Matching cognitive styles to computer-based instruction : an approach for enhanced learning in electrical engineering

An approach aimed at enhancing learning by matching individual students' preferred cognitive styles to computer-based instructional (CBI) material is presented. This approach was used in teaching some components of a third-year unit in an electrical engineering course at the Queensland University of Technology. Cognitive style characteristics of perceiving and processing information were considered. The bimodal nature of cognitive styles (analytic/imager, analytic/verbalizer, wholist/imager and wholist/verbalizer) was examined in order to assess the full ramification of cognitive styles on learning. In a quasi-experimental format, students' cognitive styles were analysed by cognitive style analysis (CSA) software. On the basis of the CSA results the system defaulted students to either matched or mismatched CBI material. The consistently better performance by the matched group suggests potential for further investigations where the limitations cited in this paper are eliminated. Analysing the differences between cognitive styles on individual test tasks also suggests that certain test tasks may better suit certain cognitive styles.

Personalizing the design of computer-based instruction to enhance learning

This paper reports two studies designed to investigate the effect on learning outcomes of matching individuals' preferred cognitive styles to computer-based instructional (CBI) material. Study 1 considered the styles individually as Verbalizer, Imager, Wholist and Analytic. Study 2 considered the bi-dimensional nature of cognitive styles in order to assess the full ramification of cognitive styles on learning: Analytic/Imager, Analytic/ Verbalizer, Wholist/Imager and the Wholist/Verbalizer. The mix of images and text, the nature of the text material, use of advance organizers and proximity of information to facilitate meaningful connections between various pieces of information were some of the considerations in the design of the CBI material. In a quasi-experimental format, students' cognitive styles were analysed by Cognitive Style Analysis (CSA) software. On the basis of the CSA result, the system defaulted students to either matched or mismatched CBI material by alternating between the two formats. The instructional material had a learning and a test phase. Learning outcome was tested on recall, labelling, explanation and problem-solving tasks. Comparison of the matched and mismatched instruction did not indicate significant difference between the groups, but the consistently better performance by the matched group suggests potential for further investigations where the limitations cited in this paper are eliminated. The result did indicate a significant difference between the four cognitive styles with the Wholist/Verbalizer group performing better then all other cognitive styles. Analysing the difference between cognitive styles on individual test tasks indicated significant difference on recall, labelling and explanation, suggesting that certain test tasks may suit certain cognitive styles.

Implementing low intensity CBT in case management of clients with severe mental illness

In a previous chapter (Dean and Kavanagh, Chapter 37), the authors made a case for applying low intensity (LI) cognitive behaviour therapy (CBT) to people with serious mental illness (SMI). As in other populations, LI CBT interventions typically deal with circumscribed problems or behaviours. LI CBT retains an emphasis on self-management, has restricted content and segment length, and does not necessarily require extensive CBT training. In applying these interventions to SMI, adjustments may be needed to address cognitive and symptomatic difficulties often faced by these groups. What may take a single session in a less affected population may require several sessions or a thematic application of the strategy within case management. In some cases, the LI CBT may begin to appear more like a high-intensity (HI) intervention, albeit simple and with many LI CBT characteristics still retained. So, if goal setting were introduced in one or two sessions, it could clearly be seen as an LI intervention. When applied to several different situations and across many sessions, it may be indistinguishable from a simple HI treatment, even if it retains the same format and is effectively applied by a practitioner with limited CBT training. ----- ----- In some ways, LI CBT should be well suited to case management of patients with SMI. treating staff typically have heavy workloads, and find it difficult to apply time-consuming treatments (Singh et al. 2003). LI CBT may allow provision of support to greater numbers of service users, and allow staff to spend more time on those who need intensive and sustained support. However, the introduction of any change in practice has to address significant challenges, and LI CBT is no exception. ----- ----- Many of the issues that we face in applying LI CBT to routine case management in a mnetal health service and their potential solutions are essentially the same as in a range of other problem domains (Turner and Sanders 2006)- and, indeed, are similar to those in any adoption of innovation (Rogers 2003). Over the last 20 years, several commentators have described barriers to implementing evidence-based innovations in mental health services (Corrigan et al. 1992; Deane et al. 2006; Kavanagh et al. 1993). The aim of the current chapter is to present a cognitive behavioural conceptualisation of problems and potential solutions for dissemination of LI CBT.

Engaging students in clinical bacteriology: A fresh look

Frequently there is a disconnectedness, either perceived or actual, between theoretical principles and laboratory practice in science education and this holds true for clinical microbiology where traditionally knowledge is delivered in ‘chunks’ in a lecture format with the misguided belief that students have to know ‘everything about everything’. This preoccupation with content delivery often leaves no time for active class discussion or reflection. Moreover, laboratory classes are treated as add-ons to the process, rather than an integrated part of the whole learning experience. In redesigning our units (subjects) we have bridged the gap between the theory and practice of clinical bacteriology. In doing so, we have seen a transformation in the learning experiences of our students and in the way we teach.

Model and prototype for querying multiple linked scientific datasets

Scientists need to transfer semantically similar queries across multiple heterogeneous linked datasets. These queries may require data from different locations and the results are not simple to combine due to differences between datasets. A query model was developed to make it simple to distribute queries across different datasets using RDF as the result format. The query model, based on the concept of publicly recognised namespaces for parts of each scientific dataset, was implemented with a configuration that includes a large number of current biological and chemical datasets. The configuration is flexible, providing the ability to transparently use both private and public datasets in any query. A prototype implementation of the model was used to resolve queries for the Bio2RDF website, including both Bio2RDF datasets and other datasets that do not follow the Bio2RDF URI conventions.

"As ideias são mais importantes que os produtos", diz Paul Makeham" [Ideas are more important than products, says Paul Makeham]

This interview with Paul Makeham was conducted in 2010 by Felipe Carneiro from Brazilian business magazine Exame. Structured around Exame's "seven questions" format ("Sete Perguntas"), the interview ranges across topics relating to the creative economy, including the increasingly important role of creativity in business, and the role of education in promoting creativity.

Ways of telling : tacit knowledge transfer for fashion design research

The knowledge and skills of fashion and textiles design have traditionally been transferred through the indenture of an apprentice to a master. This relationship relied heavily on the transfer of explicit methods of design and making but also on the transfer of tacit knowledge, explained by Michael Polanyi as knowledge that cannot be explicitly known. By watching the master and emulating his efforts in the presence of his example, the apprentice unconsciously picks up the rules of the art, including those which are not explicitly known to the master himself (Polanyi, 1962 p.53). However, it has been almost half a century since Michael Polanyi defined the tacit dimension as a state in which “we can know more than we can tell” (Polanyi, 1967 p.4) at a time when the accepted means of ‘telling’ was through academic writing and publishing in hardcopy format. The idea that tacit knowledge transfer involves a one to one relationship between apprentice and master would appear to have dire consequences for a discipline, such as fashion design, where there is no such tradition of academic writing. This paper counters this point of view by providing examples of strategies currently being employed in online environments (principally through ‘craft’) and explains how these methods might prove useful to support tacit knowledge transfer in respect to academic research within the field of fashion design, and in the wider academic community involved in creative practice research. A summary of the implications of these new ideas for contemporary fashion research will conclude the paper.

Ways of telling : research methodology for fashion textiles design

Research methodology in the discipline of Art & Design has been a topic for much debate in the academic community. The result of such avid and ongoing discussion appears to be a disciplinary obsession with research methodologies and a culture of adopting and adapting existing methodologies from more established disciplines. This has eventuated as a means of coping with academic criticism and as an attempt to elevate Art & Design to a ‘real academic status’. Whilst this adoption has had some effect in tempering the opinion of Art & Design research from more ‘serious’ academics the practice may be concealing a deeper problem for this discipline. Namely, that knowledge transfer within creative practice, particularly in fashion textiles design practice, is largely tacit in nature and not best suited to dissemination through traditional means of academic writing and publication. ----- ----- There is an opportunity to shift the academic debate away from appropriate (or inappropriate) use of methodologies and theories to demonstrate the existence (or absence) of rigor in creative practice research. In particular, the changing paradigms for the definitions of research to support new models for research quality assessment (such as the RAE in the United Kingdom and ERA in Australia) require a re-examination of the traditions of academic writing and publication in relation to this form of research. It is now appropriate to test the limits of tacit knowledge. It has been almost half a century since Michael Polanyi wrote “we know more than we can tell” (Polanyi, 1967 p.4) at a time when the only means of ‘telling’ was through academic writing and publishing in hardcopy format. ----- ----- This paper examines the academic debate surrounding research methodologies for fashion textiles design through auto-ethnographic case study and object analysis. The author argues that, while this debate is interesting, the focus should be to ask: are there more effective ways for creative practitioner researchers to disseminate their research? The aim of this research is to examine the possibilities of developing different, more effective methods of ‘telling’ to support the transfer of tacit knowledge inherent in the discipline of Fashion Textiles Design.

Motivating domestic energy conservation through comparative, community-based feedback in mobile and social media

The progress of technology has led to the increased adoption of energy monitors among household energy consumers. While the monitors available on the market deliver real-time energy usage feedback to the consumer, the format of this data is usually unengaging and mundane. Moreover, it fails to address consumers with different motivations and needs to save and compare energy. This paper presents a study that seeks to provide initial indications for motivation-specific design of energy-related feedback. We focus on comparative feedback supported by a community of energy consumers. In particular, we examine eco-visualisations, temporal self-comparison, norm comparison, one-on-one comparison and ranking, whereby the last three allow us to explore the potential of socialising energy-related feedback. These feedback types were integrated in EnergyWiz – a mobile application that enables users to compare with their past performance, neighbours, contacts from social networking sites and other EnergyWiz users. The application was evaluated in personal, semi-structured interviews, which provided first insights on how to design motivation-related comparative feedback.

Developing research data management services at QUT

QUT Library and the High Performance Computing and Research Support (HPC) Team have been collaborating on developing and delivering a range of research support services, including those designed to assist researchers to manage their data. QUT’s Management of Research Data policy has been available since 2010 and is complemented by the Data Management Guidelines and Checklist. QUT has partnered with the Australian Research Data Service (ANDS) on a number of projects including Seeding the Commons, Metadata Hub (with Griffith University) and the Data Capture program. The HPC Team has also been developing the QUT Research Data Repository based on the Architecta Mediaflux system and have run several pilots with faculties. Library and HPC staff have been trained in the principles of research data management and are providing a range of research data management seminars and workshops for researchers and HDR students.

Using data mining to predict road crash count with a focus on skid resistance values

Road crashes cost world and Australian society a significant proportion of GDP, affecting productivity and causing significant suffering for communities and individuals. This paper presents a case study that generates data mining models that contribute to understanding of road crashes by allowing examination of the role of skid resistance (F60) and other road attributes in road crashes. Predictive data mining algorithms, primarily regression trees, were used to produce road segment crash count models from the road and traffic attributes of crash scenarios. The rules derived from the regression trees provide evidence of the significance of road attributes in contributing to crash, with a focus on the evaluation of skid resistance.

Cognitive load and assembly tasks : effect of instructional formats on learning assembly procedures

The study investigated the effect on learning of four different instructional formats used to teach assembly procedures. Cognitive load and spatial information processing theories were used to generate the instructional material. The first group received a physical model to study, the second an isometric drawing, the third an isometric drawing plus a model and the fourth an orthographic drawing. Forty secondary school students were presented with the four different instructional formats and subsequently tested on an assembly task. The findings indicated that there may be evidence to argue that the model format which only required encoding of an already constructed three dimensional representation, caused less extraneous cognitive load compared to the isometric and the orthographic formats. No significant difference was found between the model and the isometric-plus-model formats on all measures because 80% of the students in the isometric-plus-model format chose to use the model format only. The model format also did not differ significantly from other groups in total time taken to complete the assembly, in number of correctly assembled pieces and in time spent on studying the tasks. However, the model group had significantly more correctly completed models and required fewer extra looks than the other groups.

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

Remote monitoring of outdoor performance of low scale dye sensitized solar cells for nanosensors nodes

This is the first outdoor test of small-scale dye sensitized solar cells (DSC) powering a standalone nanosensor node. A solar cell test station (SCTS) has been developed using standard DSC to power a gas nanosensor, a radio transmitter, and the control electronics (CE) for battery charging. The station is remotely monitored through wired (Ethernet cable) or wireless connection (radio transmitter) in order to evaluate in real time the performance of the solar cells powering a nanosensor and a transmitter under different weather conditions. We analyze trends of energy conversion efficiency after 60 days of operation. The 408 cm2 active surface module produces enough energy to power a gas nanosensor and a radio transmitter during the day and part of the night. Also, by using a variable programmable load we keep the system working on the maximum power point (MPP) quantifying the total energy generated and stored in a battery. Although this technology is at an early stage of development, these experiments provide useful data for future outdoor applications such as nanosensor network nodes.