Ethical dilemmas : a model to understand teacher practice

Over recent decades, the field of ethics has been the focus of increasing attention in teaching. This is not surprising given that teaching is a moral activity that is heavily values-laden. Because of this, teachers face ethical dilemmas in the course of their daily work. This paper presents an ethical decision-making model that helps to explain the decision-making processes that individuals or groups are likely to experience when confronted by an ethical dilemma. In order to make sense of the model, we put forward three short ethical dilemma scenarios facing teachers and apply the model to interpret them. Here we identify the critical incident, the forces at play that help to illuminate the incident, the choices confronting the individual and the implications of these choices for the individual, organization and community. Based on our analysis and the wider literature we identify several strategies that may help to minimize the impact of ethical dilemmas. These include the importance of sharing dilemmas with trusted others; having institutional structures in schools that lessen the emergence of harmful actions occurring; the necessity for individual teachers to articulate their own personal and professional ethics; acknowledging that dilemmas have multiple forces at play; the need to educate colleagues about specific issues; and the necessity of appropriate preparation and support for teachers. Of these strategies, providing support for teachers via professional development is explored more fully.

Whole-proteome phylogeny of large dsDNA viruses and parvoviruses through a composition vector method related to dynamical language model

Background The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes. Results In this paper, the DL method is used to analyze the whole-proteome phylogeny of 124 large dsDNA viruses and 30 parvoviruses, two data sets with large difference in genome size. The trees from our analyses are in good agreement to the latest classification of large dsDNA viruses and parvoviruses by the International Committee on Taxonomy of Viruses (ICTV). Conclusions The present method provides a new way for recovering the phylogeny of large dsDNA viruses and parvoviruses, and also some insights on the affiliation of a number of unclassified viruses. In comparison, some alignment-free methods such as the CV Tree method can be used for recovering the phylogeny of large dsDNA viruses, but they are not suitable for resolving the phylogeny of parvoviruses with a much smaller genome size.

The psychosocial factors influencing aggressive driving behaviour

Many drivers in highly motorised countries believe that aggressive driving is increasing. While the prevalence of the behaviour is difficult to reliably identify, the consequences of on-road aggression can be severe, with extreme cases resulting in property damage, injury and even death. This research program was undertaken to explore the nature of aggressive driving from within the framework of relevant psychological theory in order to enhance our understanding of the behaviour and to inform the development of relevant interventions. To guide the research a provisional ‘working’ definition of aggressive driving was proposed encapsulating the recurrent characteristics of the behaviour cited in the literature. The definition was: “aggressive driving is any on-road behaviour adopted by a driver that is intended to cause physical or psychological harm to another road user and is associated with feelings of frustration, anger or threat”. Two main theoretical perspectives informed the program of research. The first was Shinar’s (1998) frustration-aggression model, which identifies both the person-related and situational characteristics that contribute to aggressive driving, as well as proposing that aggressive behaviours can serve either an ‘instrumental’ or ‘hostile’ function. The second main perspective was Anderson and Bushman’s (2002) General Aggression Model. In contrast to Shinar’s model, the General Aggression Model reflects a broader perspective on human aggression that facilitates a more comprehensive examination of the emotional and cognitive aspects of aggressive behaviour. Study One (n = 48) examined aggressive driving behaviour from the perspective of young drivers as an at-risk group and involved conducting six focus groups, with eight participants in each. Qualitative analyses identified multiple situational and person-related factors that contribute to on-road aggression. Consistent with human aggression theory, examination of self-reported experiences of aggressive driving identified key psychological elements and processes that are experienced during on-road aggression. Participants cited several emotions experienced during an on-road incident: annoyance, frustration, anger, threat and excitement. Findings also suggest that off-road generated stress may transfer to the on-road environment, at times having severe consequences including crash involvement. Young drivers also appeared quick to experience negative attributions about the other driver, some having additional thoughts of taking action. Additionally, the results showed little difference between males and females in the severity of behavioural responses they were prepared to adopt, although females appeared more likely to displace their negative emotions. Following the self-reported on-road incident, evidence was also found of a post-event influence, with females being more likely to experience ongoing emotional effects after the event. This finding was evidenced by ruminating thoughts or distraction from tasks. However, the impact of such a post-event influence on later behaviours or interpersonal interactions appears to be minimal. Study Two involved the quantitative analysis of n = 926 surveys completed by a wide age range of drivers from across Queensland. The study aimed to explore the relationships between the theoretical components of aggressive driving that were identified in the literature review, and refined based on the findings of Study One. Regression analyses were used to examine participant emotional, cognitive and behavioural responses to two differing on-road scenarios whilst exploring the proposed theoretical framework. A number of socio-demographic, state and trait person-related variables such as age, pre-study emotions, trait aggression and problem-solving style were found to predict the likelihood of a negative emotional response such as frustration, anger, perceived threat, negative attributions and the likelihood of adopting either an instrumental or hostile behaviour in response to Scenarios One and Two. Complex relationships were found to exist between the variables, however, they were interpretable based on the literature review findings. Factor analysis revealed evidence supporting Shinar’s (1998) dichotomous description of on-road aggressive behaviours as being instrumental or hostile. The second stage of Study Two used logistic regression to examine the factors that predicted the potentially hostile aggressive drivers (n = 88) within the sample. These drivers were those who indicated a preparedness to engage in direct acts of interpersonal aggression on the road. Young, male drivers 17–24 years of age were more likely to be classified as potentially hostile aggressive drivers. Young drivers (17–24 years) also scored significantly higher than other drivers on all subscales of the Aggression Questionnaire (Buss & Perry, 1992) and on the ‘negative problem orientation’ and ‘impulsive careless style’ subscales of the Social Problem Solving Inventory – Revised (D’Zurilla, Nezu & Maydeu-Olivares, 2002). The potentially hostile aggressive drivers were also significantly more likely to engage in speeding and drink/drug driving behaviour. With regard to the emotional, cognitive and behavioural variables examined, the potentially hostile aggressive driver group also scored significantly higher than the ‘other driver’ group on most variables examined in the proposed theoretical framework. The variables contained in the framework of aggressive driving reliably distinguished potentially hostile aggressive drivers from other drivers (Nagalkerke R2 = .39). Study Three used a case study approach to conduct an in-depth examination of the psychosocial characteristics of n = 10 (9 males and 1 female) self-confessed hostile aggressive drivers. The self-confessed hostile aggressive drivers were aged 24–55 years of age. A large proportion of these drivers reported a Year 10 education or better and average–above average incomes. As a group, the drivers reported committing a number of speeding and unlicensed driving offences in the past three years and extensive histories of violations outside of this period. Considerable evidence was also found of exposure to a range of developmental risk factors for aggression that may have contributed to the driver’s on-road expression of aggression. These drivers scored significantly higher on the Aggression Questionnaire subscales and Social Problem Solving Inventory Revised subscales, ‘negative problem orientation’ and ‘impulsive/careless style’, than the general sample of drivers included in Study Two. The hostile aggressive driver also scored significantly higher on the Barrett Impulsivity Scale – 11 (Patton, Stanford & Barratt, 1995) measure of impulsivity than a male ‘inmate’, or female ‘general psychiatric’ comparison group. Using the Carlson Psychological Survey (Carlson, 1982), the self-confessed hostile aggressive drivers scored equal or higher scores than the comparison group of incarcerated individuals on the subscale measures of chemical abuse, thought disturbance, anti-social tendencies and self-depreciation. Using the Carlson Psychological Survey personality profiles, seven participants were profiled ‘markedly anti-social’, two were profiled ‘negative-explosive’ and one was profiled as ‘self-centred’. Qualitative analysis of the ten case study self-reports of on-road hostile aggression revealed a similar range of on-road situational factors to those identified in the literature review and Study One. Six of the case studies reported off-road generated stress that they believed contributed to the episodes of aggressive driving they recalled. Intense ‘anger’ or ‘rage’ were most frequently used to describe the emotions experienced in response to the perceived provocation. Less frequently ‘excitement’ and ‘fear’ were cited as relevant emotions. Notably, five of the case studies experienced difficulty articulating their emotions, suggesting emotional difficulties. Consistent with Study Two, these drivers reported negative attributions and most had thoughts of aggressive actions they would like to take. Similarly, these drivers adopted both instrumental and hostile aggressive behaviours during the self-reported incident. Nine participants showed little or no remorse for their behaviour and these drivers also appeared to exhibit low levels of personal insight. Interestingly, few incidents were brought to the attention of the authorities. Further, examination of the person-related characteristics of these drivers indicated that they may be more likely to have come from difficult or dysfunctional backgrounds and to have a history of anti-social behaviours on and off the road. The research program has several key theoretical implications. While many of the findings supported Shinar’s (1998) frustration-aggression model, two key areas of difference emerged. Firstly, aggressive driving behaviour does not always appear to be frustration driven, but can also be driven by feelings of excitation (consistent with the tenets of the General Aggression Model). Secondly, while the findings supported a distinction being made between instrumental and hostile aggressive behaviours, the characteristics of these two types of behaviours require more examination. For example, Shinar (1998) proposes that a driver will adopt an instrumental aggressive behaviour when their progress is impeded if it allows them to achieve their immediate goals (e.g. reaching their destination as quickly as possible); whereas they will engage in hostile aggressive behaviour if their path to their goal is blocked. However, the current results question this assertion, since many of the hostile aggressive drivers studied appeared prepared to engage in hostile acts irrespective of whether their goal was blocked or not. In fact, their behaviour appeared to be characterised by a preparedness to abandon their immediate goals (even if for a short period of time) in order to express their aggression. The use of the General Aggression Model enabled an examination of the three components of the ‘present internal state’ comprising emotions, cognitions and arousal and how these influence the likelihood of a person responding aggressively to an on-road situation. This provided a detailed insight into both the cognitive and emotional aspects of aggressive driving that have important implications for the design of relevant countermeasures. For example, the findings highlighted the potential value of utilising Cognitive Behavioural Therapy with aggressive drivers, particularly the more hostile offenders. Similarly, educational efforts need to be mindful of the way that person-related factors appear to influence one’s perception of another driver’s behaviour as aggressive or benign. Those drivers with a predisposition for aggression were more likely to perceive aggression or ‘wrong doing’ in an ambiguous on-road situation and respond with instrumental and/or hostile behaviour, highlighting the importance of perceptual processes in aggressive driving behaviour.

Melanoma mouse model implicates metabotropic glutamate signaling in melanocytic neoplasia

To gain insight into melanoma pathogenesis, we characterized an insertional mouse mutant, TG3, that is predisposed to develop multiple melanomas. Physical mapping identified multiple tandem insertions of the transgene into intron 3 of Grm1 (encoding metabotropic glutamate receptor 1) with concomitant deletion of 70 kb of intronic sequence. To assess whether this insertional mutagenesis event results in alteration of transcriptional regulation, we analyzed Grm1 and two flanking genes for aberrant expression in melanomas from TG3 mice. We observed aberrant expression of only Grm1. Although we did not detect its expression in normal mouse melanocytes, Grm1 was ectopically expressed in the melanomas from TG3 mice. To confirm the involvement of Grm1 in melanocytic neoplasia, we created an additional transgenic line with Grm1 expression driven by the dopachrome tautomerase promoter. Similar to the original TG3, the Tg(Grm1)EPv line was susceptible to melanoma. In contrast to human melanoma, these transgenic mice had a generalized hyperproliferation of melanocytes with limited transformation to fully malignant metastasis. We detected expression of GRM1 in a number of human melanoma biopsies and cell lines but not in benign nevi and melanocytes. This study provides compelling evidence for the importance of metabotropic glutamate signaling in melanocytic neoplasia.

A capability model to improve infrastructure asset performance

Infrastructure organizations are operating in an increasingly challenging business environment as a result of globalization, privatization and deregulation. In an external business environment that is constantly changing, extant literature on strategic management advocates the need to focus on factors internal to the organization such as resources and capabilities to sustain their performance. Specifically, they need to develop dynamic capabilities in order to survive and prosper under conditions of change. The aim of this paper is to explore the dynamic capabilities needed in the management of transport infrastructure assets using a multiple case study research strategy. This paper produced a number of findings. First, the empirical evidence showed that the core infrastructure asset management processes are capacity management, options evaluation, procurement & delivery, maintenance management, and asset information management. Second, the study identified five dynamic capabilities namely stakeholder connectivity, cross-functional, relational, technology absorptive and integrated information capability as central to executing the strategic infrastructure asset management processes well. These findings culminate in the development of a capability model to improve the performance of infrastructure assets in an increasingly dynamic business environment.

Beyond MOF constraints : multiple constraint set metamodelling for lifecycle management

The management of models over time in many domains requires different constraints to apply to some parts of the model as it evolves. Using EMF and its meta-language Ecore, the development of model management code and tools usually relies on the meta- model having some constraints, such as attribute and reference cardinalities and changeability, set in the least constrained way that any model user will require. Stronger versions of these constraints can then be enforced in code, or by attaching additional constraint expressions, and their evaluations engines, to the generated model code. We propose a mechanism that allows for variations to the constraining meta-attributes of metamodels, to allow enforcement of different constraints at different lifecycle stages of a model. We then discuss the implementation choices within EMF to support the validation of a state-specific metamodel on model graphs when changing states, as well as the enforcement of state-specific constraints when executing model change operations.

Interactive processes link the multiple symptoms of fatigue in sport competition

Muscle physiologists often describe fatigue simply as a decline of muscle force and infer this causes an athlete to slow down. In contrast, exercise scientists describe fatigue during sport competition more holistically as an exercise-induced impairment of performance. The aim of this review is to reconcile the different views by evaluating the many performance symptoms/measures and mechanisms of fatigue. We describe how fatigue is assessed with muscle, exercise or competition performance measures. Muscle performance (single muscle test measures) declines due to peripheral fatigue (reduced muscle cell force) and/or central fatigue (reduced motor drive from the CNS). Peak muscle force seldom falls by >30% during sport but is often exacerbated during electrical stimulation and laboratory exercise tasks. Exercise performance (whole-body exercise test measures) reveals impaired physical/technical abilities and subjective fatigue sensations. Exercise intensity is initially sustained by recruitment of new motor units and help from synergistic muscles before it declines. Technique/motor skill execution deviates as exercise proceeds to maintain outcomes before they deteriorate, e.g. reduced accuracy or velocity. The sensation of fatigue incorporates an elevated rating of perceived exertion (RPE) during submaximal tasks, due to a combination of peripheral and higher CNS inputs. Competition performance (sport symptoms) is affected more by decision-making and psychological aspects, since there are opponents and a greater importance on the result. Laboratory based decision making is generally faster or unimpaired. Motivation, self-efficacy and anxiety can change during exercise to modify RPE and, hence, alter physical performance. Symptoms of fatigue during racing, team-game or racquet sports are largely anecdotal, but sometimes assessed with time-motion analysis. Fatigue during brief all-out racing is described biomechanically as a decline of peak velocity, along with altered kinematic components. Longer sport events involve pacing strategies, central and peripheral fatigue contributions and elevated RPE. During match play, the work rate can decline late in a match (or tournament) and/or transiently after intense exercise bursts. Repeated sprint ability, agility and leg strength become slightly impaired. Technique outcomes, such as velocity and accuracy for throwing, passing, hitting and kicking, can deteriorate. Physical and subjective changes are both less severe in real rather than simulated sport activities. Little objective evidence exists to support exercise-induced mental lapses during sport. A model depicting mind-body interactions during sport competition shows that the RPE centre-motor cortex-working muscle sequence drives overall performance levels and, hence, fatigue symptoms. The sporting outputs from this sequence can be modulated by interactions with muscle afferent and circulatory feedback, psychological and decision-making inputs. Importantly, compensatory processes exist at many levels to protect against performance decrements. Small changes of putative fatigue factors can also be protective. We show that individual fatigue factors including diminished carbohydrate availability, elevated serotonin, hypoxia, acidosis, hyperkalaemia, hyperthermia, dehydration and reactive oxygen species, each contribute to several fatigue symptoms. Thus, multiple symptoms of fatigue can occur simultaneously and the underlying mechanisms overlap and interact. Based on this understanding, we reinforce the proposal that fatigue is best described globally as an exercise-induced decline of performance as this is inclusive of all viewpoints.

Towards automatic object segmentation with sequential multiple views

Object segmentation is one of the fundamental steps for a number of robotic applications such as manipulation, object detection, and obstacle avoidance. This paper proposes a visual method for incorporating colour and depth information from sequential multiview stereo images to segment objects of interest from complex and cluttered environments. Rather than segmenting objects using information from a single frame in the sequence, we incorporate information from neighbouring views to increase the reliability of the information and improve the overall segmentation result. Specifically, dense depth information of a scene is computed using multiple view stereo. Depths from neighbouring views are reprojected into the reference frame to be segmented compensating for imperfect depth computations for individual frames. The multiple depth layers are then combined with color information from the reference frame to create a Markov random field to model the segmentation problem. Finally, graphcut optimisation is employed to infer pixels belonging to the object to be segmented. The segmentation accuracy is evaluated over images from an outdoor video sequence demonstrating the viability for automatic object segmentation for mobile robots using monocular cameras as a primary sensor.

Validating the is-impact model in the Malaysian public sector

This research is one of several ongoing studies conducted within the IT Professional Services (ITPS) research programme at Queensland University of Technology (QUT). In 2003, ITPS introduced the IS-Impact model, a measurement model for measuring information systems success from the viewpoint of multiple stakeholders. The model, along with its instrument, is robust, simple, yet generalisable, and yields results that are comparable across time, stakeholders, different systems and system contexts. The IS-Impact model is defined as “a measure at a point in time, of the stream of net benefits from the Information System (IS), to date and anticipated, as perceived by all key-user-groups”. The model represents four dimensions, which are ‘Individual Impact’, ‘Organizational Impact’, ‘Information Quality’ and ‘System Quality’. The two Impact dimensions measure the up-to-date impact of the evaluated system, while the remaining two Quality dimensions act as proxies for probable future impacts (Gable, Sedera & Chan, 2008). To fulfil the goal of ITPS, “to develop the most widely employed model” this research re-validates and extends the IS-Impact model in a new context. This method/context-extension research aims to test the generalisability of the model by addressing known limitations of the model. One of the limitations of the model relates to the extent of external validity of the model. In order to gain wide acceptance, a model should be consistent and work well in different contexts. The IS-Impact model, however, was only validated in the Australian context, and packaged software was chosen as the IS understudy. Thus, this study is concerned with whether the model can be applied in another different context. Aiming for a robust and standardised measurement model that can be used across different contexts, this research re-validates and extends the IS-Impact model and its instrument to public sector organisations in Malaysia. The overarching research question (managerial question) of this research is “How can public sector organisations in Malaysia measure the impact of information systems systematically and effectively?” With two main objectives, the managerial question is broken down into two specific research questions. The first research question addresses the applicability (relevance) of the dimensions and measures of the IS-Impact model in the Malaysian context. Moreover, this research question addresses the completeness of the model in the new context. Initially, this research assumes that the dimensions and measures of the IS-Impact model are sufficient for the new context. However, some IS researchers suggest that the selection of measures needs to be done purposely for different contextual settings (DeLone & McLean, 1992, Rai, Lang & Welker, 2002). Thus, the first research question is as follows, “Is the IS-Impact model complete for measuring the impact of IS in Malaysian public sector organisations?” [RQ1]. The IS-Impact model is a multidimensional model that consists of four dimensions or constructs. Each dimension is represented by formative measures or indicators. Formative measures are known as composite variables because these measures make up or form the construct, or, in this case, the dimension in the IS-Impact model. These formative measures define different aspects of the dimension, thus, a measurement model of this kind needs to be tested not just on the structural relationship between the constructs but also the validity of each measure. In a previous study, the IS-Impact model was validated using formative validation techniques, as proposed in the literature (i.e., Diamantopoulos and Winklhofer, 2001, Diamantopoulos and Siguaw, 2006, Petter, Straub and Rai, 2007). However, there is potential for improving the validation testing of the model by adding more criterion or dependent variables. This includes identifying a consequence of the IS-Impact construct for the purpose of validation. Moreover, a different approach is employed in this research, whereby the validity of the model is tested using the Partial Least Squares (PLS) method, a component-based structural equation modelling (SEM) technique. Thus, the second research question addresses the construct validation of the IS-Impact model; “Is the IS-Impact model valid as a multidimensional formative construct?” [RQ2]. This study employs two rounds of surveys, each having a different and specific aim. The first is qualitative and exploratory, aiming to investigate the applicability and sufficiency of the IS-Impact dimensions and measures in the new context. This survey was conducted in a state government in Malaysia. A total of 77 valid responses were received, yielding 278 impact statements. The results from the qualitative analysis demonstrate the applicability of most of the IS-Impact measures. The analysis also shows a significant new measure having emerged from the context. This new measure was added as one of the System Quality measures. The second survey is a quantitative survey that aims to operationalise the measures identified from the qualitative analysis and rigorously validate the model. This survey was conducted in four state governments (including the state government that was involved in the first survey). A total of 254 valid responses were used in the data analysis. Data was analysed using structural equation modelling techniques, following the guidelines for formative construct validation, to test the validity and reliability of the constructs in the model. This study is the first research that extends the complete IS-Impact model in a new context that is different in terms of nationality, language and the type of information system (IS). The main contribution of this research is to present a comprehensive, up-to-date IS-Impact model, which has been validated in the new context. The study has accomplished its purpose of testing the generalisability of the IS-Impact model and continuing the IS evaluation research by extending it in the Malaysian context. A further contribution is a validated Malaysian language IS-Impact measurement instrument. It is hoped that the validated Malaysian IS-Impact instrument will encourage related IS research in Malaysia, and that the demonstrated model validity and generalisability will encourage a cumulative tradition of research previously not possible. The study entailed several methodological improvements on prior work, including: (1) new criterion measures for the overall IS-Impact construct employed in ‘identification through measurement relations’; (2) a stronger, multi-item ‘Satisfaction’ construct, employed in ‘identification through structural relations’; (3) an alternative version of the main survey instrument in which items are randomized (rather than blocked) for comparison with the main survey data, in attention to possible common method variance (no significant differences between these two survey instruments were observed); (4) demonstrates a validation process of formative indexes of a multidimensional, second-order construct (existing examples mostly involved unidimensional constructs); (5) testing the presence of suppressor effects that influence the significance of some measures and dimensions in the model; and (6) demonstrates the effect of an imbalanced number of measures within a construct to the contribution power of each dimension in a multidimensional model.

Test of a model of the effects of parental illness on youth and family functioning

Objective: Parental illness (PI) may have adverse impacts on youth and family functioning. Research in this area has suffered from the absence of a guiding comprehensive framework. This study tested a conceptual model of the effects of PI on youth and family functioning derived from the Family Ecology Framework (FEF; Pedersen & Revenson, 2005). Method. A total of 85 parents with multiple sclerosis and 127 youth completed questionnaires at Time 1 and 12 months later at Time 2. Results. Structural equation modeling results supported the FEF with regards to physical-illness disability. Specifically, the proposed mediators (role redistribution, stress, and stigma) were implicated in the processes that link parental disability to several domains of youth adjustment. The results suggest that the effects of parental depression (PD) are not mediated through these processes; rather, PD directly affects family functioning, which in turn mediates the effects onto youth adjustment. Family functioning further mediated between PD and youth well-being and behavioral-social difficulties. Conclusions. Although results support the effects of parental-illness disability on youth and family functioning via the proposed mediational mechanisms, the additive effects of PD on youth physical and mental health occur through direct and indirect (via family functioning) pathways, respectively.

An information literacy integration model and its application in higher education

Purpose - The purpose of this paper is to present a model for curricular integration of information literacy for undergraduate programs in higher education. Design/methodology/approach - Data are drawn from individual interviews at three universities in Australia and curricular integration working experience at a New Zealand university. Sociocultural theories are adopted in the research process and in the development of the model, Findings - Key characteristics of the curriculum integration of information literacy were identified and an information literacy integration model was developed. The S2J2 key behaviours for campus-wide multi-partner collaboration in information literacy integration were also identified. Research limitations/implications - The model was developed without including the employer needs. Through the process of further research, the point of view of the employer on how to provide information literacy education needs to be explored in order to strengthen the model in curricular design. Practical implications - The information literacy integration model was developed based on practical experience in higher education and has been applied in different undergraduate curricular programs. The model could be used or adapted by both librarians and academics when they integrate information literacy into an undergraduate curriculum from a lower level to a higher level. Originality/value - The information literacy integration model was developed based on recent PhD research. The model integrates curriculum, pedagogy and learning theories, information literacy theories, information literacy guidelines, people and collaborative together. The model provides a framework of how information literacy can be integrated into multiple courses across an undergraduate academic degree in higher education.

An aspect query language model based on query decomposition and high-order contextual term associations

In information retrieval (IR) research, more and more focus has been placed on optimizing a query language model by detecting and estimating the dependencies between the query and the observed terms occurring in the selected relevance feedback documents. In this paper, we propose a novel Aspect Language Modeling framework featuring term association acquisition, document segmentation, query decomposition, and an Aspect Model (AM) for parameter optimization. Through the proposed framework, we advance the theory and practice of applying high-order and context-sensitive term relationships to IR. We first decompose a query into subsets of query terms. Then we segment the relevance feedback documents into chunks using multiple sliding windows. Finally we discover the higher order term associations, that is, the terms in these chunks with high degree of association to the subsets of the query. In this process, we adopt an approach by combining the AM with the Association Rule (AR) mining. In our approach, the AM not only considers the subsets of a query as “hidden” states and estimates their prior distributions, but also evaluates the dependencies between the subsets of a query and the observed terms extracted from the chunks of feedback documents. The AR provides a reasonable initial estimation of the high-order term associations by discovering the associated rules from the document chunks. Experimental results on various TREC collections verify the effectiveness of our approach, which significantly outperforms a baseline language model and two state-of-the-art query language models namely the Relevance Model and the Information Flow model

Handling incomplete data in survival analysis with multiple covariates

This paper studies the missing covariate problem which is often encountered in survival analysis. Three covariate imputation methods are employed in the study, and the effectiveness of each method is evaluated within the hazard prediction framework. Data from a typical engineering asset is used in the case study. Covariate values in some time steps are deliberately discarded to generate an incomplete covariate set. It is found that although the mean imputation method is simpler than others for solving missing covariate problems, the results calculated by it can differ largely from the real values of the missing covariates. This study also shows that in general, results obtained from the regression method are more accurate than those of the mean imputation method but at the cost of a higher computational expensive. Gaussian Mixture Model (GMM) method is found to be the most effective method within these three in terms of both computation efficiency and predication accuracy.