Globalization of science education : comment and a commentary

The globalized nature of modern society has generated a number of pressures that impact internationally on countries’ policies and practices of science education. Among these pressures are key issues of health and environment confronting global science, global economic control through multinational capitalism, comparative and competitive international testing of student science achievement, and the desire for more humane and secure international society. These are not all one-way pressures and there is evidence of both more conformity in the intentions and practices of science education and of a greater appreciation of how cultural differences, and the needs of students as future citizens can be met. Hence while a case for economic and competitive subservience of science education can be made, the evidence for such narrowing is countered by new initiatives that seek to broaden its vision and practices. The research community of science education has certainly widened internationally and this generates many healthy exchanges, although cultural styles of education other than Western ones are still insufficiently recognized. The dominance of English language within these research exchanges is, however, causing as many problems as it solves. Science education, like education as a whole, is a strongly cultural phenomenon, and this provides a healthy and robust buffer to the more negative effects of globalization

Interface design in interactive science courseware for the Malaysian Smart School Project

With the goal of improving the academic performance of primary and secondary students in Malaysia by 2020, the Malaysian Ministry of Education has made a significant investment in developing a Smart School Project. The aim of this project is to introduce interactive courseware into primary and secondary schools across Malaysia. As has been the case around the world, interactive courseware is regarded as a tool to motivate students to learn meaningfully and enhance learning experiences. Through an initial pilot phase, the Malaysian government has commissioned the development of interactive courseware by a number of developers and has rolled this courseware out to selected schools over the past 12 years. However, Ministry reports and several independent researchers have concluded that its uptake has been limited, and that much of the courseware has not been used effectively in schools. This has been attributed to weaknesses in the interface design of the courseware, which, it has been argued, fails to accommodate the needs of students and teachers. Taking the Smart School Project's science courseware as a sample, this research project has investigated the extent, nature, and reasons for the problems that have arisen. In particular, it has focused on examining the quality and effectivity of the interface design in facilitating interaction and supporting learning experiences. The analysis has been conducted empirically, by first comparing the interface design principles, characteristics and components of the existing courseware against best practice, as described in the international literature, as well as against the government guidelines provided to the developers. An ethnographic study was then undertaken to observe how the courseware is used and received in the classroom, and to investigate the stakeholders' (school principal, teachers and students') perceptions of its usability and effectivity. Finally, to understand how issues may have arisen, a review of the development process has been undertaken and it has been compared to development methods recommended in the literature, as well as the guidelines provided to the developers. The outcomes of the project include an empirical evaluation of the quality of the interface design of the Smart School Project's science courseware; the identification of other issues that have affected its uptake; an evaluation of the development process and, out of this, an extended set of principles to guide the design and development of future Smart School Project courseware to ensure that it accommodates the various stakeholders' needs.

Building and construction industries supply chain project (domestic) : report for Commonwealth Department of Industry, Science and Resources

The Commonwealth Department of Industry, Science and Resources is identifying best practice case study examples of supply chain management within the building and construction industry to illustrate the concepts, innovations and initiatives that are at work. The projects provide individual enterprises with examples of how to improve their performance, and the competitiveness of the industry as a whole.

Validating the design science research roadmap : through the lens of "the idealised model for theory development"

Design Science Research (DSR) has emerged as an important approach in Information Systems (IS) research. However, DSR is still in its genesis and has yet to achieve consensus on even the fundamentals, such as what methodology / approach to use for DSR. While there has been much effort to establish DSR methodologies, a complete, holistic and validated approach for the conduct of DSR to guide IS researcher (especially novice researchers) is yet to be established. Alturki et al. (2011) present a DSR ‘Roadmap’, making the claim that it is a complete and comprehensive guide for conducting DSR. This paper aims to further assess this Roadmap, by positioning it against the ‘Idealized Model for Theory Development’ (IM4TD) (Fischer & Gregor 2011). The IM4TD highlights the role of discovery and justification and forms of reasoning to progress in theory development. Fischer and Gregor (2011) have applied IM4TD’s hypothetico-deductive method to analyze DSR methodologies, which is adopted in this study to deductively validate the Alturki et al. (2011) Roadmap. The results suggest that the Roadmap adheres to the IM4TD, is reasonably complete, overcomes most shortcomings identified in other DSR methodologies and also highlights valuable refinements that should be considered within the IM4TD.

Eliciting Expert Knowledge in Conservation Science

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.

Proteomics science & society : the role of knowledge translation in moving towards clinical applications

Background: Outside the mass-spectrometer, proteomics research does not take place in a vacuum. It is affected by policies on funding and research infrastructure. Proteomics research both impacts and is impacted by potential clinical applications. It provides new techniques & clinically relevant findings, but the possibilities for such innovations (and thus the perception of the potential for the field by funders) are also impacted by regulatory practices and the readiness of the health sector to incorporate proteomics-related tools & findings. Key to this process is how knowledge is translated. Methods: We present preliminary results from a multi-year social science project, funded by the Canadian Institutes of Health Research, on the processes and motivations for knowledge translation in the health sciences. The proteomics case within this wider study uses qualitative methods to examine the interplay between proteomics science and regulatory and policy makers regarding clinical applications of proteomics. Results: Adopting an interactive format to encourage conference attendees’ feedback, our poster focuses on deficits in effective knowledge translation strategies from the laboratory to policy, clinical, & regulatory arenas. An analysis of the interviews conducted to date suggests five significant choke points: the changing priorities of funding agencies; the complexity of proteomics research; the organisation of proteomics research; the relationship of proteomics to genomics and other omics sciences; and conflict over the appropriate role of standardisation. Conclusion: We suggest that engagement with aspects of knowledge translation, such as those mentioned above, is crucially important for the eventual clinical application ofproteomics science on any meaningful scale.

Practical considerations for integrating alternate reality gaming into science education

In this article, I present my experience with integrating an alternate reality gaming (ARG) framework into a pre-service science teacher education course. My goal is to provide an account of my experiences that can inform other science education practitioners at the tertiary and secondary levels that wish to adopt a similar approach in their classes. A game was designed to engage pre-service teachers with issues surrounding the declining enrolments in science, technology, engineering and mathematics disciplines (i.e., the STEM crisis; Tytler, 2007) and ways of re-engaging learners with STEM subjects. The use of ARG in science education is highly innovative. Literature on the use of ARG for educational purposes is scarce so in the article I have drawn on a range of available literature on gaming and ARG to define what it is and to suggest how it can be included in school science classrooms.

Traffic-related fine and ultrafine particle exposures of professional drivers and illness : An opportunity to better link exposure science and epidemiology to address an occupational hazard?

Exposures to traffic-related air pollution (TRAP) can be particularly high in transport microenvironments (i.e. in and around vehicles) despite the short durations typically spent there. There is a mounting body of evidence that suggests that this is especially true for fine (b2.5 μm) and ultrafine (b100 nm, UF) particles. Professional drivers, who spend extended periods of time in transport microenvironments due to their job, may incur exposures markedly higher than already elevated non-occupational exposures. Numerous epidemiological studies have shown a raised incidence of adverse health outcomes among professional drivers, and exposure to TRAP has been suggested as one of the possible causal factors. Despite this, data describing the range and determinants of occupational exposures to fine and UF particles are largely conspicuous in their absence. Such information could strengthen attempts to define the aetiology of professional drivers' illnesses as it relates to traffic combustion-derived particles. In this article, we suggest that the drivers' occupational fine and UF particle exposures are an exemplar case where opportunities exist to better link exposure science and epidemiology in addressing questions of causality. The nature of the hazard is first introduced, followed by an overview of the health effects attributable to exposures typical of transport microenvironments. Basic determinants of exposure and reduction strategies are also described, and finally the state of knowledge is briefly summarised along with an outline of the main unanswered questions in the topic area.

Reputation modelling in citizen science for environmental acoustic data analysis

Citizen Science projects are initiatives in which members of the general public participate in scientific research projects and perform or manage research-related tasks such as data collection and/or data annotation. Citizen Science is technologically possible and scientifically significant. However, as the gathered information is from the crowd, the data quality is always hard to manage. There are many ways to manage data quality, and reputation management is one of the common approaches. In recent year, many research teams have deployed many audio or image sensors in natural environment in order to monitor the status of animals or plants. The collected data will be analysed by ecologists. However, as the amount of collected data is exceedingly huge and the number of ecologists is very limited, it is impossible for scientists to manually analyse all these data. The functions of existing automated tools to process the data are still very limited and the results are still not very accurate. Therefore, researchers have turned to recruiting general citizens who are interested in helping scientific research to do the pre-processing tasks such as species tagging. Although research teams can save time and money by recruiting general citizens to volunteer their time and skills to help data analysis, the reliability of contributed data varies a lot. Therefore, this research aims to investigate techniques to enhance the reliability of data contributed by general citizens in scientific research projects especially for acoustic sensing projects. In particular, we aim to investigate how to use reputation management to enhance data reliability. Reputation systems have been used to solve the uncertainty and improve data quality in many marketing and E-Commerce domains. The commercial organizations which have chosen to embrace the reputation management and implement the technology have gained many benefits. Data quality issues are significant to the domain of Citizen Science due to the quantity and diversity of people and devices involved. However, research on reputation management in this area is relatively new. We therefore start our investigation by examining existing reputation systems in different domains. Then we design novel reputation management approaches for Citizen Science projects to categorise participants and data. We have investigated some critical elements which may influence data reliability in Citizen Science projects. These elements include personal information such as location and education and performance information such as the ability to recognise certain bird calls. The designed reputation framework is evaluated by a series of experiments involving many participants for collecting and interpreting data, in particular, environmental acoustic data. Our research in exploring the advantages of reputation management in Citizen Science (or crowdsourcing in general) will help increase awareness among organizations that are unacquainted with its potential benefits.

Identities and transformational experiences for quantitative problem solving : gender comparisons of first-year university science students

Women are underrepresented in science, technology, engineering and mathematics (STEM) areas in university settings; however this may be the result of attitude rather than aptitude. There is widespread agreement that quantitative problem-solving is essential for graduate competence and preparedness in science and other STEM subjects. The research question addresses the identities and transformative experiences (experiential, perception, & motivation) of both male and female university science students in quantitative problem solving. This study used surveys to investigate first-year university students’ (231 females and 198 males) perceptions of their quantitative problem solving. Stata (statistical analysis package version 11) analysed gender differences in quantitative problem solving using descriptive and inferential statistics. Males perceived themselves with a higher mathematics identity than females. Results showed that there was statistical significance (p<0.05) between the genders on 21 of the 30 survey items associated with transformative experiences. Males appeared to have a willingness to be involved in quantitative problem solving outside their science coursework requirements. Positive attitudes towards STEM-type subjects may need to be nurtured in females before arriving in the university setting (e.g., high school or earlier). Females also need equitable STEM education opportunities such as conversations or activities outside school with family and friends to develop more positive attitudes in these fields.