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Institution

Edith Cowan University

EducationPerth, Western Australia, Australia
About: Edith Cowan University is a education organization based out in Perth, Western Australia, Australia. It is known for research contribution in the topics: Population & Tourism. The organization has 4040 authors who have published 13529 publications receiving 339582 citations. The organization is also known as: Edith Cowan & ECU.


Papers
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Journal ArticleDOI
TL;DR: This research provides evidence that the computer is a social facilitator in the sense that it provides opportunities for collaboration, group work and interaction which fosters cognitive change.
Abstract: In studies on the implementation and educational uses of computers there are reports of changes in students’ behaviour as a result of working with computers (Rowe, 1993; Crook, 1994). Social, collaborative and dialogic exchanges have been observed as students engage in tasks around computers. This research provides evidence that the computer is a social facilitator in the sense that it provides opportunities for collaboration, group work and interaction which fosters cognitive change (Wild, 1995). This article recognises the social role of the computer, and supports the view that computers can be used to facilitate learning through language. There is growing awareness that if we are to realise the full potential of computers in education, consideration must be given to their role as catalysts in the learning process, rather than technological tools (Hawkridge, 1990). Computer assisted learning has progressed through many phases, and through investigation of underlying theoretical frameworks it is possible to recognise the change of focus from individual accounts of learning to social perspectives. Theoretical frameworks which emphasise the social dimensions of learning (Vygotsky, 1978) legitimise the link between computers, language use and learning and indicate that computers must be integrated into the social life of classrooms if their pedagogical benefits are to be realised.

105 citations

Journal ArticleDOI
TL;DR: Eleven non-linear regression models were examined to determine which of them best fitted curvilinear species accumulation curves based on pit-trapping data for reptiles in a range of heterogeneous and homogenous sites in mesic, semi-arid and arid regions of Western Australia to predict species richness and the relationship with diversity and rarity.
Abstract: We examined 11 non-linear regression models to determine which of them best fitted curvilinear species accumulation curves based on pit-trapping data for reptiles in a range of heterogeneous and homogenous sites in mesic, semi-arid and arid regions of Western Australia. A well-defined plateau in a species accumulation curve is required for any of the models accurately to estimate species richness. Two different measures of effort (pit-trapping days and number of individuals caught) were used to determine if the measure of effort influenced the choice of the best model(s). We used species accumulation curves to predict species richness, determined the trapping effort required to catch a nominated percentage (e.g. 95%) of the predicted number of species in an area, and examined the relationship between species accumulation curves with diversity and rarity. Species richness, diversity and the proportion of rare species in a community influenced the shape of species accumulation curves. The Beta-P model provided the best overall fit (highest r 2 ) for heterogeneous and homogeneous sites. For heterogeneous sites, Hill, Rational, Clench, Exponential and Weibull models were the next best. For homogeneous habitats, Hill, Weibull and Chapman-Richards were the next best models. There was very little difference between Beta-P and Hill models in fitting the data to accumulation curves, although the Hill model generally over-estimated species richness. Most models worked equally well for both measures of trapping effort. Because the number of individuals caught was influenced by both pit-trapping effort and the abundance of individuals, both measures of effort must be considered if species accumulation curves are to be used as a planning tool. Trapping effort to catch a nominated percentage of the total predicted species in homogeneous and heterogeneous habitats varied among sites, but even for only 75% of the predicted number of species it was generally much higher than the typical effort currently being used for terrestrial vertebrate fauna surveys in Australia. It was not possible to provide a general indication of the effort required to predict species richness for a site, or to capture a nominated proportion of species at a site, because species accumulation curves are heavily influenced by the characteristics of particular sites.

105 citations

Book ChapterDOI
18 Sep 2017
TL;DR: It is concluded that there is a great scope for automation in the analysis of digital seabed imagery using deep neural networks, especially for the detection and monitoring of seagrass.
Abstract: Deep learning, also known as deep machine learning or deep structured learning based techniques, have recently achieved tremendous success in digital image processing for object detection and classification. As a result, they are rapidly gaining popularity and attention from the computer vision research community. There has been a massive increase in the collection of digital imagery for the monitoring of underwater ecosystems, including seagrass meadows. This growth in image data has driven the need for automatic detection and classification using deep neural network based classifiers. This paper systematically describes the use of deep learning for underwater imagery analysis within the recent past. The analysis approaches are categorized according to the object of detection, and the features and deep learning architectures used are highlighted. It is concluded that there is a great scope for automation in the analysis of digital seabed imagery using deep neural networks, especially for the detection and monitoring of seagrass.

105 citations

Journal ArticleDOI
TL;DR: The significant 4.7% increase for the Antag group indicates that a strategy of alternating agonist and antagonist muscle exercises may acutely increase power output during complex power training.
Abstract: The efficient coordination of agonist and antagonist muscles is one of the important early adaptations in resistance training responsible for large increases in strength. Weak antagonist muscles may limit speed of movement; consequently, strengthening them leads to an increase in agonist muscle movement speed. However, the effect of combining agonist and antagonist muscle exercises into a power training session has been largely unexplored. The purpose of this study was to determine if a training complex consisting of contrasting agonist and antagonist muscle exercises would result in an acute increase in power output in the agonist power exercise. Twenty-four college-aged rugby league players who were experienced in combined strength and power training served as subjects for this study. They were equally assigned to an experimental (Antag) or control (Con) group and were no different in age, height, body mass, strength, or maximal power. Power output was assessed during bench press throws with a 40-kg resistance (BT P40) with the Plyometric Power System training device. After warming up, the Con group performed the BT P40 tests 3 minutes apart to determine if any acute augmentation to power output could occur without intervention. The Antag group also performed the BT P40 tests; however, an intervention strategy of a set of bench pulls, which is an antagonistic action to the bench throw, was performed between tests to determine if this would acutely affect power output during the second BT P40 test. Although the power output for the Con group remained unaltered between test occasions, the significant 4.7% increase for the Antag group indicates that a strategy of alternating agonist and antagonist muscle exercises may acutely increase power output during complex power training. This result may affect power training and specific warm-up strategies used in ballistic sports activities, with increased emphasis placed upon the antagonist muscle groups.

105 citations

Journal ArticleDOI
TL;DR: Further research is required to develop interventions that can assist nurses in providing care that meets the needs of adolescent children and other family members of women with breast cancer.
Abstract: Purpose/objectives To elicit detailed descriptions of adolescents' information and support needs in response to their mothers' breast cancer. Design Exploratory, qualitative. Setting Four different outpatient and inpatient oncology settings in western Canada. Sample 31 adolescent children of women in five illness phases. Methods 27 semistructured interviews and two focus groups were conducted. Interviews were audiotaped, transcribed, and analyzed using constant comparison techniques. The Communication Subscale of the McMaster Family Assessment Device also was administered to assess family communication patterns. Findings Information needs were sources of information, information content, degree of helpfulness, and information timing. Support needs were type, degree of helpfulness, form, and source. Conclusion Most of the adolescents reported that their needs were poorly met. Implications for nursing Women with breast cancer have a need for family-focused care. Further research is required to develop interventions that can assist nurses in providing care that meets the needs of adolescent children and other family members of women with breast cancer.

105 citations


Authors

Showing all 4128 results

NameH-indexPapersCitations
Paul Jackson141137293464
William J. Kraemer12375554774
D. Allan Butterfield11550443528
Kerry S. Courneya11260849504
Robert U. Newton10975342527
Roger A. Barker10162039728
Ralph N. Martins9563035394
Wei Wang95354459660
David W. Dunstan9140337901
Peter E.D. Love9054624815
Andrew Jones8369528290
Hongqi Sun8126520354
Leon Flicker7946522669
Mark A. Jenkins7947221100
Josep M. Gasol7731322638
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202350
2022156
20211,433
20201,372
20191,213
20181,023