Developing emerging leaders in the library profession : program content, self-efficacy and leadership

This thesis used experimental and qualitative methods to determine that a typical, formal library leadership development intervention significantly enhanced the leadership self-efficacy of participants. The investigation also ascertained what program content and attributes affected leadership self-efficacy and how these elements either deterred or enhanced leadership self-efficacy development. Self-efficacy is critical to leadership emergence and effectiveness. Leadership succession has been identified as an issue in the library profession and society as a whole. The research confirmed that leadership development interventions with appropriate structure and content can be an effective mechanism to foster the emergence of leaders.

Do good things and talk about them : a theory of academics usage of enterprise social networks for impression management tactics

Enterprise social networks provide benefits especially for knowledge-intensive work as they enable communication, collaboration and knowledge exchange. These platforms should therefore lead to increased adoption and use by knowledge-intensive workers such as consultants or indeed researchers. Our interest is in ascertaining whether scientific researchers use enterprise social networks as part of their work practices. This focus is motivated by an apparent schism between a need for researchers to exchange knowledge and profile themselves, and the aversion to sharing breakthrough ideas and joining in an ever-increasing publishing and marketing game. We draw on research on academic work practices and impression management to develop a model of academics’ ESN usage for impression management tactics. We describe important constructs of our model, offer strategies for their operationalization and give an outlook to our ongoing empirical study of the use of an ESN platform by 20 schools across six faculties at an Australian university.

A continental-scale tool for acoustic identification of European bats

Summary 1. Acoustic methods are used increasingly to survey and monitor bat populations. However, the use of acoustic methods at continental scales can be hampered by the lack of standardized and objective methods to identify all species recorded. This makes comparable continent-wide monitoring difficult, impeding progress towards developing biodiversity indicators, transboundary conservation programmes and monitoring species distribution changes. 2. Here we developed a continental-scale classifier for acoustic identification of bats, which can be used throughout Europe to ensure objective, consistent and comparable species identifications. We selected 1350 full-spectrum reference calls from a set of 15 858 calls of 34 European species, from EchoBank, a global echolocation call library. We assessed 24 call parameters to evaluate how well they distinguish between species and used the 12 most useful to train a hierarchy of ensembles of artificial neural networks to distinguish the echolocation calls of these bat species. 3. Calls are first classified to one of five call-type groups, with a median accuracy of 97·6%. The median species-level classification accuracy is 83·7%, providing robust classification for most European species, and an estimate of classification error for each species. 4. These classifiers were packaged into an online tool, iBatsID, which is freely available, enabling anyone to classify European calls in an objective and consistent way, allowing standardized acoustic identification across the continent. 5. Synthesis and applications. iBatsID is the first freely available and easily accessible continental- scale bat call classifier, providing the basis for standardized, continental acoustic bat monitoring in Europe. This method can provide key information to managers and conservation planners on distribution changes and changes in bat species activity through time.

Acoustic identification of 12 species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Exploring association between perceived importance of travel/traffic information and travel behaviour in natural disasters : a case study of the 2011 Brisbane floods

A sound understanding of travellers’ behavioural changes and adaptation when facing a natural disaster is a key factor in efficiently and effectively managing transport networks at such times. This study specifically investigates the importance of travel/traffic information and its impact on travel behaviour during natural disasters. Using the 2011 Brisbane flood as a case study, survey respondents’ perceptions of the importance of travel/traffic information before, during, and after the flood were modelled using random-effects ordered logit. A hysteresis phenomenon was observed: respondents’ perceptions of the importance of travel/traffic information increased during the flood, and although its perceived importance decreased after the flood, it did not return to the pre-flood level. Results also reveal that socio-demographic features (such as gender and age) have a significant impact on respondents’ perceptions of the importance of travel/traffic information. The roles of travel time and safety in a respondent’s trip planning are also significantly correlated to their perception of the importance of this information. The analysis further shows that during the flood, respondents generally thought that travel/traffic information was important, and adjusted their travel plans according to information received. When controlling for other factors, the estimated odds of changing routes and cancelling trips for a respondent who thought that travel/traffic information was important, are respectively about three times and seven times the estimated odds for a respondent who thought that travel/traffic information was not important. In contrast, after the flood, the influence of travel/traffic information on respondents’ travel behaviour diminishes. Finally, the analysis shows no evidence of the influence of travel/traffic information’s on respondents’ travel mode; this indicates that inducing travel mode change is a challenging task.

Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Tech Ed students strut their stuff: information literacy and a practical assignment

This reports a study that seeks to explore the experience of students majoring in technology and design in an undergraduate education degree. It examines their experiences in finding and using information for a practical assignment. In mapping the variation of the students' experience, the study uses a qualitative, interpretive approach to analyse the data, which was collected via one-to-one interviews. The analysis yielded five themes through which technology education students find and use information: interaction with others; experience (past and new); formal educational learning; the real world; and incidental occurrences. The intentions and strategies that form the students' approaches to finding and using information are discussed. So too are the implications for teaching practice.

Industry-government collaboration : Queensland's IT&T Strategy and the Information Industries Board

This paper presents a field study of the Queensland Information Technology and Telecommunications Industry Strategy (QITIS), and of the Information Industries Board (IIB), a joint industry-state government body established in 1992 to oversee the implementation of that strategy for the development of the IT&T Industry in Queensland. The aim of the study was to analyse differing stakeholder perspectives on the strategy and on its implementation by the IIB. The study forms part of a longer-term review which aims to develop methodologies for the selection of appropriate strategies for the IT&T Industry, and for the evaluation of outcomes of strategy.

Social interaction and the role of empathy in information and knowledge management

This article provides a general review of the literature on the nature and role of empathy in social interaction for information professionals working in a variety of information and knowledge environments. Relational agency theory (Edwards, 2005) is used asa framework to re-conceptualize education for empathic social interaction between information professionals and their clients. Past, present and future issues relevant to empathic interaction in information and knowledge management are discussed in the context of three shifts identified from the literature: (a) the continued increase in communication channels, both physical and virtual, for reference, information and re-search services, (b) the transition from the information age to the conceptual age and(c) the growing need for understanding of the affective paradigm in the information and knowledge professions. Findings from the literature review on the relationships between empathy and information behavior, social networking, knowledge management and information and knowledge services are presented. Findings are discussed in relation to the development of guidelines for the affective education and training of information and knowledge professionals and the potential use of virtual learning software such as Second Life in developing empathic communication skills

Citizens and social media in times of natural disaster: Exploring information experience

Introduction. Social media is becoming a vital source of information in disaster or emergency situations. While a growing number of studies have explored the use of social media in natural disasters by emergency staff, military personnel, medial and other professionals, very few studies have investigated the use of social media by members of the public. The purpose of this paper is to explore citizens’ information experiences in social media during times of natural disaster. Method. A qualitative research approach was applied. Data was collected via in-depth interviews. Twenty-five people who used social media during a natural disaster in Australia participated in the study. Analysis. Audio recordings of interviews and interview transcripts provided the empirical material for data analysis. Data was analysed using structural and focussed coding methods. Results. Eight key themes depicting various aspects of participants’ information experience during a natural disaster were uncovered by the study: connected; wellbeing; coping; help; brokerage; journalism; supplementary and characteristics. Conclusion. This study contributes insights into social media’s potential for developing community disaster resilience and promotes discussion about the value of civic participation in social media when such circumstances occur. These findings also contribute to our understanding of information experiences as a new informational research object.