Does use of touch screen computer technology improve classroom engagement in children?

Many studies have shown that the use of technology in the classroom may influence pupil engagement. Despite the recent widespread use of tablet technology, however, very little research has been carried out into their use in a primary school setting. We investigated the use of tablet computers, specifically Apple’s ‘iPad’, in an upper primary school setting with regard to children’s engagement. Cognitive, emotional and general engagement was higher in lessons based on iPads than those which were not. There was no difference in behavioral engagement. Of particular significance was the increase in engagement seen in boys, which resulted in their engagement levels increasing to levels comparable to those seen in girls. These findings suggest that tablet technology has potential as a tool in the classroom setting

The effect of lifeguard experience upon the detection of drowning victims in a realistic dynamic visual search task

Lifeguard surveillance is a complex task that is crucial for swimmer safety, though few studies of applied visual search have investigated this domain. This current study compared lifeguard and non-lifeguard search skills using dynamic, naturalistic stimuli (video clips of confederate swimmers) that varied in set size and type of drowning. Lifeguards were more accurate and responded faster to drowning targets. Differences between drowning targets were also found: passive drownings were responded to less often, but more quickly than active drownings, highlighting that passive drownings may be less salient but are highly informative once detected. Set size effects revealed a dip in reaction speeds at an intermediate set-size level, suggesting a possible change in visual search strategies as the array increases in size. Nonetheless, the ability of the test to discriminate between lifeguards and non-lifeguards offers future possibilities for training and assessing lifeguard surveillance skills

An exploration into the contributing cognitive skills of lifeguard visual search

Lifeguard drowning detection in swimming pools and beach settings is influenced by experience. The current experiment explores the cognitive skills that might underlie this experience effect. Lifeguard and non-lifeguard performance in a domain-free multiple object avoidance (MOA) task and a partially domain-free functional field of view (FFOV) task was compared to performance on an occlusion-based drowning detection task. Lifeguards performed better than non-lifeguards on the MOA task and the FFOV central task (identifying whether an isolated swimmer was drowning). However, only performance in the central FFOV task was associated with performance in the occlusion-based drowning detection task, and this was the only part of the two tasks that was not domain-free. These results suggest lifeguard drowning detection is mainly driven through the learned ability to process behaviours of drowning swimmers quicker than non-lifeguards. Therefore, it may be possible to train novices’ ability to detect drowning swimmers through an exposure task

Search for a distressed swimmer in a dynamic, real-world environment

Visual search is increasingly being explored in dynamic, real-world environments. This includes swimming pools, where lifeguards have shown superior drowning detection in simulated environments. Here we explored if lifeguard superiority is observed in real-life scenes of a busy swimming pool. Experiment 1 required participants to identify real-life distressed swimmers in clips of busy pool activity via a touchscreen interface. Experiment 2 sought to replicate the first study, with the inclusion of eye-movement measures. Experiment 3 varied the methodology, using an occlusion method where clips were frozen and blurred shortly after target onset. The results demonstrated an experience effect, with lifeguards detecting distressed swimmers more often and faster than non-lifeguards. No clear differences were found in the eye-movements between groups; thus, we cannot conclude that the lifeguards’ faster responses are due to better scanning strategies. The different methodological approaches revealed the occlusion method to have the larger effect size, supporting the growing evidence that occlusion may be a better test for dynamic target detection than traditional response-time tests. This research demonstrates that the clear lifeguard experience effect generalises to real-life pool environments with a large number of swimmers and real incidents. It could be used to inform lifeguard training tools and assessments

Spatiotemporal variation in harbor porpoise distribution and foraging across a landscape of fear

Understanding spatiotemporally varying animal distributions can inform ecological understanding of species' behavior (e.g., foraging and predator/prey interactions) and support development of management and conservation measures. Data from an array of echolocation‐click detectors (C‐PODs) were analyzed using Bayesian spatiotemporal modeling to investigate spatial and temporal variation in occurrence and foraging activity of harbor porpoises (Phocoena phocoena) and how this variation was influenced by daylight and presence of bottlenose dolphins (Tursiops truncatus). The probability of occurrence of porpoises was highest on an offshore sandbank, where the proportion of detections with foraging clicks was relatively low. The porpoises' overall distribution shifted throughout the summer and autumn, likely influenced by seasonal prey availability. Probability of porpoise occurrence was lowest in areas close to the coast, where dolphin detections were highest and declined prior to dolphin detection, leading potentially to avoidance of spatiotemporal overlap between porpoises and dolphins. Increased understanding of porpoises' seasonal distribution, key foraging areas, and their relationship with competitors can shed light on management options and potential interactions with offshore industries

Mobilising Knowledge through Global Partnerships to Support Research-informed Teaching: Five Models for Translational Research

Education Futures Collaboration Charity The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Improving the quality of teaching is of global concern: UNESCO’s Sustainable Development Goal (SDG) 4c in the Education 2030: Framework for Action calls for high quality teaching for all. The OECD challenges the education system to improve Knowledge Management. JET’s (2015) special issue: Translational Research (TR) and Knowledge Mobilisation in Teacher Education introduced the concept of ‘translational’ or ‘theory to practice’ research - well-established in medicine but not in education. Five TR models were subsequently developed by the MESH charity’s international network with organisations in South Africa, Bangladesh, Australia, Pakistan, UK. These distinct models engage 1) university staff and teachers 2) subject associations, 3) research units, 4) an international NGO working in crisis settings, 5) PhD tutors and students. Each model shares common features forming the MESH Translational Research methodology introduced in this article. A TR repository is part of the MESH knowledge mobilisation strategy giving teachers access to research summaries which, overtime, accumulate knowledge. TR publications called MESHGuides (www.meshguides.org) complement existing forms of publication. This article proposes the MESH TR methodology as one affordable and scalable solution to OECD and UNESCO’s challenges of keeping teachers up-to-date and making new knowledge accessible to teachers regardless of location

Big Data Analytics for Earth Sciences: the EarthServer approach

Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced e-infrastructures. Earth and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and simulations. However, Earth Science data and applications present specificities in terms of relevance of the geospatial information, wide heterogeneity of data models and formats, and complexity of processing. Therefore, Big Earth Data Analytics requires specifically tailored techniques and tools. The EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets, built around a high performance array database technology, and the adoption and enhancement of standards for service interaction (OGC WCS and WCPS). The EarthServer solution, led by the collection of requirements from scientific communities and international initiatives, provides a holistic approach that ranges from query languages and scalability up to mobile access and visualization. The result is demonstrated and validated through the development of lighthouse applications in the Marine, Geology, Atmospheric, Planetary and Cryospheric science domains

Genomic predictors of patterns of progression in glioblastoma and possible influences on radiation field design

We present a retrospective investigation of the role of genomics in the prediction of central versus marginal disease progression patterns for glioblastoma (GBM). Between August 2000 and May 2010, 41 patients with GBM and gene expression and methylation data available were treated with radiotherapy with or without concurrent temozolomide. Location of disease progression was categorized as within the high dose (60 Gy) or low dose (46 Gy) volume. Samples were grouped into previously described TCGA genomic groupings: Mesenchymal (m), classical (c), proneural (pn), and neural (n); and were also classified by MGMT-Methylation status and G-Cimp methylation phenotype. Genomic groupings and methylation status were investigated as a possible predictor of disease progression in the high dose region, progression in the low dose region, and time to progression. Based on TCGA category there was no difference in OS (p = 0.26), 60 Gy progression (PN: 71 %, N: 60 %, M: 89 %, C: 83 %, p = 0.19), 46 Gy progression (PN: 57 %, N: 40 %, M: 61 %, C: 50 %, p = 0.8) or time to progression (PN: 9 months, N:15 months, M: 9 months, C: 7 months, p = 0.58). MGMT methylation predicted for improved OS (median 25 vs. 13 months, p = 0.01), improved DFS (median 13 vs. 8 months, p = 0.007) and decreased 60 Gy (p = 0.003) and 46 Gy (p = 0.006) progression. There was a cohort of MGMT methylated patients with late marginal disease progression (4/22 patients, 18 %). TCGA groups demonstrated no difference in survival or progression patterns. MGMT methylation predicted for a statistically significant decrease in in-field and marginal disease progression. There was a cohort of MGMT methylated patients with late marginal progression. Validations of these findings would have implications that could affect radiation field size