Exploring the use of game making across the school curriculum

Computer games as part of education is a well-established topic for research, suggesting that creating games is linked to a range of cognitive and behavioural outcomes. Creating games in all subject disciplines is becoming increasingly possible due to the increasingly higher status of computing in schools across Europe and the prevalence of visual programming languages such as Scratch and Pocket Code. The use of games within education is not new; in a systematic review of 129 papers [1] found that playing games impacts across a range of areas including engagement, cognitive ability and, most commonly, knowledge acquisition and content understanding. However, while research has thus far examined game play and game based learning in education there is limited work focussing on the process of game creation as a method of classroom teaching. This is a prospect which is increasingly possible with the introduction of visual programming languages such as Scratch [2] and Pocket Code. It is suggested that playful learning through computer games could stimulate students’ intrinsic motivation ([3] and that knowledge creation can emerge through the construction of artefacts in a playful learning environment via the co-creation of games [4]. The research presented in this paper is from a pilot study examining the impact of game making in traditional primary and secondary school classrooms (5-18 years) in the United Kingdom (UK). The research, funded by Horizon 2020, is part of a wider European project; No-one Left Behind. In the UK the project has introduced game making into disciplines such as Religious Education, Science and History. Data indicates that although not all students found this a positive experience, computational thinking skills have increased, and students, disaffected with their learning, have re-engaged with learning, increasing their persistence and resulting in a deeper understanding of subject knowledge. In addition initial results suggest that game making has the potential to increase engagement with classroom learning and lead to increased learner satisfaction within lessons. Non-computing teachers have gained in confidence in developing game creation in their subject discipline, increasing their awareness of computational thinking. Barriers identified include teacher familiarity with programming as a means to teach non-STEM subject knowledge, a potential to decrease knowledge acquisition during the process of familiarisation with the teaching tool and a need for software developers to consider design for children with SEND. The project is changing the learning environment and emerging pedagogy has been identified which will be shared in this paper. As a result of the study lesson resources have been created for teachers to use across disciplines which are now available via the project URL; these will be shared in this paper

Characterisation of Salmonella enterica serotype Typhimurium isolates from wild birds in northern England from 2005 – 2006

<p>Abstract</p> <p>Background</p> <p>Several studies have shown that a number of serovars of <it>Salmonella enterica </it>may be isolated from wild birds, and it has been suggested that wild birds may play a role in the epidemiology of human and livestock salmonellosis. However, little is known about the relationship between wild bird <it>S. enterica </it>strains and human- and livestock- associated strains in the United Kingdom. Given the zoonotic potential of salmonellosis, the main aim of this study was to investigate the molecular epidemiology of <it>S. enterica </it>infections in wild birds in the north of England and, in particular, to determine if wild bird isolates were similar to those associated with disease in livestock or humans.</p> <p>Results</p> <p>Thirty two <it>Salmonella enterica </it>isolates were collected from wild birds in northern England between February 2005 and October 2006, of which 29 were <it>S. enterica </it>serovar Typhimurium (<it>S</it>. Typhimurium); one <it>S</it>. Newport, one <it>S</it>. Senftenberg, and one isolate could not be classified by serotyping. Further analysis through phage typing and macro-restriction pulsed-field gel electrophoresis indicated that wild passerine deaths associated with salmonellosis were caused by closely-related <it>S</it>. Typhimurium isolates, some of which were clonal. These isolates were susceptible to all antimicrobials tested, capable of invading and persisting within avian macrophage-like HD11 cells <it>in vitro</it>, and contained a range of virulence factors associated with both systemic and enteric infections of birds and mammals. However, all the isolates lacked the <it>sopE </it>gene associated with some human and livestock disease outbreaks caused by <it>S</it>. Typhimurium.</p> <p>Conclusion</p> <p>The wild bird isolates of <it>S. enterica </it>characterised in this investigation may not represent a large zoonotic risk. Molecular characterisation of isolates suggested that <it>S</it>. Typhimurium infection in wild passerines is maintained within wild bird populations and the causative strains may be host-adapted.</p

An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities

Artificial intelligence tools for education (AIEd) have been used to automate the provision of learning support to mainstream learners. One of the most innovative approaches in this field is the use of data and machine learning for the detection of a student's affective state, to move them out of negative states that inhibit learning, into positive states such as engagement. In spite of their obvious potential to provide the personalisation that would give extra support for learners with intellectual disabilities, little work on AIEd systems that utilise affect recognition currently addresses this group. Our system used multimodal sensor data and machine learning to first identify three affective states linked to learning (engagement, frustration, boredom) and second determine the presentation of learning content so that the learner is maintained in an optimal affective state and rate of learning is maximised. To evaluate this adaptive learning system, 67 participants aged between 6 and 18 years acting as their own control took part in a series of sessions using the system. Sessions alternated between using the system with both affect detection and learning achievement to drive the selection of learning content (intervention) and using learning achievement alone (control) to drive the selection of learning content. Lack of boredom was the state with the strongest link to achievement, with both frustration and engagement positively related to achievement. There was significantly more engagement and less boredom in intervention than control sessions, but no significant difference in achievement. These results suggest that engagement does increase when activities are tailored to the personal needs and emotional state of the learner and that the system was promoting affective states that in turn promote learning. However, longer exposure is necessary to determine the effect on learning

Enhancing biofeedback-driven self-guided virtual reality exposure therapy through arousal detection from multimodal data using machine learning

Virtual reality exposure therapy (VRET) is a novel intervention technique that allows individuals to experience anxiety-evoking stimuli in a safe environment, recognise specific triggers and gradually increase their exposure to perceived threats. Public-speaking anxiety (PSA) is a prevalent form of social anxiety, characterised by stressful arousal and anxiety generated when presenting to an audience. In self-guided VRET, participants can gradually increase their tolerance to exposure and reduce anxiety-induced arousal and PSA over time. However, creating such a VR environment and determining physiological indices of anxiety-induced arousal or distress is an open challenge. Environment modelling, character creation and animation, psychological state determination and the use of machine learning (ML) models for anxiety or stress detection are equally important, and multi-disciplinary expertise is required. In this work, we have explored a series of ML models with publicly available data sets (using electroencephalogram and heart rate variability) to predict arousal states. If we can detect anxiety-induced arousal, we can trigger calming activities to allow individuals to cope with and overcome distress. Here, we discuss the means of effective selection of ML models and parameters in arousal detection. We propose a pipeline to overcome the model selection problem with different parameter settings in the context of virtual reality exposure therapy. This pipeline can be extended to other domains of interest where arousal detection is crucial. Finally, we have implemented a biofeedback framework for VRET where we successfully provided feedback as a form of heart rate and brain laterality index from our acquired multimodal data for psychological intervention to overcome anxiety

Folding and organization of a contiguous chromosome region according to the gene distribution pattern in primary genomic sequence

Specific mammalian genes functionally and dynamically associate together within the nucleus. Yet, how an array of many genes along the chromosome sequence can be spatially organized and folded together is unknown. We investigated the 3D structure of a well-annotated, highly conserved 4.3-Mb region on mouse chromosome 14 that contains four clusters of genes separated by gene “deserts.” In nuclei, this region forms multiple, nonrandom “higher order” structures. These structures are based on the gene distribution pattern in primary sequence and are marked by preferential associations among multiple gene clusters. Associating gene clusters represent expressed chromatin, but their aggregation is not simply dependent on ongoing transcription. In chromosomes with aggregated gene clusters, gene deserts preferentially align with the nuclear periphery, providing evidence for chromosomal region architecture by specific associations with functional nuclear domains. Together, these data suggest dynamic, probabilistic 3D folding states for a contiguous megabase-scale chromosomal region, supporting the diverse activities of multiple genes and their conserved primary sequence organization

Dynamics of direct inter-pack encounters in endangered African wild dogs

Aggressive encounters may have important life history consequences due to the potential for injury and death, disease transmission, dispersal opportunities or exclusion from key areas of the home range. Despite this, little is known of their detailed dynamics, mainly due to the difficulties of directly observing encounters in detail. Here, we describe detailed spatial dynamics of inter-pack encounters in African wild dogs (Lycaon pictus), using data from custom-built high-resolution GPS collars in 11 free-ranging packs. On average, each pack encountered another pack approximately every 7 weeks and met each neighbour twice each year. Surprisingly, intruders were more likely to win encounters (winning 78.6% of encounters by remaining closer to the site in the short term). However, intruders did tend to move farther than residents toward their own range core in the short-term (1 h) post-encounter, and if this were used to indicate losing an encounter, then the majority (73.3%) of encounters were won by residents. Surprisingly, relative pack size had little effect on encounter outcome, and injuries were rare (<15% of encounters). These results highlight the difficulty of remotely scoring encounters involving mobile participants away from static defendable food resources. Although inter-pack range overlap was reduced following an encounter, encounter outcome did not seem to drive this, as both packs shifted their ranges post-encounter. Our results indicate that inter-pack encounters may be lower risk than previously suggested and do not appear to influence long-term movement and ranging

Smoking cigarettes of low nicotine yield does not reduce nicotine intake as expected: a study of nicotine dependency in Japanese males

BACKGROUND: Many Japanese believe that low-yield cigarettes are less hazardous than regular cigarettes, and many smokers consume low-yield cigarettes to reduce their risks from smoking. We evaluate the association between actual nicotine intake and brand nicotine yield, and the influence of nicotine dependence on this association. METHODS: The study subjects included 458 Japanese male smokers, aged 51.2 ± 9.9 years, who participated in health check-ups in a hospital in 1998 and 2000. Each subject filled out a self-administered smoking questionnaire and the score of each on the Fagerström Test for Nicotine Dependence was calculated. Urinary cotinine concentration was measured at the time of participation. RESULTS: The geometric mean of urinary cotinine concentration was 535 ng/mgCr for those who smoked brands with the lowest nicotine (0.1 mg on the package), compared with 1010 ng/mgCr for those who smoked brands with the highest (0.9–2.4 mg, weighted mean of 1.1 mg). Thus, despite the 11-fold ratio of nicotine yield on the packages, the ratio of urinary cotinine level was less than twofold. Both nicotine yield on the package and nicotine dependence significantly increased urinary cotinine concentration, and the negative interaction between them almost attained statistical significance. Cotinine concentration in heavily dependent smokers was consistently high regardless of the nicotine yield of brands. CONCLUSIONS: The nicotine yield of cigarettes measured by machine-smoking does not reliably predict the exposure of smokers. Smokers consuming low-yield nicotine cigarettes did not reduce actual intake of nicotine to the level that might be expected, especially for those heavily dependent on nicotine. Current labeling practices are misleading for the two-third of smokers who are moderately or highly dependent on nicotine

Impact of the British Lung Foundation Active Steps service on patient reported outcomes: (i) concurrent cohort study, (ii) process evaluation, (iii) economic evaluation. Presentations at European Respiratory Society International Congress 2021

Background: Active Steps is a remote behaviour change service supporting inactive adults with a lung condition to become physically active. Aim: To determine the efficacy of Active Steps in improving physical activity and quality life