Converting theory to practice : university-school collaboration on devising strategies for mentoring pedagogical knowledge

There appears no shortage of theorists for preservice teacher education; however many ideas are abandoned without practical applications. Indeed, it can take years for theories to materialise into practice, if they materialise at all. The quality of preservice teacher education is central for enhancing an education system, and mentors’ roles can assist to shape preservice teachers’ development within the school context. Yet mentoring can be haphazard without being underpinned by a theoretical framework. A mentoring model (personal attributes, system requirements, pedagogical knowledge, modelling, and feedback) has emerged from research and the literature to guide mentors’ practices. This qualitative study investigates mentors’ pedagogical knowledge as one factor crucial to the mentoring process. More specifically, this study involves a questionnaire and audio-recorded focus group meetings with experienced mentors (n=14) who deliberated on devising practical applications for mentoring pedagogical knowledge. Findings revealed that these experienced mentors pinpointed practical applications around a mentor’s role for providing pedagogical knowledge to the mentee. These strategies were varied and demonstrated that any one mentoring practice may be approached from a number of different angles. Nevertheless, there were core mentoring practices in pedagogical knowledge such as showing the mentee how to plan for teaching, articulating classroom management approaches, and talking about how to connect learning to assessment. Mentors may require education on current mentoring practices with practical strategies that are linked to theoretical underpinnings.

Occupational driver safety : conceptualising a leadership-based intervention to improve safe driving performance

Occupational driving crashes are the most common cause of death and injury in the workplace. The physical and psychological outcomes following injury are also very costly to organizations. Thus, safe driving poses a managerial challenge. Some research has attempted to address this issue through modifying discrete and often simple target behaviors (e.g., driver training programs). However, current intervention approaches in the occupational driving field generally do not consider the role of organizational factors in workplace safety. This study adopts the A-B-C framework to identify the contingencies associated with an effective exchange of safety information within the occupational driving context. Utilizing a sample of occupational drivers and their supervisors, this multi-level study examines the contingencies associated with the exchange of safety information within the supervisor-driver relationship. Safety values are identified as an antecedent of the safety information exchange, and the quality of the leader-member exchange relationship and safe driving performance is identified as the behavioral consequences. We also examine the function of role overload as a factor influencing the relationship between safety values and the safety information exchange. Hierarchical Linear Modelling found that role overload moderated the relationship between supervisors’ perceptions of the value given to safety and the safety information exchange. A significant relationship was also found between the safety information exchange and the subsequent quality of the leader-member exchange relationship. Finally, the quality of the leader-member exchange relationship was found to be significantly associated with safe driving performance. Theoretical and practical implications of these results are discussed.

Adaptive cache aware multiprocessor scheduling framework

Computer resource allocation represents a significant challenge particularly for multiprocessor systems, which consist of shared computing resources to be allocated among co-runner processes and threads. While an efficient resource allocation would result in a highly efficient and stable overall multiprocessor system and individual thread performance, ineffective poor resource allocation causes significant performance bottlenecks even for the system with high computing resources. This thesis proposes a cache aware adaptive closed loop scheduling framework as an efficient resource allocation strategy for the highly dynamic resource management problem, which requires instant estimation of highly uncertain and unpredictable resource patterns. Many different approaches to this highly dynamic resource allocation problem have been developed but neither the dynamic nature nor the time-varying and uncertain characteristics of the resource allocation problem is well considered. These approaches facilitate either static and dynamic optimization methods or advanced scheduling algorithms such as the Proportional Fair (PFair) scheduling algorithm. Some of these approaches, which consider the dynamic nature of multiprocessor systems, apply only a basic closed loop system; hence, they fail to take the time-varying and uncertainty of the system into account. Therefore, further research into the multiprocessor resource allocation is required. Our closed loop cache aware adaptive scheduling framework takes the resource availability and the resource usage patterns into account by measuring time-varying factors such as cache miss counts, stalls and instruction counts. More specifically, the cache usage pattern of the thread is identified using QR recursive least square algorithm (RLS) and cache miss count time series statistics. For the identified cache resource dynamics, our closed loop cache aware adaptive scheduling framework enforces instruction fairness for the threads. Fairness in the context of our research project is defined as a resource allocation equity, which reduces corunner thread dependence in a shared resource environment. In this way, instruction count degradation due to shared cache resource conflicts is overcome. In this respect, our closed loop cache aware adaptive scheduling framework contributes to the research field in two major and three minor aspects. The two major contributions lead to the cache aware scheduling system. The first major contribution is the development of the execution fairness algorithm, which degrades the co-runner cache impact on the thread performance. The second contribution is the development of relevant mathematical models, such as thread execution pattern and cache access pattern models, which in fact formulate the execution fairness algorithm in terms of mathematical quantities. Following the development of the cache aware scheduling system, our adaptive self-tuning control framework is constructed to add an adaptive closed loop aspect to the cache aware scheduling system. This control framework in fact consists of two main components: the parameter estimator, and the controller design module. The first minor contribution is the development of the parameter estimators; the QR Recursive Least Square(RLS) algorithm is applied into our closed loop cache aware adaptive scheduling framework to estimate highly uncertain and time-varying cache resource patterns of threads. The second minor contribution is the designing of a controller design module; the algebraic controller design algorithm, Pole Placement, is utilized to design the relevant controller, which is able to provide desired timevarying control action. The adaptive self-tuning control framework and cache aware scheduling system in fact constitute our final framework, closed loop cache aware adaptive scheduling framework. The third minor contribution is to validate this cache aware adaptive closed loop scheduling framework efficiency in overwhelming the co-runner cache dependency. The timeseries statistical counters are developed for M-Sim Multi-Core Simulator; and the theoretical findings and mathematical formulations are applied as MATLAB m-file software codes. In this way, the overall framework is tested and experiment outcomes are analyzed. According to our experiment outcomes, it is concluded that our closed loop cache aware adaptive scheduling framework successfully drives co-runner cache dependent thread instruction count to co-runner independent instruction count with an error margin up to 25% in case cache is highly utilized. In addition, thread cache access pattern is also estimated with 75% accuracy.

Human information behavior: Integrating diverse approaches and information use

For millennia humans have sought, organized, and used information as they learned and evolved patterns of human information behaviors to resolve their human problems and survive. However, despite the current focus on living in an "information age," we have a limited evolutionary understanding of human information behavior. In this article the authors examine the current three interdisciplinary approaches to conceptualizing how humans have sought information including (a) the everyday life information seeking-sense-making approach, (b) the information foraging approach, and (c) the problem-solution perspective on information seeking approach. In addition, due to the lack of clarity regarding the role of information use in information behavior, a fourth information approach is provided based on a theory of information use. The use theory proposed starts from an evolutionary psychology notion that humans are able to adapt to their environment and survive because of our modular cognitive architecture. Finally, the authors begin the process of conceptualizing these diverse approaches, and the various aspects or elements of these approaches, within an integrated model with consideration of information use. An initial integrated model of these different approaches with information use is proposed.

Quantitative approaches to content analysis : identifying conceptual drift across publication outlets

Unstructured text data, such as emails, blogs, contracts, academic publications, organizational documents, transcribed interviews, and even tweets, are important sources of data in Information Systems research. Various forms of qualitative analysis of the content of these data exist and have revealed important insights. Yet, to date, these analyses have been hampered by limitations of human coding of large data sets, and by bias due to human interpretation. In this paper, we compare and combine two quantitative analysis techniques to demonstrate the capabilities of computational analysis for content analysis of unstructured text. Specifically, we seek to demonstrate how two quantitative analytic methods, viz., Latent Semantic Analysis and data mining, can aid researchers in revealing core content topic areas in large (or small) data sets, and in visualizing how these concepts evolve, migrate, converge or diverge over time. We exemplify the complementary application of these techniques through an examination of a 25-year sample of abstracts from selected journals in Information Systems, Management, and Accounting disciplines. Through this work, we explore the capabilities of two computational techniques, and show how these techniques can be used to gather insights from a large corpus of unstructured text.

Nascent entrepreneurship

The past two decades have witnessed a surge in interest in the field of nascent entrepreneurship. In this collection, the editors successfully draw together the most important works that utilize the new real-time approaches for studying early stage entrepreneurial activity that were developed and refined in the last couple of decades. Providing the empirical, theoretical and methodological insights from some of the most influential researchers in this field, this book is an indispensable source of reference for researchers, students and others who have an interest in new venture creation and its role in the economy.

Theoretical and numerical investigation of bending properties of Cu nanowires

Based on the AFM-bending experiments, a molecular dynamics (MD) bending simulation model is established which could accurately account for the full spectrum of the mechanical properties of NWs in a double clamped beam configuration, ranging from elasticity to plasticity and failure. It is found that, loading rate exerts significant influence to the mechanical behaviours of nanowires (NWs). Specifically, a loading rate lower than 10 m/s is found reasonable for a homogonous bending deformation. Both loading rate and potential between the tip and the NW are found to play an important role in the adhesive phenomenon. The force versus displacement (F-d) curve from MD simulation is highly consistent in shapes with that from experiments. Symmetrical F-d curves during loading and unloading processes are observed, which reveal the linear-elastic and non-elastic bending deformation of NWs. The typical bending induced tensile-compressive features are observed. Meanwhile, the simulation results are excellently fitted by the classical Euler-Bernoulli beam theory with axial effect. It is concluded that, axial tensile force becomes crucial in bending deformation when the beam size is down to nanoscale for double clamped NWs. In addition, we find shorter NWs will have an earlier yielding and a larger yielding force. Mechanical properties (Young’s modulus & yield strength) obtained from both bending and tensile deformations are found comparable with each other. Specifically, the modulus is essentially similar under these two loading methods, while the yield strength during bending is observed larger than that during tension.

Trends in policies, programs and practices in the Australasian First Year Experience literature 2000-2010. The First Year in Higher Education Research Series on Evidence-based Practice. Number 1

This publication is the first in a series of scholarly reports on research-based practice related to the First Year Experience in Higher Education. This report synthesises evidence about practice-based initiatives and pragmatic approaches in Aotearoa (New Zealand) and Australia that aim to enhance the experience of commencing students in the higher education sector. Trends in policies, programs and practices ... examines the first year experience literature from 2000-2010. It acknowledges the uniqueness of the Australasian socio-political context and its influence on the interests and output of researchers. The review surveyed almost 400 empirical reports and conceptual discussions produced over the decade that dealt with the stakeholders, institutions and the higher education sector in Australasia. The literature is examined through two theoretical constructs or “lenses”: first, a set of first year curriculum design principles and second, the generational approach to describing the maturation of initiatives. These outcomes and suggested directions for further research provide the challenges and the opportunities for FYE adherents, both scholars and practitioners, to grapple with in the next decade.

A rebirth of physical activity in parents : applying a theory-based approach

Physical inactivity is a serious concern both nationally and internationally. Despite the numerous benefits of performing regular physical activity, many individuals lead sedentary lifestyles. Of concern, though, is research showing that some population sub-groups are less likely to be active, such as parents of young children. Although there is a vast amount of research dedicated to understanding people.s physical activity-related behaviours, there is a paucity of research examining those factors that influence parental physical activity. More importantly, research applying theoretical models to understand physical activity decision-making among this at-risk population is limited. Given the current obesity epidemic, the decline in physical activity with parenthood, and the many social and health benefits associated with regular physical activity, it is important that adults with young children are sufficiently active. In light of the dearth of research examining parental physical activity and the scant research applying a theory-based approach to gain this understanding, the overarching aim of the current program of research was to adopt a mixed methods approach as well as use sound theoretical frameworks to understand the regular physical activity behaviour of mothers and fathers with young children. This program of research comprised of three distinct stages: a qualitative stage exploring individual, social, and psychological factors that influence parental regular physical activity (Stage 1); a quantitative stage identifying the important predictors of parental regular physical activity intentions and behaviour using sound theoretical frameworks and testing a single-item measure for assessing parental physical activity behaviour (Stage 2); and a qualitative stage exploring strategies for an intervention program aimed at increasing parental regular physical activity (Stage 3). As a thesis by publication, eight papers report the findings of this program of research; these papers are presented according to the distinct stages of investigation that guided this program of research. Stage One of the research program comprised a qualitative investigation using a focus group/interview methodology with parents of children younger than 5 years of age (N = 40; n = 21 mothers, n = 19 fathers) (Papers 1, 2, and 3). Drawing broadly on a social constructionist approach (Paper 1), thematic analytic methods revealed parents. understandings of physical activity (e.g., requires effort), patterns of physical activity-related behaviours (e.g., grab it when you can, declining physical activity habits), and how constructions of social role expectations might influence parents. physical activity decision making (e.g., creating an active family culture, guilt and selfishness). Drawing on the belief-based framework of the TPB (Paper 2), thematic content analytic methods revealed parents. commonly held beliefs about the advantages (e.g., improves parenting practices), disadvantages (e.g., interferes with commitments), barriers (e.g., time), and facilitators (e.g., social support) to performing regular physical activity. Parents. normative beliefs about social approval from important others or groups (e.g., spouse/partner) were also identified. Guided by theories of social support, Paper Three identified parents. perceptions about the specific social support dimensions that influence their physical activity decision making. Thematic content analysis identified instrumental (e.g., providing childcare, taking over chores), emotional (e.g., encouragement, companionship), and informational support (e.g., ideas and advice) as being important to the decision-making of parents in relation to their regular physical activity behaviour. The results revealed also that having support for being active is not straightforward (e.g., guilt-related issues inhibited the facilitative nature of social support for physical activity). Stage Two of the research program comprised a quantitative examination of parents. physical activity intentions and behaviour (Papers 4, 5, 6, and 7). Parents completed an extended TPB questionnaire at Time 1 (N = 580; n = 288 mothers, n = 292 fathers) and self-reported their physical activity at Time 2, 1 week later (N = 458; n = 252 mothers, n = 206 fathers). Paper Four revealed key behavioural (e.g., improving parenting practices), normative (e.g., people I exercise with), and control (e.g., lack of time) beliefs as significant independent predictors of parental physical activity. A test of the TPB augmented to include the constructs of self-determined motivation and planning was assessed in Paper Five. The findings revealed that the effect of self-determined motivation on intention was fully mediated by the TPB variables and the impact of intention on behaviour was partially mediated by the planning variables. Slight differences in the model.s motivational sequence between the sexes were also noted. Paper Six investigated, within a TPB framework, a range of social influences on parents. intentions to be active. For both sexes, attitude, perceived behavioural control, group norms, friend general support, and an active parent identity predicted intentions, with subjective norms and family support further predicting mothers. intentions and descriptive norms further predicting fathers. intentions. Finally, the measurement of parental physical activity was investigated in Paper Seven of Stage Two. The results showed that parents are at risk of low levels of physical activity, with the findings also revealing validation support for a brief single-item physical activity measure. Stage Three of the research program comprised a qualitative examination of parents. (N = 12; n = 6 mothers, n = 6 fathers) ideas for strategies that may be useful for developing and delivering an intervention program aimed at increasing parental physical activity (Paper 8). Parents revealed a range of strategies for what to include in a physical activity intervention designed for parents of young children. For example, parents identified persuasion and information type messages, problem-solving strategies that engage parents in generating a priority list of their lifestyle commitments, and behavioural modification techniques such as goal setting and incentives. Social intervention strategies (e.g., social comparison, counselling) and environmental approaches (e.g., community-based integrative parent/child programs) were also identified as was a skill-based strategy in helping parents generate a flexible life/family plan. Additionally, a range of strategies for how to best deliver a parental physical activity intervention was discussed. Taken as a whole, Paper Eight found that adopting a multifaceted approach in both the design and implementation of a resultant physical activity intervention may be useful in helping to increase parental physical activity. Overall, this program of research found support for parents as a unique group who hold both similar and distinctive perceptions about regular physical activity to the general adult population. Thus, these findings highlight the importance of targeting intervention strategies for parents of young children. Additionally, the findings suggest that it might also be useful to tailor some messages specifically to each sex. Effective promotion of physical activity in parents of young children is essential given the low rate of activity in this population. Results from this program of research highlight parents as an at-risk group for inactivity and provide an important first step in identifying the factors that influence both mothers. and fathers. physical activity decision making. These findings, in turn, provide a foundation on which to build effective intervention programs aimed at increasing parents. regular physical activity which is essential for ensuring the health and well-being of parents with young children.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

The relationship between academic library usage and educational performance in Kuwait

University libraries play an important role in contributing to student and faculty members’ academic achievement. This study examines perceptions of university library usage to consider factors that influence achievement of students, academics and administrators. A thorough review of relevant literature examined approaches to determining user satisfaction of students and faculty, and factors that influence library usage. It highlighted the value of usage on educational performance. It enabled development of a theoretical framework leading to the Factors of Academic Library Usage (FALU) model, which was developed to investigate the effect of usage factors. FALU was tested in Kuwait university libraries. The study used validated questionnaires from 792 students, 143 academics and 121 administrators to measure five library factors. Interviews were conducted across the three University libraries. The findings are useful in measuring the correlation between the current academic library usage and educational performance.

Computational approaches to the visual validation of 3D virtual environments

Virtual environments can provide, through digital games and online social interfaces, extremely exciting forms of interactive entertainment. Because of their capability in displaying and manipulating information in natural and intuitive ways, such environments have found extensive applications in decision support, education and training in the health and science domains amongst others. Currently, the burden of validating both the interactive functionality and visual consistency of a virtual environment content is entirely carried out by developers and play-testers. While considerable research has been conducted in assisting the design of virtual world content and mechanics, to date, only limited contributions have been made regarding the automatic testing of the underpinning graphics software and hardware. The aim of this thesis is to determine whether the correctness of the images generated by a virtual environment can be quantitatively defined, and automatically measured, in order to facilitate the validation of the content. In an attempt to provide an environment-independent definition of visual consistency, a number of classification approaches were developed. First, a novel model-based object description was proposed in order to enable reasoning about the color and geometry change of virtual entities during a play-session. From such an analysis, two view-based connectionist approaches were developed to map from geometry and color spaces to a single, environment-independent, geometric transformation space; we used such a mapping to predict the correct visualization of the scene. Finally, an appearance-based aliasing detector was developed to show how incorrectness too, can be quantified for debugging purposes. Since computer games heavily rely on the use of highly complex and interactive virtual worlds, they provide an excellent test bed against which to develop, calibrate and validate our techniques. Experiments were conducted on a game engine and other virtual worlds prototypes to determine the applicability and effectiveness of our algorithms. The results show that quantifying visual correctness in virtual scenes is a feasible enterprise, and that effective automatic bug detection can be performed through the techniques we have developed. We expect these techniques to find application in large 3D games and virtual world studios that require a scalable solution to testing their virtual world software and digital content.

Reframing the design of context-aware computing

From location-aware computing to mining the social web, representations of context have promised to make better software applications. The opportunities and challenges of context-aware computing from representational, situated and interactional perspectives have been well documented, but arguments from the perspective of design are somewhat disparate. This paper draws on both theoretical perspectives and a design framing, using the problem of designing a social mobile agile ridesharing system, in order to reflect upon and call for broader design approaches for context-aware computing and human-computer Interaction research in general.

Classifying external causes of injury : history, current approaches, and future directions

The International Classification of Diseases (ICD) is used to categorise diseases, injuries and external causes, and is a key epidemiological tool enabling the storage and retrieval of data from health and vital records to produce core international mortality and morbidity statistics. The ICD is updated periodically to ensure the classification remains current and work is now underway to develop the next revision, ICD-11. There have been almost 20 years since the last ICD edition was published and over 60 years since the last substantial structural revision of the external causes chapter. Revision of such a critical tool requires transparency and documentation to ensure that changes made to the classification system are recorded comprehensively for future reference. In this paper, the authors provide a history of external causes classification development and outline the external cause structure. Approaches to manage ICD-10 deficiencies are discussed and the ICD-11 revision approach regarding the development of, rationale for and implications of proposed changes to the chapter are outlined. Through improved capture of external cause concepts in ICD-11, a stronger evidence base will be available to inform injury prevention, treatment, rehabilitation and policy initiatives to ultimately contribute to a reduction in injury morbidity and mortality.