charities across time and locale. The analysis of the primary literature identifies common issues and suggested remedies pertaining to the regulatory failures of charities. These issues may well be appropriate for consideration by the commission and participants given their persistence in various inquiries for nearly four centuries. Such inquiries also considered other issues not directly referred to in this paper, to also include them would exponentially increase the already unwieldy size of this paper.

An empirical study of business method patent applications filed in Australia 2000-2009

This article sets out the results of an empirical research study into the uses to which the Australian patent system is being put in the early 21st century. The focus of the study is business method patents, which are of interest because they are a controversial class of patent that are thought to differ significantly from the mechanical, chemical and industrial inventions that have traditionally been the mainstay of the patent system. The purpose of the study is to understand what sort of business method patent applications have been lodged in Australia in the first decade of this century and how the patent office is responding to those applications.

Justifiability of littering : an empirical investigation

This paper investigates the relationship between voluntary participation in environmental organisations and the justifiability of littering behaviour. Previous empirical work regarding determinants of littering and littering behaviour remains scarce, particularly in socio-economic analysis. We address these deficiencies, demonstrating a strong empirical link between environmental participation and reduced public littering in the European Values Survey (EVS) data for 30 Western and Eastern European countries. The results suggest that membership in environmental organisations is related to a stronger commitment to anti-littering behaviour, thereby supporting improved environmental quality.

Indigeneity and the likelihood of imprisonment in Queensland’s adult and children’s courts

Australian research on Indigenous sentencing disparities of the standard of international work is somewhat recent. Contrary to expectations based on international research, Australian studies generally have not found Indigenous offenders to be treated substantively more harshly than non-Indigenous offenders in similar circumstances. However, this research has primarily focused on adult higher courts, with little attention to lower courts and children’s courts. In this article, we examine whether Indigeneity has a direct impact on the judicial decision to incarcerate for three courts (adult higher, adult lower, children’s higher court) in Queensland. We found no significant differences in the likelihood of a sentence of incarceration in the higher courts (adult and children’s). In contrast, in the lower courts, Indigenous defendants were more likely to be imprisoned than non-Indigenous defendants when sentenced under statistically similar circumstances.

Determinants of health costs due to farmers’ exposure to pesticides: an empirical analysis

Pesticide spraying by farmers has an adverse impact on their health. However, in studies to date examining farmers’ exposure to pesticides, the costs of ill health and their determinants have been based on information provided by farmers themselves. Some doubt has therefore been cast on the reliability of these estimates. In this study, we address this by conducting surveys among two groups of farmers who use pesticides on a regular basis. The first group is made up of farmers who perceive that their ill health is due to exposure to pesticides and have obtained at least some form of treatment (described in this article as the ‘general farmer group’). The second group is composed of farmers whose ill health has been diagnosed by doctors and who have been treated in hospital for exposure to pesticides (described here as the ‘hospitalised farmer group’). Cost comparisons are made between the two groups of farmers. Regression analysis of the determinants of health costs show that the most important determinants of medical costs for both samples are the defensive expenditure, the quantity of pesticides used per acre per month, frequency of pesticide use and number of pesticides used per hour per day. The results have important policy implications.

The impact of litigation risk on corporate prospective disclosure : a review of the empirical literature

We review the literature on the impact of litigation risk (a form of external governance) on corporate prospective disclosure decisions as reflected in management earnings forecasts. From this analysis we identify four key areas for future research. First, litigation risk warrants more attention from researchers; currently it tends to be treated as a secondary factor impacting MEF decisions. Second, it would be informative from a governance perspective for researchers to explore why litigation risk has a differential impact on MEF decisions across countries. Third, understanding the interaction between litigation risk and forecast/firm-specific characteristics is important from management, investor and regulatory perspectives but is currently under-explored Last, research on the litigation risk and MEF attributes link is piecemeal and incomplete, requiring more integrated and expanded analysis.

Analyses of systems theory for construction accident prevention with specific reference to OSHA accident reports

To enhance workplace safety in the construction industry it is important to understand interrelationships among safety risk factors associated with construction accidents. This study incorporates the systems theory into Heinrich’s domino theory to explore the interrelationships of risks and break the chain of accident causation. Through both empirical and statistical analyses of 9,358 accidents which occurred in the U.S. construction industry between 2002 and 2011, the study investigates relationships between accidents and injury elements (e.g., injury type, part of body, injury severity) and the nature of construction injuries by accident type. The study then discusses relationships between accidents and risks, including worker behavior, injury source, and environmental condition, and identifies key risk factors and risk combinations causing accidents. The research outcomes will assist safety managers to prioritize risks according to the likelihood of accident occurrence and injury characteristics, and pay more attention to balancing significant risk relationships to prevent accidents and achieve safer working environments.

Impact fees and new housing cost: A comparative analysis of the empirical models

Developers and policy makers are consistently at odds over the debate as to whether impact fees increase house prices. This debate continues despite the extensive body of theoretical and empirical international literature that discusses the passing on to home buyers of impact fees, and the corresponding increase to housing prices. In attempting to quantify this impact, over a dozen empirical studies have been carried out in the US and Canada since the 1980’s. However the methodologies used vary greatly, as do the results. Despite similar infrastructure funding policies in numerous developed countries, no such empirical works exist outside of the US/Canada. The purpose of this research is to analyse the existing econometric models in order to identify, compare and contrast the theoretical bases, methodologies, key assumptions and findings of each. This research will assist in identifying if further model development is required and/or whether any of these models have external validity and are readily transferable outside of the US. The findings conclude that there is very little explicit rationale behind the various model selections and that significant model deficiencies appear still to exist.

Empirical analysis of the effect of dimension reduction and word order on semantic vectors

The aim of this paper is to provide a comparison of various algorithms and parameters to build reduced semantic spaces. The effect of dimension reduction, the stability of the representation and the effect of word order are examined in the context of the five algorithms bearing on semantic vectors: Random projection (RP), singular value decom- position (SVD), non-negative matrix factorization (NMF), permutations and holographic reduced representations (HRR). The quality of semantic representation was tested by means of synonym finding task using the TOEFL test on the TASA corpus. Dimension reduction was found to improve the quality of semantic representation but it is hard to find the optimal parameter settings. Even though dimension reduction by RP was found to be more generally applicable than SVD, the semantic vectors produced by RP are somewhat unstable. The effect of encoding word order into the semantic vector representation via HRR did not lead to any increase in scores over vectors constructed from word co-occurrence in context information. In this regard, very small context windows resulted in better semantic vectors for the TOEFL test.

Automatic Audio Segmentation Using the Generalized Likelihood Ratio

This paper presents a novel technique for segmenting an audio stream into homogeneous regions according to speaker identities, background noise, music, environmental and channel conditions. Audio segmentation is useful in audio diarization systems, which aim to annotate an input audio stream with information that attributes temporal regions of the audio into their specific sources. The segmentation method introduced in this paper is performed using the Generalized Likelihood Ratio (GLR), computed between two adjacent sliding windows over preprocessed speech. This approach is inspired by the popular segmentation method proposed by the pioneering work of Chen and Gopalakrishnan, using the Bayesian Information Criterion (BIC) with an expanding search window. This paper will aim to identify and address the shortcomings associated with such an approach. The result obtained by the proposed segmentation strategy is evaluated on the 2002 Rich Transcription (RT-02) Evaluation dataset, and a miss rate of 19.47% and a false alarm rate of 16.94% is achieved at the optimal threshold.

Eigenvoice modeling for cross likelihood ratio based speaker clustering : a Bayesian approach

This paper proposes the use of Bayesian approaches with the cross likelihood ratio (CLR) as a criterion for speaker clustering within a speaker diarization system, using eigenvoice modeling techniques. The CLR has previously been shown to be an effective decision criterion for speaker clustering using Gaussian mixture models. Recently, eigenvoice modeling has become an increasingly popular technique, due to its ability to adequately represent a speaker based on sparse training data, as well as to provide an improved capture of differences in speaker characteristics. The integration of eigenvoice modeling into the CLR framework to capitalize on the advantage of both techniques has also been shown to be beneficial for the speaker clustering task. Building on that success, this paper proposes the use of Bayesian methods to compute the conditional probabilities in computing the CLR, thus effectively combining the eigenvoice-CLR framework with the advantages of a Bayesian approach to the diarization problem. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 33.5% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.

The role of the Internet on export market growth : an empirical study in Latin America

The Internet has been shown to positively influence the export activities of firms from developed countries. However, the literature is vague as to whether the Internet has an impact on the export market growth of firms form developing countries. This paper examines of a cross-national sample of 204 firms from a Latin American country (Chile). The results show that Internet marketing activities positively influence information availability and business relationships, which lead to an increase in export market growth. The findings indicate that the Internet influences not only information availability for export performance but also business relationships generally thought to be face to face interactions in nature.