Preservice teachers’ memories of their secondary science education experiences

Understanding preservice teachers’ memories of their education may aid towards articulating high-impact teaching practices. This study describes 246 preservice teachers’ perceptions of their secondary science education experiences through a questionnaire and 28-item survey. ANOVA was statistically significant about participants’ memories of science with 15 of the 28 survey items. Descriptive statistics through SPSS further showed that a teacher’s enthusiastic nature (87%) and positive attitude towards science (87%) were regarded as highly memorable. In addition, explaining abstract concepts well (79%), and guiding the students’ conceptual development with practical science activities (73%) may be considered as memorable secondary science teaching strategies. Implementing science lessons with one or more of these memorable science teaching practices may “make a difference” towards influencing high school students’ positive long-term memories about science and their science education. Further research in other key learning areas may provide a clearer picture of high-impact teaching and a way to enhance pedagogical practices.

Fusing curricula : science, technology and ICT

Curriculum demands continue to increase on school education systems with teachers at the forefront of implementing syllabus requirements. Education is reported frequently as a solution to most societal problems and, as a result of the world’s information explosion, teachers are expected to cover more and more within teaching programs. How can teachers combine subjects in order to capitalise on the competing educational agendas within school timeframes? Fusing curricula requires the bonding of standards from two or more syllabuses. Both technology and ICT complement the learning of science. This study analyses selected examples of preservice teachers’ overviews for fusing science, technology and ICT. These program overviews focused on primary students and the achievement of two standards (one from science and one from either technology or ICT). These primary preservice teachers’ fused-curricula overviews included scientific concepts and related technology and/or ICT skills and knowledge. Findings indicated a range of innovative curriculum plans for teaching primary science through technology and ICT, demonstrating that these subjects can form cohesive links towards achieving the respective learning standards. Teachers can work more astutely by fusing curricula; however further professional development may be required to advance thinking about these processes. Bonding subjects through their learning standards can extend beyond previous integration or thematic work where standards may not have been assessed. Education systems need to articulate through syllabus documents how effective fusing of curricula can be achieved. It appears that education is a key avenue for addressing societal needs, problems and issues. Education is promoted as a universal solution, which has resulted in curriculum overload (Dare, Durand, Moeller, & Washington, 1997; Vinson, 2001). Societal and curriculum demands have placed added pressure on teachers with many extenuating education issues increasing teachers’ workloads (Mobilise for Public Education, 2002). For example, as Australia has weather conducive for outdoor activities, social problems and issues arise that are reported through the media calling for action; consequently schools have been involved in swimming programs, road and bicycle safety programs, and a wide range of activities that had been considered a parental responsibility in the past. Teachers are expected to plan, implement and assess these extra-curricula activities within their already overcrowded timetables. At the same stage, key learning areas (KLAs) such as science and technology are mandatory requirements within all Australian education systems. These systems have syllabuses outlining levels of content and the anticipated learning outcomes (also known as standards, essential learnings, and frameworks). Time allocated for teaching science in obviously an issue. In 2001, it was estimated that on average the time spent in teaching science in Australian Primary Schools was almost an hour per week (Goodrum, Hackling, & Rennie, 2001). More recently, a study undertaken in the U.S. reported a similar finding. More than 80% of the teachers in K-5 classrooms spent less than an hour teaching science (Dorph, Goldstein, Lee, et al., 2007). More importantly, 16% did not spend teaching science in their classrooms. Teachers need to learn to work smarter by optimising the use of their in-class time. Integration is proposed as one of the ways to address the issue of curriculum overload (Venville & Dawson, 2005; Vogler, 2003). Even though there may be a lack of definition for integration (Hurley, 2001), curriculum integration aims at covering key concepts in two or more subject areas within the same lesson (Buxton & Whatley, 2002). This implies covering the curriculum in less time than if the subjects were taught separately; therefore teachers should have more time to cover other educational issues. Expectedly, the reality can be decidedly different (e.g., Brophy & Alleman, 1991; Venville & Dawson, 2005). Nevertheless, teachers report that students expand their knowledge and skills as a result of subject integration (James, Lamb, Householder, & Bailey, 2000). There seems to be considerable value for integrating science with other KLAs besides aiming to address teaching workloads. Over two decades ago, Cohen and Staley (1982) claimed that integration can bring a subject into the primary curriculum that may be otherwise left out. Integrating science education aims to develop a more holistic perspective. Indeed, life is not neat components of stand-alone subjects; life integrates subject content in numerous ways, and curriculum integration can assist students to make these real-life connections (Burnett & Wichman, 1997). Science integration can provide the scope for real-life learning and the possibility of targeting students’ learning styles more effectively by providing more than one perspective (Hudson & Hudson, 2001). To illustrate, technology is essential to science education (Blueford & Rosenbloom, 2003; Board of Studies, 1999; Penick, 2002), and constructing technology immediately evokes a social purpose for such construction (Marker, 1992). For example, building a model windmill requires science and technology (Zubrowski, 2002) but has a key focus on sustainability and the social sciences. Science has the potential to be integrated with all KLAs (e.g., Cohen & Staley, 1982; Dobbs, 1995; James et al., 2000). Yet, “integration” appears to be a confusing term. Integration has an educational meaning focused on special education students being assimilated into mainstream classrooms. The word integration was used in the late seventies and generally focused around thematic approaches for teaching. For instance, a science theme about flight only has to have a student drawing a picture of plane to show integration; it did not connect the anticipated outcomes from science and art. The term “fusing curricula” presents a seamless bonding between two subjects; hence standards (or outcomes) need to be linked from both subjects. This also goes beyond just embedding one subject within another. Embedding implies that one subject is dominant, while fusing curricula proposes an equal mix of learning within both subject areas. Primary education in Queensland has eight KLAs, each with its established content and each with a proposed structure for levels of learning. Primary teachers attempt to cover these syllabus requirements across the eight KLAs in less than five hours a day, and between many of the extra-curricula activities occurring throughout a school year (e.g., Easter activities, Education Week, concerts, excursions, performances). In Australia, education systems have developed standards for all KLAs (e.g., Education Queensland, NSW Department of Education and Training, Victorian Education) usually designated by a code. In the late 1990’s (in Queensland), “core learning outcomes” for strands across all KLA’s. For example, LL2.1 for the Queensland Education science syllabus means Life and Living at Level 2 standard number 1. Thus, a teacher’s planning requires the inclusion of standards as indicated by the presiding syllabus. More recently, the core learning outcomes were replaced by “essential learnings”. They specify “what students should be taught and what is important for students to have opportunities to know, understand and be able to do” (Queensland Studies Authority, 2009, para. 1). Fusing science education with other KLAs may facilitate more efficient use of time and resources; however this type of planning needs to combine standards from two syllabuses. To further assist in facilitating sound pedagogical practices, there are models proposed for learning science, technology and other KLAs such as Bloom’s Taxonomy (Bloom, 1956), Productive Pedagogies (Education Queensland, 2004), de Bono’s Six Hats (de Bono, 1985), and Gardner’s Multiple Intelligences (Gardner, 1999) that imply, warrant, or necessitate fused curricula. Bybee’s 5 Es, for example, has five levels of learning (engage, explore, explain, elaborate, and evaluate; Bybee, 1997) can have the potential for fusing science and ICT standards.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

A model for integrating clinical care and basic science research, and pitfalls of performing complex research projects for addressing a clinical challenge

The collaboration of clinicians with basic science researchers is crucial for addressing clinically relevant research questions. In order to initiate such mutually beneficial relationships, we propose a model where early career clinicians spend a designated time embedded in established basic science research groups, in order to pursue a postgraduate qualification. During this time, clinicians become integral members of the research team, fostering long term relationships and opening up opportunities for continuing collaboration. However, for these collaborations to be successful there are pitfalls to be avoided. Limited time and funding can lead to attempts to answer clinical challenges with highly complex research projects characterised by a large number of "clinical" factors being introduced in the hope that the research outcomes will be more clinically relevant. As a result, the complexity of such studies and variability of its outcomes may lead to difficulties in drawing scientifically justified and clinically useful conclusions. Consequently, we stress that it is the basic science researcher and the clinician's obligation to be mindful of the limitations and challenges of such multi-factorial research projects. A systematic step-by-step approach to address clinical research questions with limited, but highly targeted and well defined research projects provides the solid foundation which may lead to the development of a longer term research program for addressing more challenging clinical problems. Ultimately, we believe that it is such models, encouraging the vital collaboration between clinicians and researchers for the work on targeted, well defined research projects, which will result in answers to the important clinical challenges of today.

Becoming “Librarian 2.0” : the skills, knowledge, and attributes required by library and information science professionals in a Web 2.0 world (and beyond)

In 2005, Stephen Abram, vice president of Innovation at SirsiDynix, challenged library and information science (LIS) professionals to start becoming “librarian 2.0.” In the last few years, discussion and debate about the “core competencies” needed by librarian 2.0 have appeared in the “biblioblogosphere” (blogs written by LIS professionals). However, beyond these informal blog discussions few systematic and empirically based studies have taken place. This article will discuss a research project that fills this gap. Funded by the Australian Learning and Teaching Council, the project identifies the key skills, knowledge, and attributes required by “librarian 2.0.” Eighty-one members of the Australian LIS profession participated in a series of focus groups. Eight themes emerged as being critical to “librarian 2.0”: technology, communication, teamwork, user focus, business savvy, evidence based practice, learning and education, and personal traits. This article will provide a detailed discussion on each of these themes. The study’s findings also suggest that “librarian 2.0” is a state of mind, and that the Australian LIS profession is undergoing a significant shift in “attitude.”

Paradigm shifters : tricksters and cultural science

This paper seeks to link anthropological and economic treatments of the process of innovation and change, not only within a given ‘complex system’ (e.g. a cosmology; an industry) but also between systems (e.g. cultural and economic systems; but also divine and human systems). The role of the ‘Go-Between’ is considered, both in the anthropological figure of the Trickster (Hyde 1998) and in the Schumpeterian entrepreneur. Both figures parlay appetite (economic wants) into meaning (cultural signs). Both practice a form of creativity based on deception, ‘creative destruction’; renewal by disruption and needs-must adaptation. The disciplinary purpose of the paper is to try to bridge two otherwise disconnected domains – cultural studies and evolutionary economics – by showing that the traditional methods of the humanities (e.g. anthropological, textual and historical analysis) have explanatory force in the context of economic actions and complex-system evolutionary dynamics. The objective is to understand creative innovation as a general cultural attribute rather than one restricted only to accredited experts such as artists; thus to theorise creativity as a form of emergence for dynamic adaptive systems. In this context, change is led by ‘paradigm shifters’ – tricksters and entrepreneurs who create new meanings out of the clash of difference, including the clash of mutually untranslatable communication systems (language, media, culture).

Near infrared for non-destructive testing of articular cartilage

The concept of non-destructive testing (NDT) of materials and structures is of immense importance in engineering and medicine. Several NDT methods including electromagnetic (EM)-based e.g. X-ray and Infrared; ultrasound; and S-waves have been proposed for medical applications. This paper evaluates the viability of near infrared (NIR) spectroscopy, an EM method for rapid non-destructive evaluation of articular cartilage. Specifically, we tested the hypothesis that there is a correlation between the NIR spectrum and the physical and mechanical characteristics of articular cartilage such as thickness, stress and stiffness. Intact, visually normal cartilage-on-bone plugs from 2-3yr old bovine patellae were exposed to NIR light from a diffuse reflectance fibre-optic probe and tested mechanically to obtain their thickness, stress, and stiffness. Multivariate statistical analysis-based predictive models relating articular cartilage NIR spectra to these characterising parameters were developed. Our results show that there is a varying degree of correlation between the different parameters and the NIR spectra of the samples with R2 varying between 65 and 93%. We therefore conclude that NIR can be used to determine, nondestructively, the physical and functional characteristics of articular cartilage.

Simulated cataract and low contrast stimuli impair cognitive performance in older adults : implications for neuropsychological assessment and everyday function

Objective: To investigate how age-related declines in vision (particularly contrast sensitivity), simulated using cataract-goggles and low-contrast stimuli, influence the accuracy and speed of cognitive test performance in older adults. An additional aim was to investigate whether declines in vision differentially affect secondary more than primary memory. Method: Using a fully within-subjects design, 50 older drivers aged 66-87 years completed two tests of cognitive performance - letter matching (perceptual speed) and symbol recall (short-term memory) - under different viewing conditions that degraded visual input (low-contrast stimuli, cataract-goggles, and low-contrast stimuli combined with cataract-goggles, compared with normal viewing). However, presentation time was also manipulated for letter matching. Visual function, as measured using standard charts, was taken into account in statistical analyses. Results: Accuracy and speed for cognitive tasks were significantly impaired when visual input was degraded. Furthermore, cognitive performance was positively associated with contrast sensitivity. Presentation time did not influence cognitive performance, and visual gradation did not differentially influence primary and secondary memory. Conclusion: Age-related declines in visual function can impact on the accuracy and speed of cognitive performance, and therefore the cognitive abilities of older adults may be underestimated in neuropsychological testing. It is thus critical that visual function be assessed prior to testing, and that stimuli be adapted to older adults' sensory capabilities (e.g., by maximising stimuli contrast).

Down the rabbit hole and through the looking glass: A conception of information seeking and searching through a diary study.

Information behaviour (IB) is an area within Library and Information Science that studies the totality of human behaviour in relation to information, both active and passive, along with the explicit and the tacit mental states related to information. This study reports on a recently completed dissertation research that integrates the different models of information behaviours using a diary study where 34 participants maintained a daily journal for two weeks through a web log or paper diary. This resulted in thick descriptions of IB, which were manually analysed using the Grounded Theory method of inquiry, and then cross-referenced through both text-analysis and statistical analysis programs. Among the many key findings of this study, one is the focus this paper: how participants express their feelings of the information seeking process and their mental and affective states related specifically to the sense-making component which co-occurs with almost every other aspect of information behaviour. The paper title – Down the Rabbit Hole and Through the Looking Glass – refers to an observation that some of the participants made in their journals when they searched for, or avoided information, and wrote that they felt like they have fallen into a rabbit hole where nothing made sense, and reported both positive feelings of surprise and amazement, and negative feelings of confusion, puzzlement, apprehensiveness, frustration, stress, ambiguity, and fatigue. The study situates this sense-making aspects of IB within an overarching model of information behaviour that includes IB concepts like monitoring information, encountering information, information seeking and searching, flow, multitasking, information grounds, information horizons, and more, and proposes an integrated model of information behaviour illuminating how these different concepts are interleaved and inter-connected with each other, along with it's implications for information services.

A statistical framework for natural feature representation

This paper presents a robust stochastic framework for the incorporation of visual observations into conventional estimation, data fusion, navigation and control algorithms. The representation combines Isomap, a non-linear dimensionality reduction algorithm, with expectation maximization, a statistical learning scheme. The joint probability distribution of this representation is computed offline based on existing training data. The training phase of the algorithm results in a nonlinear and non-Gaussian likelihood model of natural features conditioned on the underlying visual states. This generative model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The instantiated likelihoods are expressed as a Gaussian mixture model and are conveniently integrated within existing non-linear filtering algorithms. Example applications based on real visual data from heterogenous, unstructured environments demonstrate the versatility of the generative models.

Incorporating parameter uncertainty into quantitative microbial risk assessment (QMRA)

Modern statistical models and computational methods can now incorporate uncertainty of the parameters used in Quantitative Microbial Risk Assessments (QMRA). Many QMRAs use Monte Carlo methods, but work from fixed estimates for means, variances and other parameters. We illustrate the ease of estimating all parameters contemporaneously with the risk assessment, incorporating all the parameter uncertainty arising from the experiments from which these parameters are estimated. A Bayesian approach is adopted, using Markov Chain Monte Carlo Gibbs sampling (MCMC) via the freely available software, WinBUGS. The method and its ease of implementation are illustrated by a case study that involves incorporating three disparate datasets into an MCMC framework. The probabilities of infection when the uncertainty associated with parameter estimation is incorporated into a QMRA are shown to be considerably more variable over various dose ranges than the analogous probabilities obtained when constants from the literature are simply ‘plugged’ in as is done in most QMRAs. Neglecting these sources of uncertainty may lead to erroneous decisions for public health and risk management.

Cultivating Innovation through Social Relationships: A Qualitative Study of Outstanding Australian Innovators in Science, Technology and the Creative Industries

In this chapter, we describe and explore social relationship patterns associated with outstanding innovation. In doing so, we draw upon the findings of 16 in-depth interviews with award-winning Australian innovators from science & technology and the creative industries. The interviews covered topics relating to various influences on individual innovation capacity and career development. We found that for all of the participants, innovation was a highly social process. Although each had been recognised individually for their innovative success, none worked in isolation. The ability to generate innovative outcomes was grounded in certain types of interaction and collaboration. We outline the distinctive features of the social relationships which seem to be important to innovation, and ask which ‘social network capabilities’ might underlie the ability to create an optimal pattern of interpersonal relationships. We discuss the implications of these findings for universities, which we argue play a key role in the development of nascent innovators.

Improved design method for biosecurity surveillance and early detection of non-indigenous rats

A recent advance in biosecurity surveillance design aims to benefit island conservation through early and improved detection of incursions by non-indigenous species. The novel aspects of the design are that it achieves a specified power of detection in a cost-managed system, while acknowledging heterogeneity of risk in the study area and stratifying the area to target surveillance deployment. The design also utilises a variety of surveillance system components, such as formal scientific surveys, trapping methods, and incidental sightings by non-biologist observers. These advances in design were applied to black rats (Rattus rattus) representing the group of invasive rats including R. norvegicus, and R. exulans, which are potential threats to Barrow Island, Australia, a high value conservation nature reserve where a proposed liquefied natural gas development is a potential source of incursions. Rats are important to consider as they are prevalent invaders worldwide, difficult to detect early when present in low numbers, and able to spread and establish relatively quickly after arrival. The ‘exemplar’ design for the black rat is then applied in a manner that enables the detection of a range of non-indigenous species of rat that could potentially be introduced. Many of the design decisions were based on expert opinion as data gaps exist in empirical data. The surveillance system was able to take into account factors such as collateral effects on native species, the availability of limited resources on an offshore island, financial costs, demands on expertise and other logistical constraints. We demonstrate the flexibility and robustness of the surveillance system and discuss how it could be updated as empirical data are collected to supplement expert opinion and provide a basis for adaptive management. Overall, the surveillance system promotes an efficient use of resources while providing defined power to detect early rat incursions, translating to reduced environmental, resourcing and financial costs.

Combining expert opinions in prior elicitation

A method of eliciting prior distributions for Bayesian models using expert knowledge is proposed. Elicitation is a widely studied problem, from a psychological perspective as well as from a statistical perspective. Here, we are interested in combining opinions from more than one expert using an explicitly model-based approach so that we may account for various sources of variation affecting elicited expert opinions. We use a hierarchical model to achieve this. We apply this approach to two problems. The first problem involves a food risk assessment problem involving modelling dose-response for Listeria monocytogenes contamination of mice. The second concerns the time taken by PhD students to submit their thesis in a particular school.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.